An Efficient Hardware Circuit for Spike Sorting Based on Competitive Learning Networks

PubMed Central

Chen, Huan-Yuan; Chen, Chih-Chang

2017-01-01

This study aims to present an effective VLSI circuit for multi-channel spike sorting. The circuit supports the spike detection, feature extraction and classification operations. The detection circuit is implemented in accordance with the nonlinear energy operator algorithm. Both the peak detection and area computation operations are adopted for the realization of the hardware architecture for feature extraction. The resulting feature vectors are classified by a circuit for competitive learning (CL) neural networks. The CL circuit supports both online training and classification. In the proposed architecture, all the channels share the same detection, feature extraction, learning and classification circuits for a low area cost hardware implementation. The clock-gating technique is also employed for reducing the power dissipation. To evaluate the performance of the architecture, an application-specific integrated circuit (ASIC) implementation is presented. Experimental results demonstrate that the proposed circuit exhibits the advantages of a low chip area, a low power dissipation and a high classification success rate for spike sorting. PMID:28956859

ID card number detection algorithm based on convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Jian; Ma, Hanjie; Feng, Jie; Dai, Leiyan

2018-04-01

In this paper, a new detection algorithm based on Convolutional Neural Network is presented in order to realize the fast and convenient ID information extraction in multiple scenarios. The algorithm uses the mobile device equipped with Android operating system to locate and extract the ID number; Use the special color distribution of the ID card, select the appropriate channel component; Use the image threshold segmentation, noise processing and morphological processing to take the binary processing for image; At the same time, the image rotation and projection method are used for horizontal correction when image was tilting; Finally, the single character is extracted by the projection method, and recognized by using Convolutional Neural Network. Through test shows that, A single ID number image from the extraction to the identification time is about 80ms, the accuracy rate is about 99%, It can be applied to the actual production and living environment.

An approach to emotion recognition in single-channel EEG signals: a mother child interaction

NASA Astrophysics Data System (ADS)

Gómez, A.; Quintero, L.; López, N.; Castro, J.

2016-04-01

In this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains. Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadness.

Extraction of Inter-Aural Time Differences Using a Spiking Neuron Network Model of the Medial Superior Olive.

PubMed

Encke, Jörg; Hemmert, Werner

2018-01-01

The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs) which are first analyzed in the medial superior olive (MSO) in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.

Fractal Analysis of Drainage Basins on Mars

NASA Technical Reports Server (NTRS)

Stepinski, T. F.; Marinova, M. M.; McGovern, P. J.; Clifford, S. M.

2002-01-01

We used statistical properties of drainage networks on Mars as a measure of martian landscape morphology and an indicator of landscape evolution processes. We utilize the Mars Orbiter Laser Altimeter (MOLA) data to construct digital elevation maps (DEMs) of several, mostly ancient, martian terrains. Drainage basins and channel networks are computationally extracted from DEMs and their structures are analyzed and compared to drainage networks extracted from terrestrial and lunar DEMs. We show that martian networks are self-affine statistical fractals with planar properties similar to terrestrial networks, but vertical properties similar to lunar networks. The uniformity of martian drainage density is between those for terrestrial and lunar landscapes. Our results are consistent with the roughening of ancient martian terrains by combination of rainfall-fed erosion and impacts, although roughening by other fluvial processes cannot be excluded. The notion of sustained rainfall in recent Mars history is inconsistent with our findings.

A Novel Modulation Classification Approach Using Gabor Filter Network

PubMed Central

Ghauri, Sajjad Ahmed; Qureshi, Ijaz Mansoor; Cheema, Tanveer Ahmed; Malik, Aqdas Naveed

2014-01-01

A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the signal classification part. The Gabor atom parameters are tuned using Delta rule and updating of weights of Gabor filter using least mean square (LMS) algorithm. The simulation results show that proposed novel modulation classification algorithm has high classification accuracy at low signal to noise ratio (SNR) on AWGN channel. PMID:25126603

Patterns of Energy Drink Advertising over U.S. Television Networks

PubMed Central

Emond, Jennifer A.; Sargent, James D.; Gilbert-Diamond, Diane

2014-01-01

Objective To describe programming themes and the inclusion of adolescents in the base audience for television channels with high levels of energy drink ad airtime. Design Secondary analysis of energy drink ad airtime over U.S. network and cable television channels (n=139) March 2012-February 2013. Programming themes and the inclusion of adolescents in each channel's base audience were extracted from cable television trade reports. Main Outcome Measure Energy drink ad airtime. Analysis Channels were ranked by airtime; programming themes and the inclusion of adolescents in the base audience were summarized for the 10 channels with the most airtime. Results Over the study year, 36,501 minutes (608 hours) were devoted to energy drink ads; the top 10 channels accounted 46.5% of such airtime. Programming themes for the top 10 channels were music (n=3), sports (n=3), action-adventure lifestyle (n=2), African-American lifestyle (n=1) and comedy (n=1). MTV2 ranked first in airtime devoted to energy drink ads. Six of the 10 channels with the most airtime included adolescents aged 12-17 years in their base audience. Conclusions and Implications Energy drink manufacturers primarily advertise on channels that likely appeal to adolescents. Nutritionists may wish to consider energy drink media literacy when advising adolescents about energy drink consumption. PMID:25754297

Direct estimations of linear and nonlinear functionals of a quantum state.

PubMed

Ekert, Artur K; Alves, Carolina Moura; Oi, Daniel K L; Horodecki, Michał; Horodecki, Paweł; Kwek, L C

2002-05-27

We present a simple quantum network, based on the controlled-SWAP gate, that can extract certain properties of quantum states without recourse to quantum tomography. It can be used as a basic building block for direct quantum estimations of both linear and nonlinear functionals of any density operator. The network has many potential applications ranging from purity tests and eigenvalue estimations to direct characterization of some properties of quantum channels. Experimental realizations of the proposed network are within the reach of quantum technology that is currently being developed.

Patterns of energy drink advertising over US television networks.

PubMed

Emond, Jennifer A; Sargent, James D; Gilbert-Diamond, Diane

2015-01-01

To describe programming themes and the inclusion of adolescents in the base audience for television channels with high levels of energy drink advertising airtime. Secondary analysis of energy drink advertising airtime over US network and cable television channels (n = 139) from March, 2012 to February, 2013. Programming themes and the inclusion of adolescents in each channel's base audience were extracted from cable television trade reports. Energy drink advertising airtime. Channels were ranked by airtime; programming themes and the inclusion of adolescents in the base audience were summarized for the 10 channels with the most airtime. Over the study year, 36,501 minutes (608 hours) were devoted to energy drink advertisements; the top 10 channels accounted for 46.5% of such airtime. Programming themes for the top 10 channels were music (n = 3), sports (n = 3), action-adventure lifestyle (n = 2), African American lifestyle (n = 1), and comedy (n = 1). MTV2 ranked first in airtime devoted to energy drink advertisements. Six of the 10 channels with the most airtime included adolescents aged 12-17 years in their base audience. Energy drink manufacturers primarily advertise on channels that likely appeal to adolescents. Nutritionists may wish to consider energy drink media literacy when advising adolescents about energy drink consumption. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Semiconducting carbon nanotube network thin-film transistors with enhanced inkjet-printed source and drain contact interfaces

NASA Astrophysics Data System (ADS)

Lee, Yongwoo; Yoon, Jinsu; Choi, Bongsik; Lee, Heesung; Park, Jinhee; Jeon, Minsu; Han, Jungmin; Lee, Jieun; Kim, Yeamin; Kim, Dae Hwan; Kim, Dong Myong; Choi, Sung-Jin

2017-10-01

Carbon nanotubes (CNTs) are emerging materials for semiconducting channels in high-performance thin-film transistor (TFT) technology. However, there are concerns regarding the contact resistance (Rcontact) in CNT-TFTs, which limits the ultimate performance, especially the CNT-TFTs with the inkjet-printed source/drain (S/D) electrodes. Thus, the contact interfaces comprising the overlap between CNTs and metal S/D electrodes play a particularly dominant role in determining the performances and degree of variability in the CNT-TFTs with inkjet-printed S/D electrodes. In this work, the CNT-TFTs with improved device performance are demonstrated to enhance contact interfaces by controlling the CNT density at the network channel and underneath the inkjet-printed S/D electrodes during the formation of a CNT network channel. The origin of the improved device performance was systematically investigated by extracting Rcontact in the CNT-TFTs with the enhanced contact interfaces by depositing a high density of CNTs underneath the S/D electrodes, resulting in a 59% reduction in Rcontact; hence, the key performance metrics were correspondingly improved without sacrificing any other device metrics.

Controls on the spatial variability of supraglacial channel morphology and network characteristics

NASA Astrophysics Data System (ADS)

King, L.

2015-12-01

Supraglacial streams are widespread and ubiquitous features of glacial ice surfaces around the world. They play an important role in the spatial and temporal distribution of meltwater on a glacier, moderating the flux of meltwater to the bed. They are themselves unique fluvial features in which erosion and deposition is achieved through thermal erosion of ice rather than alluvial substrate. As such, they are of both glaciological and fluvial geomorphological interest for both practical and theoretical reasons. However, little is known about their characteristics through space and time, or how these characteristics reflect external driving forces. This research aims to address these gaps by characterizing the spatial variability of supraglacial stream morphology across a range of glacier types and environmental conditions and identifying forcings that control channel form. Topographic data was analyzed from a range of glacier surface types including icesheets, pocket alpine glaciers, and outlet valley glaciers spanning a range of latitudes and elevations, comprising glaciers from Greenland, British Columbia, Alaska, Iceland and Sweden. Channels were extracted from the topographic data using an automated approach based on identifying topographic depressions at different size scales, in which the method was tested relative to manually digitized stream networks. Channel geomorphology was subsequently characterized according to planimetric and drainage network geometries. Resulting morphometric characteristics were analyzed with regards to endo and exogenic environmental forcings such as ice topography and characteristics and climatic forcings to identify the primary controls on supraglacial channel morphology and the response of these channels with respect to these controls.

A Framework for Fracture Network Formation in Overpressurised Impermeable Shale: Deformability Versus Diagenesis

NASA Astrophysics Data System (ADS)

Alevizos, Sotiris; Poulet, Thomas; Sari, Mustafa; Lesueur, Martin; Regenauer-Lieb, Klaus; Veveakis, Manolis

2017-03-01

Understanding the formation, geometry and fluid connectivity of nominally impermeable unconventional shale gas and oil reservoirs is crucial for safe unlocking of these vast energy resources. We present a recent discovery of volumetric instabilities of ductile materials that may explain why impermeable formations become permeable. Here, we present the fundamental mechanisms, the critical parameters and the applicability of the novel theory to unconventional reservoirs. We show that for a reservoir under compaction, there exist certain ambient and permeability conditions at which diagenetic (fluid-release) reactions may provoke channelling localisation instabilities. These channels are periodically interspersed in the matrix and represent areas where the excess fluid from the reaction is segregated at high velocity. We find that channelling instabilities are favoured from pore collapse features for extremely low-permeability formations and fluid-release diagenetic reactions, therefore providing a natural, periodic network of efficient fluid pathways in an otherwise impermeable matrix (i.e. fractures). Such an outcome is of extreme importance the for exploration and extraction phases of unconventional reservoirs.

Extraction of Built-Up Areas Using Convolutional Neural Networks and Transfer Learning from SENTINEL-2 Satellite Images

NASA Astrophysics Data System (ADS)

Bramhe, V. S.; Ghosh, S. K.; Garg, P. K.

2018-04-01

With rapid globalization, the extent of built-up areas is continuously increasing. Extraction of features for classifying built-up areas that are more robust and abstract is a leading research topic from past many years. Although, various studies have been carried out where spatial information along with spectral features has been utilized to enhance the accuracy of classification. Still, these feature extraction techniques require a large number of user-specific parameters and generally application specific. On the other hand, recently introduced Deep Learning (DL) techniques requires less number of parameters to represent more abstract aspects of the data without any manual effort. Since, it is difficult to acquire high-resolution datasets for applications that require large scale monitoring of areas. Therefore, in this study Sentinel-2 image has been used for built-up areas extraction. In this work, pre-trained Convolutional Neural Networks (ConvNets) i.e. Inception v3 and VGGNet are employed for transfer learning. Since these networks are trained on generic images of ImageNet dataset which are having very different characteristics from satellite images. Therefore, weights of networks are fine-tuned using data derived from Sentinel-2 images. To compare the accuracies with existing shallow networks, two state of art classifiers i.e. Gaussian Support Vector Machine (SVM) and Back-Propagation Neural Network (BP-NN) are also implemented. Both SVM and BP-NN gives 84.31 % and 82.86 % overall accuracies respectively. Inception-v3 and VGGNet gives 89.43 % of overall accuracy using fine-tuned VGGNet and 92.10 % when using Inception-v3. The results indicate high accuracy of proposed fine-tuned ConvNets on a 4-channel Sentinel-2 dataset for built-up area extraction.

Channels selection using independent component analysis and scalp map projection for EEG-based driver fatigue classification.

PubMed

Rifai Chai; Naik, Ganesh R; Sai Ho Ling; Tran, Yvonne; Craig, Ashley; Nguyen, Hung T

2017-07-01

This paper presents a classification of driver fatigue with electroencephalography (EEG) channels selection analysis. The system employs independent component analysis (ICA) with scalp map back projection to select the dominant of EEG channels. After channel selection, the features of the selected EEG channels were extracted based on power spectral density (PSD), and then classified using a Bayesian neural network. The results of the ICA decomposition with the back-projected scalp map and a threshold showed that the EEG channels can be reduced from 32 channels into 16 dominants channels involved in fatigue assessment as chosen channels, which included AF3, F3, FC1, FC5, T7, CP5, P3, O1, P4, P8, CP6, T8, FC2, F8, AF4, FP2. The result of fatigue vs. alert classification of the selected 16 channels yielded a sensitivity of 76.8%, specificity of 74.3% and an accuracy of 75.5%. Also, the classification results of the selected 16 channels are comparable to those using the original 32 channels. So, the selected 16 channels is preferable for ergonomics improvement of EEG-based fatigue classification system.

Automated extraction of metadata from remotely sensed satellite imagery

NASA Technical Reports Server (NTRS)

Cromp, Robert F.

1991-01-01

The paper discusses research in the Intelligent Data Management project at the NASA/Goddard Space Flight Center, with emphasis on recent improvements in low-level feature detection algorithms for performing real-time characterization of images. Images, including MSS and TM data, are characterized using neural networks and the interpretation of the neural network output by an expert system for subsequent archiving in an object-oriented data base. The data show the applicability of this approach to different arrangements of low-level remote sensing channels. The technique works well when the neural network is trained on data similar to the data used for testing.

Extraction of a Weak Co-Channel Interfering Communication Signal Using Complex Independent Component Analysis

DTIC Science & Technology

2013-06-01

zarzoso/ biblio /tnn10.pdf"> % "Robust independent component analysis by iterative maximization</a> % <a href = "http://www.i3s.unice.fr/~zarzoso... biblio /tnn10.pdf"> % of the kurtosis contrast with algebraic optimal step size"</a>, % IEEE Transactions on Neural Networks, vol. 21, no. 2, % pp

High-efficient Extraction of Drainage Networks from Digital Elevation Model Data Constrained by Enhanced Flow Enforcement from Known River Map

NASA Astrophysics Data System (ADS)

Wu, T.; Li, T.; Li, J.; Wang, G.

2017-12-01

Improved drainage network extraction can be achieved by flow enforcement whereby information of known river maps is imposed to the flow-path modeling process. However, the common elevation-based stream burning method can sometimes cause unintended topological errors and misinterpret the overall drainage pattern. We presented an enhanced flow enforcement method to facilitate accurate and efficient process of drainage network extraction. Both the topology of the mapped hydrography and the initial landscape of the DEM are well preserved and fully utilized in the proposed method. An improved stream rasterization is achieved here, yielding continuous, unambiguous and stream-collision-free raster equivalent of stream vectors for flow enforcement. By imposing priority-based enforcement with a complementary flow direction enhancement procedure, the drainage patterns of the mapped hydrography are fully represented in the derived results. The proposed method was tested over the Rogue River Basin, using DEMs with various resolutions. As indicated by the visual and statistical analyses, the proposed method has three major advantages: (1) it significantly reduces the occurrences of topological errors, yielding very accurate watershed partition and channel delineation, (2) it ensures scale-consistent performance at DEMs of various resolutions, and (3) the entire extraction process is well-designed to achieve great computational efficiency.

CALYPSO: a new HF RADAR network to monitor sea surface currents in the Malta-Sicily channel (Mediterranean sea)

NASA Astrophysics Data System (ADS)

Cosoli, S.; Ciraolo, G.; Drago, A.; Capodici, F.; Maltese, A.; Gauci, A.; Galea, A.; Azzopardi, J.; Buscaino, G.; Raffa, F.; Mazzola, S.; Sinatra, R.

2016-12-01

Located in one of the main shipping lanes in the Mediterranean Sea, and in a strategic region for oil extraction platforms, the Malta-Sicily channel is exposed to significant oil spill risks. Shipping and extraction activities constitute a major threat for marine areas of relevant ecological value in the area, and impacts of oil spills on the local ecosystems and the economic activities, including tourism and fisheries, can be dramatic. Damages would be even more devastating for the Maltese archipelago, where marine resources represent important economic assets. Additionally, North Africa coastal areas are also under threat, due to their proximity to the Malta-Sicily Channel. Prevention and mitigation measures, together with rapid-response and decision-making in case of emergency situations, are fundamental steps that help accomplishing the tasks of minimizing risks and reducing impacts to the various compartments. Thanks to state-of-art technology for the monitoring of sea-surface currents in real-time under all sea-state conditions, the CALYPSO network of High-Frequency Radars represents an essential and invaluable tool for the specific purpose. HF radars technology provide a unique tool to track surface currents in near-real time, and as such the dispersion of pollutants can be monitored and forecasted and their origin backtracked, for instance through data assimilation into ocean circulation models or through short-term data-driven statistical forecasts of ocean currents. The network is constituted of four SeaSonde systems that work in the 13.5MHz frequency band. The network is operative since August 2012 and has been extensively validated using a variety of independent platforms and devices, including current meter data and drifting buoys. The latter provided clear evidences of the reliability of the collected data as for tracking the drifting objects. Additionally, data have provided a new insight into the oceanographic characteristics of the region, documenting the presence of a number of previously unreported features. The observing network represents an unique opportunity that exploit HF radar in coastal seas to meet Europe's needs for operational mapping of the surface ocean. Additionally, it provides expertise and support for a new generation of scientists and technical staff.

Rain/No-Rain Identification from Bispectral Satellite Information using Deep Neural Networks

NASA Astrophysics Data System (ADS)

Tao, Y.

2016-12-01

Satellite-based precipitation estimation products have the advantage of high resolution and global coverage. However, they still suffer from insufficient accuracy. To accurately estimate precipitation from satellite data, there are two most important aspects: sufficient precipitation information in the satellite information and proper methodologies to extract such information effectively. This study applies the state-of-the-art machine learning methodologies to bispectral satellite information for Rain/No-Rain detection. Specifically, we use deep neural networks to extract features from infrared and water vapor channels and connect it to precipitation identification. To evaluate the effectiveness of the methodology, we first applies it to the infrared data only (Model DL-IR only), the most commonly used inputs for satellite-based precipitation estimation. Then we incorporates water vapor data (Model DL-IR + WV) to further improve the prediction performance. Radar stage IV dataset is used as ground measurement for parameter calibration. The operational product, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), is used as a reference to compare the performance of both models in both winter and summer seasons.The experiments show significant improvement for both models in precipitation identification. The overall performance gains in the Critical Success Index (CSI) are 21.60% and 43.66% over the verification periods for Model DL-IR only and Model DL-IR+WV model compared to PERSIANN-CCS, respectively. Moreover, specific case studies show that the water vapor channel information and the deep neural networks effectively help recover a large number of missing precipitation pixels under warm clouds while reducing false alarms under cold clouds.

Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines (nifedipine analogous).

PubMed

Hemmateenejad, Bahram; Akhond, Morteza; Miri, Ramin; Shamsipur, Mojtaba

2003-01-01

A QSAR algorithm, principal component-genetic algorithm-artificial neural network (PC-GA-ANN), has been applied to a set of newly synthesized calcium channel blockers, which are of special interest because of their role in cardiac diseases. A data set of 124 1,4-dihydropyridines bearing different ester substituents at the C-3 and C-5 positions of the dihydropyridine ring and nitroimidazolyl, phenylimidazolyl, and methylsulfonylimidazolyl groups at the C-4 position with known Ca(2+) channel binding affinities was employed in this study. Ten different sets of descriptors (837 descriptors) were calculated for each molecule. The principal component analysis was used to compress the descriptor groups into principal components. The most significant descriptors of each set were selected and used as input for the ANN. The genetic algorithm (GA) was used for the selection of the best set of extracted principal components. A feed forward artificial neural network with a back-propagation of error algorithm was used to process the nonlinear relationship between the selected principal components and biological activity of the dihydropyridines. A comparison between PC-GA-ANN and routine PC-ANN shows that the first model yields better prediction ability.

Identifying the Minimum Model Features to Replicate Historic Morphodynamics of a Juvenile Delta

NASA Astrophysics Data System (ADS)

Czapiga, M. J.; Parker, G.

2017-12-01

We introduce a quasi-2D morphodynamic delta model that improves on past models that require many simplifying assumptions, e.g. a single channel representative of a channel network, fixed channel width, and spatially uniform deposition. Our model is useful for studying long-term progradation rates of any generic micro-tidal delta system with specification of: characteristic grain size, input water and sediment discharges and basin morphology. In particular, we relax the assumption of a single, implicit channel sweeping across the delta topset in favor of an implicit channel network. This network, coupled with recent research on channel-forming Shields number, quantitative assessments of the lateral depositional length of sand (corresponding loosely to levees) and length between bifurcations create a spatial web of deposition within the receiving basin. The depositional web includes spatial boundaries for areas infilling with sands carried as bed material load, as well as those filling via passive deposition of washload mud. Our main goal is to identify the minimum features necessary to accurately model the morphodynamics of channel number, width, depth, and overall delta progradation rate in a juvenile delta. We use the Wax Lake Delta in Louisiana as a test site due to its rapid growth in the last 40 years. Field data including topset/island bathymetry, channel bathymetry, topset/island width, channel width, number of channels, and radial topset length are compiled from US Army Corps of Engineers data for 1989, 1998, and 2006. Additional data is extracted from a DEM from 2015. These data are used as benchmarks for the hindcast model runs. The morphology of Wax Lake Delta is also strongly affected by a pre-delta substrate that acts as a lower "bedrock" boundary. Therefore, we also include closures for a bedrock-alluvial transition and an excess shear rate-law incision model to estimate bedrock incision. The model's framework is generic, but inclusion of individual sub-models, such as those mentioned above, allow us to answer basic research questions without the parameterization necessary in higher resolution models. Thus, this type of model offers an alternative to higher-resolution models.

Modeling Music Emotion Judgments Using Machine Learning Methods

PubMed Central

Vempala, Naresh N.; Russo, Frank A.

2018-01-01

Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML) methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that were used for modeling, we conclude that neural networks were optimal, yielding models that were flexible as well as interpretable. Inspection of a committee machine, encompassing an ensemble of networks, revealed that arousal judgments were predominantly influenced by felt emotion, whereas valence judgments were predominantly influenced by perceived emotion. PMID:29354080

Modeling Music Emotion Judgments Using Machine Learning Methods.

PubMed

Vempala, Naresh N; Russo, Frank A

2017-01-01

Emotion judgments and five channels of physiological data were obtained from 60 participants listening to 60 music excerpts. Various machine learning (ML) methods were used to model the emotion judgments inclusive of neural networks, linear regression, and random forests. Input for models of perceived emotion consisted of audio features extracted from the music recordings. Input for models of felt emotion consisted of physiological features extracted from the physiological recordings. Models were trained and interpreted with consideration of the classic debate in music emotion between cognitivists and emotivists. Our models supported a hybrid position wherein emotion judgments were influenced by a combination of perceived and felt emotions. In comparing the different ML approaches that were used for modeling, we conclude that neural networks were optimal, yielding models that were flexible as well as interpretable. Inspection of a committee machine, encompassing an ensemble of networks, revealed that arousal judgments were predominantly influenced by felt emotion, whereas valence judgments were predominantly influenced by perceived emotion.

Single-channel EEG-based mental fatigue detection based on deep belief network.

PubMed

Pinyi Li; Wenhui Jiang; Fei Su

2016-08-01

Mental fatigue has a pernicious influence on road and work place safety as well as a negative symptom of many acute and chronic illnesses, since the ability of concentrating, responding and judging quickly decreases during the fatigue or drowsiness stage. Electroencephalography (EEG) has been proven to be a robust physiological indicator of human cognitive state over the last few decades. But most existing EEG-based fatigue detection methods have poor performance in accuracy. This paper proposed a single-channel EEG-based mental fatigue detection method based on Deep Belief Network (DBN). The fused nonliear features from specified sub-bands and dynamic analysis, a total of 21 features are extracted as the input of the DBN to discriminate three classes of mental state including alert, slight fatigue and severe fatigue. Experimental results show the good performance of the proposed model comparing with those state-of-art methods.

Salt marsh vegetation promotes efficient tidal channel networks

PubMed Central

Kearney, William S.; Fagherazzi, Sergio

2016-01-01

Tidal channel networks mediate the exchange of water, nutrients and sediment between an estuary and marshes. Biology feeds back into channel morphodynamics through the influence of vegetation on both flow and the cohesive strength of channel banks. Determining how vegetation affects channel networks is essential in understanding the biological functioning of intertidal ecosystems and their ecosystem services. However, the processes that control the formation of an efficient tidal channel network remain unclear. Here we compare the channel networks of vegetated salt marshes in Massachusetts and the Venice Lagoon to unvegetated systems in the arid environments of the Gulf of California and Yemen. We find that the unvegetated systems are dissected by less efficient channel networks than the vegetated salt marshes. These differences in network geometry reflect differences in the branching and meandering of the channels in the network, characteristics that are related to the density of vegetation on the marsh. PMID:27430165

Utilizing Lidar Data for Detection of Channel Migration: Taylor Valley, Antarctica

NASA Astrophysics Data System (ADS)

Barlow, M. C.; Telling, J. W.; Glennie, C.; Fountain, A.

2017-12-01

The McMurdo Dry Valleys is the largest ice-free expanse in Antarctica and one of the most studied regions on the continent. The valleys are a hyper-arid, cold-polar desert that receives little precipitation (<50 mm weq yr-1). The valley bottoms are covered in a sandy-gravel, dotted with ice-covered lakes and ponds, and alpine glaciers that descend from the surrounding mountains. Glacial melt feeds the lakes via ephemeral streams that flow 6 - 10 weeks each summer. Field observations indicate that the valley floors, particularly in Taylor Valley, contain numerous abandoned stream channels but, given the modest stream flows, channel migration is rarely observed. Only a few channels have been surveyed in the field due to the slow pace of manual methods. Here we present a method to assess channel migration over a broad region in order to study the pattern of channel migration as a function of climatic and/or geologic gradients in Taylor Valley. Raster images of high-resolution topography were created from two lidar (Light Detection and Ranging) datasets and were used to analyze channel migration in Taylor Valley. The first lidar dataset was collected in 2001 by NASA's Airborne Topographic Mapper (ATM) and the second was collected by the National Center for Airborne Laser Mapping (NCALM) in 2014 with an Optech Titan Sensor. The channels were extracted for each dataset using GeoNet, which is an open source tool used for the automatic extraction of channel networks. Channel migration was found to range from 0 to 50 cm per year depending upon the location. Channel complexity was determined based on the change in the number of channel branches and their length. We present the results for various regions in Taylor Valley with differing degrees of stream complexity. Further research is being done to determine factors that drive channel migration rates in this unique environment.

Emancipating traditional channel network types: quantification of topology and geometry, and relation to geologic boundary conditions

NASA Astrophysics Data System (ADS)

Temme, A.; Langston, A. L.

2017-12-01

Traditional classification of channel networks is helpful for qualitative geologic and geomorphic inference. For instance, a dendritic network indicates no strong lithological control on where channels flow. However, an approach where channel network structure is quantified, is required to be able to indicate for instance how increasing levels of lithological control lead, gradually or suddenly, to a trellis-type drainage network Our contribution aims to aid this transition to a quantitative analysis of channel networks. First, to establish the range of typically occurring channel network properties, we selected 30 examples of traditional drainage network types from around the world. For each of these, we calculated a set of topological and geometric properties, such as total drainage length, average length of a channel segment and the average angle of intersection of channel segments. A decision tree was used to formalize the relation between these newly quantified properties on the one hand, and traditional network types on the other hand. Then, to explore how variations in lithological and geomorphic boundary conditions affect channel network structure, we ran a set of experiments with landscape evolution model Landlab. For each simulated channel network, the same set of topological and geometric properties was calculated as for the 30 real-world channel networks. The latter were used for a first, visual evaluation to find out whether a simulated network that looked, for instance, rectangular, also had the same set of properties as real-world rectangular channel networks. Ultimately, the relation between these properties and the imposed lithological and geomorphic boundary conditions was explored using simple bivariate statistics.

Dynamics in steady state in vitro acto-myosin networks

NASA Astrophysics Data System (ADS)

Sonn-Segev, Adar; Bernheim-Groswasser, Anne; Roichman, Yael

2017-04-01

It is well known that many biochemical processes in the cell such as gene regulation, growth signals and activation of ion channels, rely on mechanical stimuli. However, the mechanism by which mechanical signals propagate through cells is not as well understood. In this review we focus on stress propagation in a minimal model for cell elasticity, actomyosin networks, which are comprised of a sub-family of cytoskeleton proteins. After giving an overview of th actomyosin network components, structure and evolution we review stress propagation in these materials as measured through the correlated motion of tracer beads. We also discuss the possibility to extract structural features of these networks from the same experiments. We show that stress transmission through these networks has two pathways, a quickly dissipative one through the bulk, and a long ranged weakly dissipative one through the pre-stressed actin network.

Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

NASA Astrophysics Data System (ADS)

Coffey, T.

2016-12-01

Distributary channel bifurcations on river deltas are important features in both modern systems, where the channels control water, sediment, and nutrient routing, and in ancient deltas, where the channel networks can dictate large-scale stratigraphic heterogeneity. Geometric features of distributary channels, such as channel dimensions and network structure, have long been thought to be defined by factors such as flow velocity, grain size, or channel aspect ratio where the channel enters the basin. We use theory originally developed for tributary networks fed by groundwater seepage to understand the dynamics of distributary channel bifurcations. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to evolve dependent on the diffusive flow patterns around the channel network. These networks possess a characteristic bifurcation angle of 72°, due to Laplacian flow (gradient2h2=0, where h is water surface elevation) in the groundwater flow field near tributary channel tips. We develop and test the hypothesis that bifurcation angles in distributary channel networks are likewise dictated by the external flow field, in this case the shallow surface water surrounding the subaqueous portion of distributary channel bifurcations in a deltaic setting. We measured 130 unique distributary channel bifurcations in a single experimental delta and in 10 natural deltas, yielding a mean angle of 70.35°±2.59° (95% confidence interval), in line with the theoretical prediction. This similarity implies that flow outside of the distributary channel network is also Laplacian, which we use scaling arguments to justify. We conclude that the dynamics of the unchannelized flow control bifurcation formation in distributary networks.

Reactive immunization on complex networks

NASA Astrophysics Data System (ADS)

Alfinito, Eleonora; Beccaria, Matteo; Fachechi, Alberto; Macorini, Guido

2017-01-01

Epidemic spreading on complex networks depends on the topological structure as well as on the dynamical properties of the infection itself. Generally speaking, highly connected individuals play the role of hubs and are crucial to channel information across the network. On the other hand, static topological quantities measuring the connectivity structure are independent of the dynamical mechanisms of the infection. A natural question is therefore how to improve the topological analysis by some kind of dynamical information that may be extracted from the ongoing infection itself. In this spirit, we propose a novel vaccination scheme that exploits information from the details of the infection pattern at the moment when the vaccination strategy is applied. Numerical simulations of the infection process show that the proposed immunization strategy is effective and robust on a wide class of complex networks.

From Understanding Cellular Function to Novel Drug Discovery: The Role of Planar Patch-Clamp Array Chip Technology

PubMed Central

Py, Christophe; Martina, Marzia; Diaz-Quijada, Gerardo A.; Luk, Collin C.; Martinez, Dolores; Denhoff, Mike W.; Charrier, Anne; Comas, Tanya; Monette, Robert; Krantis, Anthony; Syed, Naweed I.; Mealing, Geoffrey A. R.

2011-01-01

All excitable cell functions rely upon ion channels that are embedded in their plasma membrane. Perturbations of ion channel structure or function result in pathologies ranging from cardiac dysfunction to neurodegenerative disorders. Consequently, to understand the functions of excitable cells and to remedy their pathophysiology, it is important to understand the ion channel functions under various experimental conditions – including exposure to novel drug targets. Glass pipette patch-clamp is the state of the art technique to monitor the intrinsic and synaptic properties of neurons. However, this technique is labor intensive and has low data throughput. Planar patch-clamp chips, integrated into automated systems, offer high throughputs but are limited to isolated cells from suspensions, thus limiting their use in modeling physiological function. These chips are therefore not most suitable for studies involving neuronal communication. Multielectrode arrays (MEAs), in contrast, have the ability to monitor network activity by measuring local field potentials from multiple extracellular sites, but specific ion channel activity is challenging to extract from these multiplexed signals. Here we describe a novel planar patch-clamp chip technology that enables the simultaneous high-resolution electrophysiological interrogation of individual neurons at multiple sites in synaptically connected neuronal networks, thereby combining the advantages of MEA and patch-clamp techniques. Each neuron can be probed through an aperture that connects to a dedicated subterranean microfluidic channel. Neurons growing in networks are aligned to the apertures by physisorbed or chemisorbed chemical cues. In this review, we describe the design and fabrication process of these chips, approaches to chemical patterning for cell placement, and present physiological data from cultured neuronal cells. PMID:22007170

From understanding cellular function to novel drug discovery: the role of planar patch-clamp array chip technology.

PubMed

Py, Christophe; Martina, Marzia; Diaz-Quijada, Gerardo A; Luk, Collin C; Martinez, Dolores; Denhoff, Mike W; Charrier, Anne; Comas, Tanya; Monette, Robert; Krantis, Anthony; Syed, Naweed I; Mealing, Geoffrey A R

2011-01-01

All excitable cell functions rely upon ion channels that are embedded in their plasma membrane. Perturbations of ion channel structure or function result in pathologies ranging from cardiac dysfunction to neurodegenerative disorders. Consequently, to understand the functions of excitable cells and to remedy their pathophysiology, it is important to understand the ion channel functions under various experimental conditions - including exposure to novel drug targets. Glass pipette patch-clamp is the state of the art technique to monitor the intrinsic and synaptic properties of neurons. However, this technique is labor intensive and has low data throughput. Planar patch-clamp chips, integrated into automated systems, offer high throughputs but are limited to isolated cells from suspensions, thus limiting their use in modeling physiological function. These chips are therefore not most suitable for studies involving neuronal communication. Multielectrode arrays (MEAs), in contrast, have the ability to monitor network activity by measuring local field potentials from multiple extracellular sites, but specific ion channel activity is challenging to extract from these multiplexed signals. Here we describe a novel planar patch-clamp chip technology that enables the simultaneous high-resolution electrophysiological interrogation of individual neurons at multiple sites in synaptically connected neuronal networks, thereby combining the advantages of MEA and patch-clamp techniques. Each neuron can be probed through an aperture that connects to a dedicated subterranean microfluidic channel. Neurons growing in networks are aligned to the apertures by physisorbed or chemisorbed chemical cues. In this review, we describe the design and fabrication process of these chips, approaches to chemical patterning for cell placement, and present physiological data from cultured neuronal cells.

Effects of channel noise on firing coherence of small-world Hodgkin-Huxley neuronal networks

NASA Astrophysics Data System (ADS)

Sun, X. J.; Lei, J. Z.; Perc, M.; Lu, Q. S.; Lv, S. J.

2011-01-01

We investigate the effects of channel noise on firing coherence of Watts-Strogatz small-world networks consisting of biophysically realistic HH neurons having a fraction of blocked voltage-gated sodium and potassium ion channels embedded in their neuronal membranes. The intensity of channel noise is determined by the number of non-blocked ion channels, which depends on the fraction of working ion channels and the membrane patch size with the assumption of homogeneous ion channel density. We find that firing coherence of the neuronal network can be either enhanced or reduced depending on the source of channel noise. As shown in this paper, sodium channel noise reduces firing coherence of neuronal networks; in contrast, potassium channel noise enhances it. Furthermore, compared with potassium channel noise, sodium channel noise plays a dominant role in affecting firing coherence of the neuronal network. Moreover, we declare that the observed phenomena are independent of the rewiring probability.

A multichannel nonlinear adaptive noise canceller based on generalized FLANN for fetal ECG extraction

NASA Astrophysics Data System (ADS)

Ma, Yaping; Xiao, Yegui; Wei, Guo; Sun, Jinwei

2016-01-01

In this paper, a multichannel nonlinear adaptive noise canceller (ANC) based on the generalized functional link artificial neural network (FLANN, GFLANN) is proposed for fetal electrocardiogram (FECG) extraction. A FIR filter and a GFLANN are equipped in parallel in each reference channel to respectively approximate the linearity and nonlinearity between the maternal ECG (MECG) and the composite abdominal ECG (AECG). A fast scheme is also introduced to reduce the computational cost of the FLANN and the GFLANN. Two (2) sets of ECG time sequences, one synthetic and one real, are utilized to demonstrate the improved effectiveness of the proposed nonlinear ANC. The real dataset is derived from the Physionet non-invasive FECG database (PNIFECGDB) including 55 multichannel recordings taken from a pregnant woman. It contains two subdatasets that consist of 14 and 8 recordings, respectively, with each recording being 90 s long. Simulation results based on these two datasets reveal, on the whole, that the proposed ANC does enjoy higher capability to deal with nonlinearity between MECG and AECG as compared with previous ANCs in terms of fetal QRS (FQRS)-related statistics and morphology of the extracted FECG waveforms. In particular, for the second real subdataset, the F1-measure results produced by the PCA-based template subtraction (TSpca) technique and six (6) single-reference channel ANCs using LMS- and RLS-based FIR filters, Volterra filter, FLANN, GFLANN, and adaptive echo state neural network (ESN a ) are 92.47%, 93.70%, 94.07%, 94.22%, 94.90%, 94.90%, and 95.46%, respectively. The same F1-measure statistical results from five (5) multi-reference channel ANCs (LMS- and RLS-based FIR filters, Volterra filter, FLANN, and GFLANN) for the second real subdataset turn out to be 94.08%, 94.29%, 94.68%, 94.91%, and 94.96%, respectively. These results indicate that the ESN a and GFLANN perform best, with the ESN a being slightly better than the GFLANN but about four times more computationally expensive than the GFLANN, which makes the GFLANN a good alternative for NI-FECG extraction.

Improvement of proteolytic efficiency towards low-level proteins by an antifouling surface of alumina gel in a microchannel.

PubMed

Liu, Yun; Wang, Huixiang; Liu, Qingping; Qu, Haiyun; Liu, Baohong; Yang, Pengyuan

2010-11-07

A microfluidic reactor has been developed for rapid enhancement of protein digestion by constructing an alumina network within a poly(ethylene terephthalate) (PET) microchannel. Trypsin is stably immobilized in a sol-gel network on the PET channel surface after pretreatment, which produces a protein-resistant interface to reduce memory effects, as characterized by X-ray fluorescence spectrometry and electroosmotic flow. The gel-derived network within a microchannel provides a large surface-to-volume ratio stationary phase for highly efficient proteolysis of proteins existing both at a low level and in complex extracts. The maximum reaction rate of the encapsulated trypsin reactor, measured by kinetic analysis, is much faster than in bulk solution. Due to the microscopic confinement effect, high levels of enzyme entrapment and the biocompatible microenvironment provided by the alumina gel network, the low-level proteins can be efficiently digested using such a microreactor within a very short residence time of a few seconds. The on-chip microreactor is further applied to the identification of a mixture of proteins extracted from normal mouse liver cytoplasm sample via integration with 2D-LC-ESI-MS/MS to show its potential application for large-scale protein identification.

Bank gully extraction from DEMs utilizing the geomorphologic features of a loess hilly area in China

NASA Astrophysics Data System (ADS)

Yang, Xin; Na, Jiaming; Tang, Guoan; Wang, Tingting; Zhu, Axing

2018-04-01

As one of most active gully types in the Chinese Loess Plateau, bank gullies generally indicate soil loss and land degradation. This study addressed the lack of detailed, large scale monitoring of bank gullies and proposed a semi-automatic method for extracting bank gullies, given typical topographic features based on 5 m resolution DEMs. First, channel networks, including bank gullies, are extracted through an iterative channel burn-in algorithm. Second, gully heads are correctly positioned based on the spatial relationship between gully heads and their corresponding gully shoulder lines. Third, bank gullies are distinguished from other gullies using the newly proposed topographic measurement of "relative gully depth (RGD)." The experimental results from the loess hilly area of the Linjiajian watershed in the Chinese Loess Plateau show that the producer accuracy reaches 87.5%. The accuracy is affected by the DEM resolution and RGD parameters, as well as the accuracy of the gully shoulder line. The application in the Madigou watershed with a high DEM resolution validated the duplicability of this method in other areas. The overall performance shows that bank gullies can be extracted with acceptable accuracy over a large area, which provides essential information for research on soil erosion, geomorphology, and environmental ecology.

Electrical characteristics of silicon percolating nanonet-based field effect transistors in the presence of dispersion

NASA Astrophysics Data System (ADS)

Cazimajou, T.; Legallais, M.; Mouis, M.; Ternon, C.; Salem, B.; Ghibaudo, G.

2018-05-01

We studied the current-voltage characteristics of percolating networks of silicon nanowires (nanonets), operated in back-gated transistor mode, for future use as gas or biosensors. These devices featured P-type field-effect characteristics. It was found that a Lambert W function-based compact model could be used for parameter extraction of electrical parameters such as apparent low field mobility, threshold voltage and subthreshold slope ideality factor. Their variation with channel length and nanowire density was related to the change of conduction regime from direct source/drain connection by parallel nanowires to percolating channels. Experimental results could be related in part to an influence of the threshold voltage dispersion of individual nanowires.

Channel Noise-Enhanced Synchronization Transitions Induced by Time Delay in Adaptive Neuronal Networks with Spike-Timing-Dependent Plasticity

NASA Astrophysics Data System (ADS)

Xie, Huijuan; Gong, Yubing; Wang, Baoying

In this paper, we numerically study the effect of channel noise on synchronization transitions induced by time delay in adaptive scale-free Hodgkin-Huxley neuronal networks with spike-timing-dependent plasticity (STDP). It is found that synchronization transitions by time delay vary as channel noise intensity is changed and become most pronounced when channel noise intensity is optimal. This phenomenon depends on STDP and network average degree, and it can be either enhanced or suppressed as network average degree increases depending on channel noise intensity. These results show that there are optimal channel noise and network average degree that can enhance the synchronization transitions by time delay in the adaptive neuronal networks. These findings could be helpful for better understanding of the regulation effect of channel noise on synchronization of neuronal networks. They could find potential implications for information transmission in neural systems.

Fat fractal scaling of drainage networks from a random spatial network model

USGS Publications Warehouse

Karlinger, Michael R.; Troutman, Brent M.

1992-01-01

An alternative quantification of the scaling properties of river channel networks is explored using a spatial network model. Whereas scaling descriptions of drainage networks previously have been presented using a fractal analysis primarily of the channel lengths, we illustrate the scaling of the surface area of the channels defining the network pattern with an exponent which is independent of the fractal dimension but not of the fractal nature of the network. The methodology presented is a fat fractal analysis in which the drainage basin minus the channel area is considered the fat fractal. Random channel networks within a fixed basin area are generated on grids of different scales. The sample channel networks generated by the model have a common outlet of fixed width and a rule of upstream channel narrowing specified by a diameter branching exponent using hydraulic and geomorphologic principles. Scaling exponents are computed for each sample network on a given grid size and are regressed against network magnitude. Results indicate that the size of the exponents are related to magnitude of the networks and generally decrease as network magnitude increases. Cases showing differences in scaling exponents with like magnitudes suggest a direction of future work regarding other topologic basin characteristics as potential explanatory variables.

Improving PERSIANN-CCS rain estimation using probabilistic approach and multi-sensors information

NASA Astrophysics Data System (ADS)

Karbalaee, N.; Hsu, K. L.; Sorooshian, S.; Kirstetter, P.; Hong, Y.

2016-12-01

This presentation discusses the recent implemented approaches to improve the rainfall estimation from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System (PERSIANN-CCS). PERSIANN-CCS is an infrared (IR) based algorithm being integrated in the IMERG (Integrated Multi-Satellite Retrievals for the Global Precipitation Mission GPM) to create a precipitation product in 0.1x0.1degree resolution over the chosen domain 50N to 50S every 30 minutes. Although PERSIANN-CCS has a high spatial and temporal resolution, it overestimates or underestimates due to some limitations.PERSIANN-CCS can estimate rainfall based on the extracted information from IR channels at three different temperature threshold levels (220, 235, and 253k). This algorithm relies only on infrared data to estimate rainfall indirectly from this channel which cause missing the rainfall from warm clouds and false estimation for no precipitating cold clouds. In this research the effectiveness of using other channels of GOES satellites such as visible and water vapors has been investigated. By using multi-sensors the precipitation can be estimated based on the extracted information from multiple channels. Also, instead of using the exponential function for estimating rainfall from cloud top temperature, the probabilistic method has been used. Using probability distributions of precipitation rates instead of deterministic values has improved the rainfall estimation for different type of clouds.

A non-conventional watershed partitioning method for semi-distributed hydrological modelling: the package ALADHYN

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Pagani, Alessandro; Rulli, Maria Cristina; Rosso, Renzo

2002-02-01

The extraction of the river network from a digital elevation model (DEM) plays a fundamental role in modelling spatially distributed hydrological processes. The present paper deals with a new two-step procedure based on the preliminary identification of an ideal drainage network (IDN) from contour lines through a variable mesh size, and the further extraction of the actual drainage network (AND) from the IDN using land morphology. The steepest downslope direction search is used to identify individual channels, which are further merged into a network path draining to a given node of the IDN. The contributing area, peaks and saddles are determined by means of a steepest upslope direction search. The basin area is thus partitioned into physically based finite elements enclosed by irregular polygons. Different methods, i.e. the constant and variable threshold area methods, the contour line curvature method, and a topologic method descending from the Hortonian ordering scheme, are used to extract the ADN from the IDN. The contour line curvature method is shown to provide the most appropriate method from a comparison with field surveys. Using the ADN one can model the hydrological response of any sub-basin using a semi-distributed approach. The model presented here combines storm abstraction by the SCS-CN method with surface runoff routing as a geomorphological dispersion process. This is modelled using the gamma instantaneous unit hydrograph as parameterized by river geomorphology. The results are implemented using a project-oriented software facility for the Analysis of LAnd Digital HYdrological Networks (ALADHYN).

Subject-based feature extraction by using fisher WPD-CSP in brain-computer interfaces.

PubMed

Yang, Banghua; Li, Huarong; Wang, Qian; Zhang, Yunyuan

2016-06-01

Feature extraction of electroencephalogram (EEG) plays a vital role in brain-computer interfaces (BCIs). In recent years, common spatial pattern (CSP) has been proven to be an effective feature extraction method. However, the traditional CSP has disadvantages of requiring a lot of input channels and the lack of frequency information. In order to remedy the defects of CSP, wavelet packet decomposition (WPD) and CSP are combined to extract effective features. But WPD-CSP method considers less about extracting specific features that are fitted for the specific subject. So a subject-based feature extraction method using fisher WPD-CSP is proposed in this paper. The idea of proposed method is to adapt fisher WPD-CSP to each subject separately. It mainly includes the following six steps: (1) original EEG signals from all channels are decomposed into a series of sub-bands using WPD; (2) average power values of obtained sub-bands are computed; (3) the specified sub-bands with larger values of fisher distance according to average power are selected for that particular subject; (4) each selected sub-band is reconstructed to be regarded as a new EEG channel; (5) all new EEG channels are used as input of the CSP and a six-dimensional feature vector is obtained by the CSP. The subject-based feature extraction model is so formed; (6) the probabilistic neural network (PNN) is used as the classifier and the classification accuracy is obtained. Data from six subjects are processed by the subject-based fisher WPD-CSP, the non-subject-based fisher WPD-CSP and WPD-CSP, respectively. Compared with non-subject-based fisher WPD-CSP and WPD-CSP, the results show that the proposed method yields better performance (sensitivity: 88.7±0.9%, and specificity: 91±1%) and the classification accuracy from subject-based fisher WPD-CSP is increased by 6-12% and 14%, respectively. The proposed subject-based fisher WPD-CSP method can not only remedy disadvantages of CSP by WPD but also discriminate helpless sub-bands for each subject and make remaining fewer sub-bands keep better separability by fisher distance, which leads to a higher classification accuracy than WPD-CSP method. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Branching pattern in natural drainage network

NASA Astrophysics Data System (ADS)

Hooshyar, M.; Singh, A.; Wang, D.

2017-12-01

The formation and growth of river channels and their network evolution are governed by the erosional and depositional processes operating on the landscape due to movement of water. The branching structure of drainage network is an important feature related to the network topology and contain valuable information about the forming mechanisms of the landscape. We studied the branching patterns in natural drainage networks, extracted from 1 m Digital Elevation Models (DEMs) of 120 catchments with minimal human impacts across the United States. We showed that the junction angles have two distinct modes an the observed modes are physically explained as the optimal angles that result in minimum energy dissipation and are linked to the exponent characterizing slope-area curve. Our findings suggest that the flow regimes, debris-flow dominated or fluvial, have distinct characteristic angles which are functions of the scaling exponent of the slope-area curve. These findings enable us to understand the geomorphological signature of hydrological processes on drainage networks and develop more refined landscape evolution models.

Neural network approach in multichannel auditory event-related potential analysis.

PubMed

Wu, F Y; Slater, J D; Ramsay, R E

1994-04-01

Even though there are presently no clearly defined criteria for the assessment of P300 event-related potential (ERP) abnormality, it is strongly indicated through statistical analysis that such criteria exist for classifying control subjects and patients with diseases resulting in neuropsychological impairment such as multiple sclerosis (MS). We have demonstrated the feasibility of artificial neural network (ANN) methods in classifying ERP waveforms measured at a single channel (Cz) from control subjects and MS patients. In this paper, we report the results of multichannel ERP analysis and a modified network analysis methodology to enhance automation of the classification rule extraction process. The proposed methodology significantly reduces the work of statistical analysis. It also helps to standardize the criteria of P300 ERP assessment and facilitate the computer-aided analysis on neuropsychological functions.

An Emergent Bifurcation Angle on River Deltas

NASA Astrophysics Data System (ADS)

Shaw, J.; Coffey, T.

2017-12-01

Distributary channel bifurcations on river deltas are important features that control water, sediment, and nutrient routing and can dictate large-scale stratigraphic heterogeneity. We use theory originally developed for a special case of tributary networks to understand the dynamics of distributary channel bifurcations. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to evolve dependent on the diffusive flow field outside the network. These networks possess a characteristic bifurcation angle of 72°, due to Laplacian flow in the groundwater flow field near tributary channel tips (gradient2h2=0, where h is water surface elevation). We develop and test the hypothesis that bifurcation angles in distributary channel networks are likewise dictated by the external flow field, in this case the shallow surface water surrounding the subaqueous portion of distributary channel bifurcations in a deltaic setting. We measured 130 unique distributary channel bifurcations in a single experimental delta and in 10 natural deltas, yielding a mean angle of 70.35°±2.59° (95% confidence interval), in line with the theoretical prediction. These data and hydrodynamic scaling arguments convince us that distributary network formation can result simply from the coupling of (Laplacian) extra-channel flow to channels along subaqueous channel networks. The simplicity of this model provides new insight into distributary network formation and its geomorphic and stratigraphic consequences.

Study on effective MOSFET channel length extracted from gate capacitance

NASA Astrophysics Data System (ADS)

Tsuji, Katsuhiro; Terada, Kazuo; Fujisaka, Hisato

2018-01-01

The effective channel length (L GCM) of metal-oxide-semiconductor field-effect transistors (MOSFETs) is extracted from the gate capacitances of actual-size MOSFETs, which are measured by charge-injection-induced-error-free charge-based capacitance measurement (CIEF CBCM). To accurately evaluate the capacitances between the gate and the channel of test MOSFETs, the parasitic capacitances are removed by using test MOSFETs having various channel sizes and a source/drain reference device. A strong linear relationship between the gate-channel capacitance and the design channel length is obtained, from which L GCM is extracted. It is found that L GCM is slightly less than the effective channel length (L CRM) extracted from the measured MOSFET drain current. The reason for this is discussed, and it is found that the capacitance between the gate electrode and the source and drain regions affects this extraction.

A novel approach for assessments of erythrocyte sedimentation rate.

PubMed

Pribush, A; Hatskelzon, L; Meyerstein, N

2011-06-01

Previous studies have shown that the dispersed phase of sedimenting blood undergoes dramatic structural changes: Discrete red blood cell (RBC) aggregates formed shortly after a settling tube is filled with blood are combined into a continuous network followed by its collapse via the formation of plasma channels, and finally, the collapsed network is dispersed into individual fragments. Based on this scheme of structural transformation, a novel approach for assessments of erythrocyte sedimentation is suggested. Information about erythrocyte sedimentation is extracted from time records of the blood conductivity measured after a dispersion of RBC network into individual fragments. It was found that the sedimentation velocity of RBC network fragments correlates positively with the intensity of attractive intercellular interactions, whereas no effect of hematocrit (Hct) was observed. Thus, unlike Westergren erythrocyte sedimentation rate, sedimentation data obtained by the proposed method do not require correction for Hct. © 2010 Blackwell Publishing Ltd.

Role of Unchannelized Flow in Determining Bifurcation Angle in Distributary Channel Networks

NASA Astrophysics Data System (ADS)

Coffey, T.

2016-02-01

Distributary channel bifurcations on river deltas are important features in both actively prograding river deltas and in lithified deltas within the stratigraphic record. Attributes of distributary channels have long been thought to be defined by flow velocity, grain size and channel aspect ratio where the channel enters the basin. Interestingly, bifurcations in groundwater-fed tributary networks have been shown to grow and bifurcate independent of flow within the exposed channel network. These networks possess a characteristic bifurcation angle of 72°, based on Laplacian flow (water surface concavity equals zero) in the groundwater flow field near tributary channel tips. Based on the tributary channel model, we develop and test the hypothesis that bifurcation angles in distributary channels are likewise dictated by the external flow field, in this case the surface water surrounding the subaqueous portion of distributary channel tips in a deltaic setting. We measured 64 unique distributary bifurcations in an experimental delta, yielding a characteristic angle of 70.2°±2.2° (95% confidence interval), in line with the theoretical prediction for tributary channels. This similarity between bifurcation angles suggests that (A) flow directly outside of the distributary network is Laplacian, (B) the external flow field controls the bifurcation dynamics of distributary channels, and (C) that flow within the channel plays a secondary role in network dynamics.

Can Computational Sediment Transport Models Reproduce the Observed Variability of Channel Networks in Modern Deltas?

NASA Astrophysics Data System (ADS)

Nesvold, E.; Mukerji, T.

2017-12-01

River deltas display complex channel networks that can be characterized through the framework of graph theory, as shown by Tejedor et al. (2015). Deltaic patterns may also be useful in a Bayesian approach to uncertainty quantification of the subsurface, but this requires a prior distribution of the networks of ancient deltas. By considering subaerial deltas, one can at least obtain a snapshot in time of the channel network spectrum across deltas. In this study, the directed graph structure is semi-automatically extracted from satellite imagery using techniques from statistical processing and machine learning. Once the network is labeled with vertices and edges, spatial trends and width and sinuosity distributions can also be found easily. Since imagery is inherently 2D, computational sediment transport models can serve as a link between 2D network structure and 3D depositional elements; the numerous empirical rules and parameters built into such models makes it necessary to validate the output with field data. For this purpose we have used a set of 110 modern deltas, with average water discharge ranging from 10 - 200,000 m3/s, as a benchmark for natural variability. Both graph theoretic and more general distributions are established. A key question is whether it is possible to reproduce this deltaic network spectrum with computational models. Delft3D was used to solve the shallow water equations coupled with sediment transport. The experimental setup was relatively simple; incoming channelized flow onto a tilted plane, with varying wave and tidal energy, sediment types and grain size distributions, river discharge and a few other input parameters. Each realization was run until a delta had fully developed: between 50 and 500 years (with a morphology acceleration factor). It is shown that input parameters should not be sampled independently from the natural ranges, since this may result in deltaic output that falls well outside the natural spectrum. Since we are interested in studying the patterns occurring in nature, ideas are proposed for how to sample computer realizations that match this distribution. By establishing a link between surface based patterns from the field with the associated subsurface structure from physics-based models, this is a step towards a fully Bayesian workflow in subsurface simulation.

How Are Television Networks Involved in Distance Learning?

ERIC Educational Resources Information Center

Bucher, Katherine

1996-01-01

Reviews the involvement of various television networks in distance learning, including public broadcasting stations, Cable in the Classroom, Arts and Entertainment Network, Black Entertainment Television, C-SPAN, CNN (Cable News Network), The Discovery Channel, The Learning Channel, Mind Extension University, The Weather Channel, National Teacher…

Multi-channel distributed coordinated function over single radio in wireless sensor networks.

PubMed

Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

Multi-Channel Distributed Coordinated Function over Single Radio in Wireless Sensor Networks

PubMed Central

Campbell, Carlene E.-A.; Loo, Kok-Keong (Jonathan); Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band. PMID:22346614

Optimal fractal tree-like microchannel networks with slip for laminar-flow-modified Murray's law.

PubMed

Jing, Dalei; Song, Shiyu; Pan, Yunlu; Wang, Xiaoming

2018-01-01

The fractal tree-like branched network is an effective channel design structure to reduce the hydraulic resistance as compared with the conventional parallel channel network. In order for a laminar flow to achieve minimum hydraulic resistance, it is believed that the optimal fractal tree-like channel network obeys the well-accepted Murray's law of β m = N -1/3 (β m is the optimal diameter ratio between the daughter channel and the parent channel and N is the branching number at every level), which is obtained under the assumption of no-slip conditions at the channel wall-liquid interface. However, at the microscale, the no-slip condition is not always reasonable; the slip condition should indeed be considered at some solid-liquid interfaces for the optimal design of the fractal tree-like channel network. The present work reinvestigates Murray's law for laminar flow in a fractal tree-like microchannel network considering slip condition. It is found that the slip increases the complexity of the optimal design of the fractal tree-like microchannel network to achieve the minimum hydraulic resistance. The optimal diameter ratio to achieve minimum hydraulic resistance is not only dependent on the branching number, as stated by Murray's law, but also dependent on the slip length, the level number, the length ratio between the daughter channel and the parent channel, and the diameter of the channel. The optimal diameter ratio decreases with the increasing slip length, the increasing level number and the increasing length ratio between the daughter channel and the parent channel, and decreases with decreasing channel diameter. These complicated relations were found to become relaxed and simplified to Murray's law when the ratio between the slip length and the diameter of the channel is small enough.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface is a state machine, such as an ASIC, that operates independent of a processor in communicating with the bus controller and data channels.

Loops in hierarchical channel networks

NASA Astrophysics Data System (ADS)

Katifori, Eleni; Magnasco, Marcelo

2012-02-01

Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

Are Equilibrium Multichannel Networks Predictable? the Case of the Indus River, Pakistan

NASA Astrophysics Data System (ADS)

Darby, S. E.; Carling, P. A.

2017-12-01

Focusing on the specific case of the Indus River, we argue that the equilibrium planform network structure of large, multi-channel, rivers is predictable. Between Chashma and Taunsa, Pakistan, the Indus is a 264 km long multiple-channel reach. Remote sensing imagery, including a period of time that encompasses the occurrence of major floods in 2007 and 2010, shows that Indus has a minimum of two and a maximum of nine channels, with on average four active channels during the dry season and five during the monsoon. We show that the network structure, if not detailed planform, remains stable, even for the record 2010 flood (27,100 m3s-1; recurrence interval > 100 years). Bankline recession is negligible for discharges less than a peak annual discharge of 6,000 m3s-1 ( 80% of mean annual flow). Maximum Flow Efficiency (MFE) principle demonstrates the channel network is insensitive to the monsoon floods, which typically peak at 13,200 m3s-1. Rather, the network is in near-equilibrium with the mean annual flood (7,530 m3s-1). MFE principle indicates stable networks have three to four channels, thus the observed stability in the number of active channels accords with the presence of a near-equilibrium reach-scale channel network. Insensitivity to the annual hydrological cycle demonstrates that the time-scale for network adjustment is much longer than the time-scale of the monsoon hydrograph, with the annual excess water being stored on floodplains, rather than being conveyed in an enlarged channel network. The analysis explains the lack of significant channel adjustment following the largest flood in 40 years and the extensive Indus flooding experienced on an annual basis, with its substantial impacts on the populace and agricultural production.

Channel Networks on Large Fans: Refining Analogs for the Ridge-forming Unit, Sinus Meridiani

NASA Technical Reports Server (NTRS)

Wilkinson, Justin

2009-01-01

Stream channels are generally thought of as forming within confined valley settings, separated by interfluves. Sinuous ridges on Mars and Earth are often interpreted as stream channels inverted by subsequent erosion of valley sides. In the case of the ridge-forming unit (RFU), this interpretation fails to explain the (i) close spacing of the ridges, which are (ii) organized in networks, and which (iii) cover large areas (approximately 175,000 km (exp 2)). Channel networks on terrestrial fans develop unconfined by valley slopes. Large fans (100s km long) are low-angle, fluvial features, documented worldwide, with characteristics that address these aspects of the RFU. Ridge patterns Channels on large fans provide an analog for the sinuous and elongated morphology of RFU ridges, but more especially for other patterns such as subparallel, branching and crossing networks. Branches are related to splays (delta-like distributaries are rare), whose channels can rejoin the main channel. Crossing patterns can be caused by even slight sinuosity splay-related side channels often intersect. An avulsion node distant from the fan apex, gives rise to channels with slightly different, and hence intersecting, orientations. Channels on neighboring fans intersect along the common fan margin. 2. Network density Channels are the dominant feature on large terrestrial fans (lakes and dune fields are minor). Inverted landscapes on subsequently eroded fans thus display indurated channels as networks of significantly close-spaced ridges. 3. Channel networks covering large areas Areas of individual large terrestrial fans can reach >200,000 km 2 (105-6 km 2 with nested fans), providing an analog for the wide area distribution of the RFU.

Load-adaptive practical multi-channel communications in wireless sensor networks.

PubMed

Islam, Md Shariful; Alam, Muhammad Mahbub; Hong, Choong Seon; Lee, Sungwon

2010-01-01

In recent years, a significant number of sensor node prototypes have been designed that provide communications in multiple channels. This multi-channel feature can be effectively exploited to increase the overall capacity and performance of wireless sensor networks (WSNs). In this paper, we present a multi-channel communications system for WSNs that is referred to as load-adaptive practical multi-channel communications (LPMC). LPMC estimates the active load of a channel at the sink since it has a more comprehensive view of the network behavior, and dynamically adds or removes channels based on the estimated load. LPMC updates the routing path to balance the loads of the channels. The nodes in a path use the same channel; therefore, they do not need to switch channels to receive or forward packets. LPMC has been evaluated through extensive simulations, and the results demonstrate that it can effectively increase the delivery ratio, network throughput, and channel utilization, and that it can decrease the end-to-end delay and energy consumption.

DeepSleepNet: A Model for Automatic Sleep Stage Scoring Based on Raw Single-Channel EEG.

PubMed

Supratak, Akara; Dong, Hao; Wu, Chao; Guo, Yike

2017-11-01

This paper proposes a deep learning model, named DeepSleepNet, for automatic sleep stage scoring based on raw single-channel EEG. Most of the existing methods rely on hand-engineered features, which require prior knowledge of sleep analysis. Only a few of them encode the temporal information, such as transition rules, which is important for identifying the next sleep stages, into the extracted features. In the proposed model, we utilize convolutional neural networks to extract time-invariant features, and bidirectional-long short-term memory to learn transition rules among sleep stages automatically from EEG epochs. We implement a two-step training algorithm to train our model efficiently. We evaluated our model using different single-channel EEGs (F4-EOG (left), Fpz-Cz, and Pz-Oz) from two public sleep data sets, that have different properties (e.g., sampling rate) and scoring standards (AASM and R&K). The results showed that our model achieved similar overall accuracy and macro F1-score (MASS: 86.2%-81.7, Sleep-EDF: 82.0%-76.9) compared with the state-of-the-art methods (MASS: 85.9%-80.5, Sleep-EDF: 78.9%-73.7) on both data sets. This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different data sets without utilizing any hand-engineered features.

Extraction channel design based on an equivalent lumped parameter method for a SCC-250 MeV superconducting cyclotron

NASA Astrophysics Data System (ADS)

Zhang, Lige; Fan, Kuanjun; Hu, Shengwei; Li, Xiaofei; Mei, Zhiyuan; Zeng, Zhijie; Chen, Wei; Qin, Bin; Rao, Yinong

2018-07-01

A SCC-250 MeV cyclotron, producing a 250 MeV proton beam, is under development in Huazhong University of Science and Technology (HUST) for proton therapy. The magnetic flux density, as a function of radius, decreases rapidly in the beam extraction region, which increases the radial beam size continuously along the extraction orbit. In this paper, an extraction channel inside the SCC-250 MeV is designed to control the beam size using passive magnetic channels. An equivalent lumped parameter method is used to establish the model of the extraction channel in the complex fringe magnetic field of the main magnet. Then, the extraction channel is designed using the lattice design software MADX. The beam envelopes are verified using particle tracing method. The maximum radial size of 6.8 mm and axial size of 4.3 mm meet the requirements of the extraction from the SCC-250 MeV.

Effects of spatial constraints on channel network topology: Implications for geomorphological inference

NASA Astrophysics Data System (ADS)

Cabral, Mariza Castanheira De Moura Da Costa

In the fifty-two years since Robert Horton's 1945 pioneering quantitative description of channel network planform (or plan view morphology), no conclusive findings have been presented that permit inference of geomorphological processes from any measures of network planform. All measures of network planform studied exhibit limited geographic variability across different environments. Horton (1945), Langbein et al. (1947), Schumm (1956), Hack (1957), Melton (1958), and Gray (1961) established various "laws" of network planform, that is, statistical relationships between different variables which have limited variability. A wide variety of models which have been proposed to simulate the growth of channel networks in time over a landsurface are generally also in agreement with the above planform laws. An explanation is proposed for the generality of the channel network planform laws. Channel networks must be space filling, that is, they must extend over the landscape to drain every hillslope, leaving no large undrained areas, and with no crossing of channels, often achieving a roughly uniform drainage density in a given environment. It is shown that the space-filling constraint can reduce the sensitivity of planform variables to different network growth models, and it is proposed that this constraint may determine the planform laws. The "Q model" of network growth of Van Pelt and Verwer (1985) is used to generate samples of networks. Sensitivity to the model parameter Q is markedly reduced when the networks generated are required to be space filling. For a wide variety of Q values, the space-filling networks are in approximate agreement with the various channel network planform laws. Additional constraints, including of energy efficiency, were not studied but may further reduce the variability of planform laws. Inference of model parameter Q from network topology is successful only in networks not subject to spatial constraints. In space-filling networks, for a wide range of Q values, the maximal-likelihood Q parameter value is generally in the vicinity of 1/2, which yields topological randomness. It is proposed that space filling originates the appearance of randomness in channel network topology, and may cause difficulties to geomorphological inference from network planform.

Predicting musically induced emotions from physiological inputs: linear and neural network models.

PubMed

Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M

2013-01-01

Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.

Expected number of quantum channels in quantum networks.

PubMed

Chen, Xi; Wang, He-Ming; Ji, Dan-Tong; Mu, Liang-Zhu; Fan, Heng

2015-07-15

Quantum communication between nodes in quantum networks plays an important role in quantum information processing. Here, we proposed the use of the expected number of quantum channels as a measure of the efficiency of quantum communication for quantum networks. This measure quantified the amount of quantum information that can be teleported between nodes in a quantum network, which differs from classical case in that the quantum channels will be consumed if teleportation is performed. We further demonstrated that the expected number of quantum channels represents local correlations depicted by effective circles. Significantly, capacity of quantum communication of quantum networks quantified by ENQC is independent of distance for the communicating nodes, if the effective circles of communication nodes are not overlapped. The expected number of quantum channels can be enhanced through transformations of the lattice configurations of quantum networks via entanglement swapping. Our results can shed lights on the study of quantum communication in quantum networks.

Expected number of quantum channels in quantum networks

PubMed Central

Chen, Xi; Wang, He-Ming; Ji, Dan-Tong; Mu, Liang-Zhu; Fan, Heng

2015-01-01

Quantum communication between nodes in quantum networks plays an important role in quantum information processing. Here, we proposed the use of the expected number of quantum channels as a measure of the efficiency of quantum communication for quantum networks. This measure quantified the amount of quantum information that can be teleported between nodes in a quantum network, which differs from classical case in that the quantum channels will be consumed if teleportation is performed. We further demonstrated that the expected number of quantum channels represents local correlations depicted by effective circles. Significantly, capacity of quantum communication of quantum networks quantified by ENQC is independent of distance for the communicating nodes, if the effective circles of communication nodes are not overlapped. The expected number of quantum channels can be enhanced through transformations of the lattice configurations of quantum networks via entanglement swapping. Our results can shed lights on the study of quantum communication in quantum networks. PMID:26173556

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor)

2007-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. In some embodiments, network device interfaces associated with different data channels coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.

PubMed

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun

2015-12-03

Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.

High resolution multibeam and hydrodynamic datasets of tidal channels and inlets of the Venice Lagoon

NASA Astrophysics Data System (ADS)

Madricardo, Fantina; Foglini, Federica; Kruss, Aleksandra; Ferrarin, Christian; Pizzeghello, Nicola Marco; Murri, Chiara; Rossi, Monica; Bajo, Marco; Bellafiore, Debora; Campiani, Elisabetta; Fogarin, Stefano; Grande, Valentina; Janowski, Lukasz; Keppel, Erica; Leidi, Elisa; Lorenzetti, Giuliano; Maicu, Francesco; Maselli, Vittorio; Mercorella, Alessandra; Montereale Gavazzi, Giacomo; Minuzzo, Tiziano; Pellegrini, Claudio; Petrizzo, Antonio; Prampolini, Mariacristina; Remia, Alessandro; Rizzetto, Federica; Rovere, Marzia; Sarretta, Alessandro; Sigovini, Marco; Sinapi, Luigi; Umgiesser, Georg; Trincardi, Fabio

2017-09-01

Tidal channels are crucial for the functioning of wetlands, though their morphological properties, which are relevant for seafloor habitats and flow, have been understudied so far. Here, we release a dataset composed of Digital Terrain Models (DTMs) extracted from a total of 2,500 linear kilometres of high-resolution multibeam echosounder (MBES) data collected in 2013 covering the entire network of tidal channels and inlets of the Venice Lagoon, Italy. The dataset comprises also the backscatter (BS) data, which reflect the acoustic properties of the seafloor, and the tidal current fields simulated by means of a high-resolution three-dimensional unstructured hydrodynamic model. The DTMs and the current fields help define how morphological and benthic properties of tidal channels are affected by the action of currents. These data are of potential broad interest not only to geomorphologists, oceanographers and ecologists studying the morphology, hydrodynamics, sediment transport and benthic habitats of tidal environments, but also to coastal engineers and stakeholders for cost-effective monitoring and sustainable management of this peculiar shallow coastal system.

High resolution multibeam and hydrodynamic datasets of tidal channels and inlets of the Venice Lagoon

PubMed Central

Madricardo, Fantina; Foglini, Federica; Kruss, Aleksandra; Ferrarin, Christian; Pizzeghello, Nicola Marco; Murri, Chiara; Rossi, Monica; Bajo, Marco; Bellafiore, Debora; Campiani, Elisabetta; Fogarin, Stefano; Grande, Valentina; Janowski, Lukasz; Keppel, Erica; Leidi, Elisa; Lorenzetti, Giuliano; Maicu, Francesco; Maselli, Vittorio; Mercorella, Alessandra; Montereale Gavazzi, Giacomo; Minuzzo, Tiziano; Pellegrini, Claudio; Petrizzo, Antonio; Prampolini, Mariacristina; Remia, Alessandro; Rizzetto, Federica; Rovere, Marzia; Sarretta, Alessandro; Sigovini, Marco; Sinapi, Luigi; Umgiesser, Georg; Trincardi, Fabio

2017-01-01

Tidal channels are crucial for the functioning of wetlands, though their morphological properties, which are relevant for seafloor habitats and flow, have been understudied so far. Here, we release a dataset composed of Digital Terrain Models (DTMs) extracted from a total of 2,500 linear kilometres of high-resolution multibeam echosounder (MBES) data collected in 2013 covering the entire network of tidal channels and inlets of the Venice Lagoon, Italy. The dataset comprises also the backscatter (BS) data, which reflect the acoustic properties of the seafloor, and the tidal current fields simulated by means of a high-resolution three-dimensional unstructured hydrodynamic model. The DTMs and the current fields help define how morphological and benthic properties of tidal channels are affected by the action of currents. These data are of potential broad interest not only to geomorphologists, oceanographers and ecologists studying the morphology, hydrodynamics, sediment transport and benthic habitats of tidal environments, but also to coastal engineers and stakeholders for cost-effective monitoring and sustainable management of this peculiar shallow coastal system. PMID:28872636

High resolution multibeam and hydrodynamic datasets of tidal channels and inlets of the Venice Lagoon.

PubMed

Madricardo, Fantina; Foglini, Federica; Kruss, Aleksandra; Ferrarin, Christian; Pizzeghello, Nicola Marco; Murri, Chiara; Rossi, Monica; Bajo, Marco; Bellafiore, Debora; Campiani, Elisabetta; Fogarin, Stefano; Grande, Valentina; Janowski, Lukasz; Keppel, Erica; Leidi, Elisa; Lorenzetti, Giuliano; Maicu, Francesco; Maselli, Vittorio; Mercorella, Alessandra; Montereale Gavazzi, Giacomo; Minuzzo, Tiziano; Pellegrini, Claudio; Petrizzo, Antonio; Prampolini, Mariacristina; Remia, Alessandro; Rizzetto, Federica; Rovere, Marzia; Sarretta, Alessandro; Sigovini, Marco; Sinapi, Luigi; Umgiesser, Georg; Trincardi, Fabio

2017-09-05

Tidal channels are crucial for the functioning of wetlands, though their morphological properties, which are relevant for seafloor habitats and flow, have been understudied so far. Here, we release a dataset composed of Digital Terrain Models (DTMs) extracted from a total of 2,500 linear kilometres of high-resolution multibeam echosounder (MBES) data collected in 2013 covering the entire network of tidal channels and inlets of the Venice Lagoon, Italy. The dataset comprises also the backscatter (BS) data, which reflect the acoustic properties of the seafloor, and the tidal current fields simulated by means of a high-resolution three-dimensional unstructured hydrodynamic model. The DTMs and the current fields help define how morphological and benthic properties of tidal channels are affected by the action of currents. These data are of potential broad interest not only to geomorphologists, oceanographers and ecologists studying the morphology, hydrodynamics, sediment transport and benthic habitats of tidal environments, but also to coastal engineers and stakeholders for cost-effective monitoring and sustainable management of this peculiar shallow coastal system.

Student researchers' perceived prerequisites for voluntary research collaboration in the context of Flemish and Chinese universities.

PubMed

Li, Sisi; Zhu, Chang; Li, Shasha

2018-01-01

While numerous papers have illuminated the worthiness of research collaboration, relatively few have addressed its prerequisites. In our study, seven prerequisites for research collaboration were extracted from the existing literature, and 460 student researchers were surveyed for their perceptions of the prerequisites' importance. Focusing on voluntary research collaborations rather than brokered ones, it was found that socially oriented prerequisites such as reciprocal interactions, accountability, trust, and equality are perceived of more importance than prerequisites of psychical proximity, networking channels, and funds and material supplies (substance- and entity-related prerequisites). With latent regression analyses, we also found that Chinese and older, more experienced researchers are inclined to stress the importance of equality. Researchers of different cohorts prioritise substance- and entity-related prerequisites disparately. Specifically, Chinese researchers emphasise the necessity of funds, while researchers from first-tier universities place more value on networking channels. Disciplinary differences for the prerequisite of proximity were also discovered. Based on these results, discussion and implications were referred. Further suggestions on research collaboration studies are rendered.

A performance analysis in AF full duplex relay selection network

NASA Astrophysics Data System (ADS)

Ngoc, Long Nguyen; Hong, Nhu Nguyen; Loan, Nguyen Thi Phuong; Kieu, Tam Nguyen; Voznak, Miroslav; Zdralek, Jaroslav

2018-04-01

This paper studies on the relaying selective matter in amplify-and-forward (AF) cooperation communication with full-duplex (FD) activity. Various relay choice models supposing the present of different instant information are investigated. We examine a maximal relaying choice that optimizes the instant FD channel capacity and asks for global channel state information (CSI) as well as partial CSI learning. To make comparison easy, accurate outage probability clauses and asymptote form of these strategies that give a diversity rank are extracted. From that, we can see clearly that the number of relays, noise factor, the transmittance coefficient as well as the information transfer power had impacted on their performance. Besides, the optimal relay selection (ORS) model can promote than that of the partial relay selection (PRS) model.

Received signal strength and local terrain profile data for radio network planning and optimization at GSM frequency bands.

PubMed

Popoola, Segun I; Atayero, Aderemi A; Faruk, Nasir

2018-02-01

The behaviour of radio wave signals in a wireless channel depends on the local terrain profile of the propagation environments. In view of this, Received Signal Strength (RSS) of transmitted signals are measured at different points in space for radio network planning and optimization. However, these important data are often not publicly available for wireless channel characterization and propagation model development. In this data article, RSS data of a commercial base station operating at 900 and 1800 MHz were measured along three different routes of Lagos-Badagry Highway, Nigeria. In addition, local terrain profile data of the study area (terrain elevation, clutter height, altitude, and the distance of the mobile station from the base station) are extracted from Digital Terrain Map (DTM) to account for the unique environmental features. Statistical analyses and probability distributions of the RSS data are presented in tables and graphs. Furthermore, the degree of correlations (and the corresponding significance) between the RSS and the local terrain parameters were computed and analyzed for proper interpretations. The data provided in this article will help radio network engineers to: predict signal path loss; estimate radio coverage; efficiently reuse limited frequencies; avoid interferences; optimize handover; and adjust transmitted power level.

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

Optimal chroma-like channel design for passive color image splicing detection

NASA Astrophysics Data System (ADS)

Zhao, Xudong; Li, Shenghong; Wang, Shilin; Li, Jianhua; Yang, Kongjin

2012-12-01

Image splicing is one of the most common image forgeries in our daily life and due to the powerful image manipulation tools, image splicing is becoming easier and easier. Several methods have been proposed for image splicing detection and all of them worked on certain existing color channels. However, the splicing artifacts vary in different color channels and the selection of color model is important for image splicing detection. In this article, instead of finding an existing color model, we propose a color channel design method to find the most discriminative channel which is referred to as optimal chroma-like channel for a given feature extraction method. Experimental results show that both spatial and frequency features extracted from the designed channel achieve higher detection rate than those extracted from traditional color channels.

A new scripting library for modeling flow and transport in fractured rock with channel networks

NASA Astrophysics Data System (ADS)

Dessirier, Benoît; Tsang, Chin-Fu; Niemi, Auli

2018-02-01

Deep crystalline bedrock formations are targeted to host spent nuclear fuel owing to their overall low permeability. They are however highly heterogeneous and only a few preferential paths pertaining to a small set of dominant rock fractures usually carry most of the flow or mass fluxes, a behavior known as channeling that needs to be accounted for in the performance assessment of repositories. Channel network models have been developed and used to investigate the effect of channeling. They are usually simpler than discrete fracture networks based on rock fracture mappings and rely on idealized full or sparsely populated lattices of channels. This study reexamines the fundamental parameter structure required to describe a channel network in terms of groundwater flow and solute transport, leading to an extended description suitable for unstructured arbitrary networks of channels. An implementation of this formalism in a Python scripting library is presented and released along with this article. A new algebraic multigrid preconditioner delivers a significant speedup in the flow solution step compared to previous channel network codes. 3D visualization is readily available for verification and interpretation of the results by exporting the results to an open and free dedicated software. The new code is applied to three example cases to verify its results on full uncorrelated lattices of channels, sparsely populated percolation lattices and to exemplify the use of unstructured networks to accommodate knowledge on local rock fractures.

A Low Collision and High Throughput Data Collection Mechanism for Large-Scale Super Dense Wireless Sensor Networks.

PubMed

Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Gaura, Elena; Brusey, James; Zhang, Xuekun; Dutkiewicz, Eryk

2016-07-18

Super dense wireless sensor networks (WSNs) have become popular with the development of Internet of Things (IoT), Machine-to-Machine (M2M) communications and Vehicular-to-Vehicular (V2V) networks. While highly-dense wireless networks provide efficient and sustainable solutions to collect precise environmental information, a new channel access scheme is needed to solve the channel collision problem caused by the large number of competing nodes accessing the channel simultaneously. In this paper, we propose a space-time random access method based on a directional data transmission strategy, by which collisions in the wireless channel are significantly decreased and channel utility efficiency is greatly enhanced. Simulation results show that our proposed method can decrease the packet loss rate to less than 2 % in large scale WSNs and in comparison with other channel access schemes for WSNs, the average network throughput can be doubled.

Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis.

PubMed

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner; Sakaguchi, Jun; Olmos, Juan José Vegas; Awaji, Yoshinari; Monroy, Idelfonso Tafur; Wada, Naoya

2017-09-18

This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor)

2005-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Konz, Daniel W. (Inventor); Winkelmann, Joseph P. (Inventor); Grant, Robert L. (Inventor)

2004-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted by the network device interface into digital signals and transmitted back to the controller. In one advantageous embodiment, the network device interface uses a specialized protocol for communicating across the network bus that uses a low-level instruction set and has low overhead for data communication.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor); Konz, Daniel W. (Inventor)

2009-01-01

A communications system and method are provided for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is converted into digital signals and transmitted to the controller. Network device interfaces associated with different data channels can coordinate communications with the other interfaces based on either a transition in a command message sent by the bus controller or a synchronous clock signal.

Growth of a Dendritic Channel Network (Invited)

NASA Astrophysics Data System (ADS)

Rothman, D.; Abrams, D. M.; Devauchelle, O.; Petroff, A. P.; Lobkovsky, A. E.; Straub, K. M.; McElroy, B.; Mohrig, D. C.; Kudrolli, A.

2009-12-01

Dendritic channel networks are a ubiquitous feature of Earth's topography. A half century of work has detailed their scale-invariant geometry. But relatively little is known about how such networks grow, especially in natural settings at geologic time scales. This talk addresses the growth of a particularly simple class of channel networks: those which drain groundwater. We focus on a pristine field site in the Florida Panhandle, in which channels extending for kilometers have been incised vertically through tens of meters of ancient beach sands. We first show how the flow of subsurface water interacts with the planform geometry of the network. Ground-penetrating radar images of the water table shape near a highly-ramified section of the network provide a qualitative view of groundwater focusing. Noting that the water table represents a balance between water input via rain and water flowing into the channel network, we solve for the steady state shape of the water table around the entire network and the associated water fluxes. Comparison of predicted and measured fluxes shows that the ramified structure of the Florida network is consistent with uniformly forced unstable growth through a homogeneous medium. In other words, the dendritic pattern results intrinsically from growth dynamics rather than geologic heterogeneity. We then use these observations to show that the growth of groundwater-driven networks can be described by two linear response laws. Remarkably, one of these growth laws is reversible, which allows us to reconstruct network history and estimate network age. A particularly striking feature of the Florida network is the existence of a characteristic length scale between channels. Our theory predicts how this length scale evolves, thereby linking network growth to geometric form. Reference: D. M. Abrams, A. E. Lobkovsky, A. P. Petroff, K. M. Straub, B. McElroy, D. C. Mohrig, A. Kudrolli, and D. H. Rothman,, Growth laws for channel networks incised by groundwater flow, Nature Geoscience, v. 2, 193-196, March 2009.

Software-Defined Architectures for Spectrally Efficient Cognitive Networking in Extreme Environments

NASA Astrophysics Data System (ADS)

Sklivanitis, Georgios

The objective of this dissertation is the design, development, and experimental evaluation of novel algorithms and reconfigurable radio architectures for spectrally efficient cognitive networking in terrestrial, airborne, and underwater environments. Next-generation wireless communication architectures and networking protocols that maximize spectrum utilization efficiency in congested/contested or low-spectral availability (extreme) communication environments can enable a rich body of applications with unprecedented societal impact. In recent years, underwater wireless networks have attracted significant attention for military and commercial applications including oceanographic data collection, disaster prevention, tactical surveillance, offshore exploration, and pollution monitoring. Unmanned aerial systems that are autonomously networked and fully mobile can assist humans in extreme or difficult-to-reach environments and provide cost-effective wireless connectivity for devices without infrastructure coverage. Cognitive radio (CR) has emerged as a promising technology to maximize spectral efficiency in dynamically changing communication environments by adaptively reconfiguring radio communication parameters. At the same time, the fast developing technology of software-defined radio (SDR) platforms has enabled hardware realization of cognitive radio algorithms for opportunistic spectrum access. However, existing algorithmic designs and protocols for shared spectrum access do not effectively capture the interdependencies between radio parameters at the physical (PHY), medium-access control (MAC), and network (NET) layers of the network protocol stack. In addition, existing off-the-shelf radio platforms and SDR programmable architectures are far from fulfilling runtime adaptation and reconfiguration across PHY, MAC, and NET layers. Spectrum allocation in cognitive networks with multi-hop communication requirements depends on the location, network traffic load, and interference profile at each network node. As a result, the development and implementation of algorithms and cross-layer reconfigurable radio platforms that can jointly treat space, time, and frequency as a unified resource to be dynamically optimized according to inter- and intra-network interference constraints is of fundamental importance. In the next chapters, we present novel algorithmic and software/hardware implementation developments toward the deployment of spectrally efficient terrestrial, airborne, and underwater wireless networks. In Chapter 1 we review the state-of-art in commercially available SDR platforms, describe their software and hardware capabilities, and classify them based on their ability to enable rapid prototyping and advance experimental research in wireless networks. Chapter 2 discusses system design and implementation details toward real-time evaluation of a software-radio platform for all-spectrum cognitive channelization in the presence of narrowband or wideband primary stations. All-spectrum channelization is achieved by designing maximum signal-to-interference-plus-noise ratio (SINR) waveforms that span the whole continuum of the device-accessible spectrum, while satisfying peak power and interference temperature (IT) constraints for the secondary and primary users, respectively. In Chapter 3, we introduce the concept of all-spectrum channelization based on max-SINR optimized sparse-binary waveforms, we propose optimal and suboptimal waveform design algorithms, and evaluate their SINR and bit-error-rate (BER) performance in an SDR testbed. Chapter 4 considers the problem of channel estimation with minimal pilot signaling in multi-cell multi-user multi-input multi-output (MIMO) systems with very large antenna arrays at the base station, and proposes a least-squares (LS)-type algorithm that iteratively extracts channel and data estimates from a short record of data measurements. Our algorithmic developments toward spectrally-efficient cognitive networking through joint optimization of channel access code-waveforms and routes in a multi-hop network are described in Chapter 5. Algorithmic designs are software optimized on heterogeneous multi-core general-purpose processor (GPP)-based SDR architectures by leveraging a novel software-radio framework that offers self-optimization and real-time adaptation capabilities at the PHY, MAC, and NET layers of the network protocol stack. Our system design approach is experimentally validated under realistic conditions in a large-scale hybrid ground-air testbed deployment. Chapter 6 reviews the state-of-art in software and hardware platforms for underwater wireless networking and proposes a software-defined acoustic modem prototype that enables (i) cognitive reconfiguration of PHY/MAC parameters, and (ii) cross-technology communication adaptation. The proposed modem design is evaluated in terms of effective communication data rate in both water tank and lake testbed setups. In Chapter 7, we present a novel receiver configuration for code-waveform-based multiple-access underwater communications. The proposed receiver is fully reconfigurable and executes (i) all-spectrum cognitive channelization, and (ii) combined synchronization, channel estimation, and demodulation. Experimental evaluation in terms of SINR and BER show that all-spectrum channelization is a powerful proposition for underwater communications. At the same time, the proposed receiver design can significantly enhance bandwidth utilization. Finally, in Chapter 8, we focus on challenging practical issues that arise in underwater acoustic sensor network setups where co-located multi-antenna sensor deployment is not feasible due to power, computation, and hardware limitations, and design, implement, and evaluate an underwater receiver structure that accounts for multiple carrier frequency and timing offsets in virtual (distributed) MIMO underwater systems.

Are equilibrium multichannel networks predictable? The case of the regulated Indus River, Pakistan

NASA Astrophysics Data System (ADS)

Carling, P. A.; Trieu, H.; Hornby, D. D.; Huang, He Qing; Darby, S. E.; Sear, D. A.; Hutton, C.; Hill, C.; Ali, Z.; Ahmed, A.; Iqbal, I.; Hussain, Z.

2018-02-01

Arguably, the current planform behaviour of the Indus River is broadly predictable. Between Chashma and Taunsa, Pakistan, the Indus is a 264-km-long multiple-channel reach. Remote sensing imagery, encompassing major floods in 2007 and 2010, shows that the Indus has a minimum of two and a maximum of nine channels, with on average four active channels during the dry season and five during the annual monsoon. Thus, the network structure, if not detailed planform, remains stable even for the record 2010 flood (27,100 m3 s- 1; recurrence interval > 100 years). Bankline recession is negligible for discharges less than a peak annual discharge of 6000 m3 s- 1 ( 80% of mean annual flood). The Maximum Flow Efficiency (MFE) principle demonstrates that the channel network is insensitive to the monsoon floods, which typically peak at 13,200 m3 s- 1. Rather, the network is in near-equilibrium with the mean annual flood (7530 m3 s- 1). The MFE principle indicates that stable networks have three to four channels, thus the observed stability in the number of active channels accords with the presence of a near-equilibrium reach-scale channel network. Insensitivity to the annual hydrological cycle demonstrates that the timescale for network adjustment is much longer than the timescale of the monsoon hydrograph, with the annual excess water being stored on floodplains rather than being conveyed in an enlarged channel network. The analysis explains the lack of significant channel adjustment following the largest flood in 40 years and the extensive Indus flooding experienced on an annual basis, with its substantial impacts on the populace and agricultural production.

Sediment and Vegetation Controls on Delta Channel Networks

NASA Astrophysics Data System (ADS)

Lauzon, R.; Murray, A. B.; Piliouras, A.; Kim, W.

2016-12-01

Numerous factors control the patterns of distributary channels formed on a delta, including water and sediment discharge, grain size, sea level rise rates, and vegetation type. In turn, these channel networks influence the shape and evolution of a delta, including what types of plant and animal life - such as humans - it can support. Previous fluvial modeling and flume experiments, outside of the delta context, have addressed how interactions between sediment and vegetation, through their influence on lateral transport of sediment, determine what type of channel networks develops. Similar interactions likely also shape delta flow patterns. Vegetation introduces cohesion, tending to reduce channel migration rates and strengthen existing channel banks, reinforcing existing channels and resulting in localized, relatively stable flow patterns. On the other hand, sediment transport processes can result in lateral migration and frequent switching of active channels, resulting in flow resembling that of a braided stream. While previous studies of deltas have indirectly explored the effects of vegetation through the introduction of cohesive sediment, we directly incorporate key effects of vegetation on flow and sediment transport into the delta-building model DeltaRCM to explore how these effects influence delta channel network formation. Model development is informed by laboratory flume experiments at UT Austin. Here we present initial results of experiments exploring the effects of sea level rise rate, sediment grain size, vegetation type, and vegetation growth rate on delta channel network morphology. These results support the hypothesis that the ability for lateral transport of sediment to occur plays a key role in determining the evolution of delta channel networks and delta morphology.

Throughput and Energy Efficiency of a Cooperative Hybrid ARQ Protocol for Underwater Acoustic Sensor Networks

PubMed Central

Ghosh, Arindam; Lee, Jae-Won; Cho, Ho-Shin

2013-01-01

Due to its efficiency, reliability and better channel and resource utilization, cooperative transmission technologies have been attractive options in underwater as well as terrestrial sensor networks. Their performance can be further improved if merged with forward error correction (FEC) techniques. In this paper, we propose and analyze a retransmission protocol named Cooperative-Hybrid Automatic Repeat reQuest (C-HARQ) for underwater acoustic sensor networks, which exploits both the reliability of cooperative ARQ (CARQ) and the efficiency of incremental redundancy-hybrid ARQ (IR-HARQ) using rate-compatible punctured convolution (RCPC) codes. Extensive Monte Carlo simulations are performed to investigate the performance of the protocol, in terms of both throughput and energy efficiency. The results clearly reveal the enhancement in performance achieved by the C-HARQ protocol, which outperforms both CARQ and conventional stop and wait ARQ (S&W ARQ). Further, using computer simulations, optimum values of various network parameters are estimated so as to extract the best performance out of the C-HARQ protocol. PMID:24217359

Connectivity of Multi-Channel Fluvial Systems: A Comparison of Topology Metrics for Braided Rivers and Delta Networks

NASA Astrophysics Data System (ADS)

Tejedor, A.; Marra, W. A.; Addink, E. A.; Foufoula-Georgiou, E.; Kleinhans, M. G.

2016-12-01

Advancing quantitative understanding of the structure and dynamics of complex networks has transformed research in many fields as diverse as protein interactions in a cell to page connectivity in the World Wide Web and relationships in human societies. However, Geosciences have not benefited much from this new conceptual framework, although connectivity is at the center of many processes in hydro-geomorphology. One of the first efforts in this direction was the seminal work of Smart and Moruzzi (1971), proposing the use of graph theory for studying the intricate structure of delta channel networks. In recent years, this preliminary work has precipitated in a body of research that examines the connectivity of multiple-channel fluvial systems, such as delta networks and braided rivers. In this work, we compare two approaches recently introduced in the literature: (1) Marra et al. (2014) utilized network centrality measures to identify important channels in a braided section of the Jamuna River, and used the changes of bifurcations within the network over time to explain the overall river evolution; and (2) Tejedor et al. (2015a,b) developed a set of metrics to characterize the complexity of deltaic channel networks, as well as defined a vulnerability index that quantifies the relative change of sediment and water delivery to the shoreline outlets in response to upstream perturbations. Here we present a comparative analysis of metrics of centrality and vulnerability applied to both braided and deltaic channel networks to depict critical channels in those systems, i.e., channels where a change would contribute more substantially to overall system changes, and to understand what attributes of interest in a channel network are most succinctly depicted in what metrics. Marra, W. A., Kleinhans, M. G., & Addink, E. A. (2014). Earth Surface Processes and Landforms, doi:10.1002/esp.3482Smart, J. S., and V. L. Moruzzi (1971), Quantitative properties of delta channel networks, Tech. Rep. 3, 27 pp., IBM Thomas J. Watson Res. Cent., Yorktown, NYTejedor, A., Longjas, A., Zaliapin, I., & Foufoula-Georgiou, E. (2015a/b). Water Resources Research, doi:10.1002/2014WR016259 & doi:10.1002/2014WR016604

Network device interface for digitally interfacing data channels to a controller a via network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. In one embodiment, the bus controller transmits messages to the network device interface containing a plurality of bits having a value defined by a transition between first and second states in the bits. The network device interface determines timing of the data sequence of the message and uses the determined timing to communicate with the bus controller.

75 FR 36456 - Channel America Television Network, Inc., EquiMed, Inc., Kore Holdings, Inc., Robotic Vision...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-25

... SECURITIES AND EXCHANGE COMMISSION [File No. 500-1] Channel America Television Network, Inc., EquiMed, Inc., Kore Holdings, Inc., Robotic Vision Systems, Inc. (n/k/a Acuity Cimatrix, Inc.), Security... information concerning the securities of Channel America Television Network, Inc. because it has not filed any...

Classification of breast MRI lesions using small-size training sets: comparison of deep learning approaches

NASA Astrophysics Data System (ADS)

Amit, Guy; Ben-Ari, Rami; Hadad, Omer; Monovich, Einat; Granot, Noa; Hashoul, Sharbell

2017-03-01

Diagnostic interpretation of breast MRI studies requires meticulous work and a high level of expertise. Computerized algorithms can assist radiologists by automatically characterizing the detected lesions. Deep learning approaches have shown promising results in natural image classification, but their applicability to medical imaging is limited by the shortage of large annotated training sets. In this work, we address automatic classification of breast MRI lesions using two different deep learning approaches. We propose a novel image representation for dynamic contrast enhanced (DCE) breast MRI lesions, which combines the morphological and kinetics information in a single multi-channel image. We compare two classification approaches for discriminating between benign and malignant lesions: training a designated convolutional neural network and using a pre-trained deep network to extract features for a shallow classifier. The domain-specific trained network provided higher classification accuracy, compared to the pre-trained model, with an area under the ROC curve of 0.91 versus 0.81, and an accuracy of 0.83 versus 0.71. Similar accuracy was achieved in classifying benign lesions, malignant lesions, and normal tissue images. The trained network was able to improve accuracy by using the multi-channel image representation, and was more robust to reductions in the size of the training set. A small-size convolutional neural network can learn to accurately classify findings in medical images using only a few hundred images from a few dozen patients. With sufficient data augmentation, such a network can be trained to outperform a pre-trained out-of-domain classifier. Developing domain-specific deep-learning models for medical imaging can facilitate technological advancements in computer-aided diagnosis.

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

NASA Astrophysics Data System (ADS)

Gong, Yubing; Xie, Huijuan

2017-09-01

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems.

Connectivity of Secondary Channels in the Floodplain of a Low-Gradient Midwestern U.S. Agricultural River

NASA Astrophysics Data System (ADS)

Czuba, J. A.; David, S. R.; Edmonds, D. A.

2016-12-01

Floodplains of low-gradient Midwestern U.S. agricultural rivers are commonly dissected by a network of secondary channels that convey flow only during flood events. These networks of secondary channels have only recently been revealed by high resolution digital elevation models. Secondary channels, as referred to here, span multiple meander wavelengths and appear fundamentally different from chute channels. While secondary channels have been described to some extent in other river systems, our focus here is on those found in Indiana, which are revealed by state-wide LiDAR data acquired in 2011. In this work, we quantify how the network connectivity of the secondary channels in the floodplain develops as a function of flow stage. Secondary channels begin conveying water at stages just below bankfull, become an interconnected web of flow pathways above bankfull stage, and are completely inundated at higher stages. We construct a two-dimensional numerical model of the river/floodplain system from LiDAR data and from main-channel river bathymetry in order to obtain the extent of floodplain inundation at various flows. The inundated area within the secondary channels is then converted into a river/floodplain flow-channel network and quantified using various network metrics. Future work will explore the morphodynamics of this river/floodplain system extended to 100-1,000 year timescales. The goal is to develop a simple model to test hypotheses about how these floodplain channels evolve. Relevant research questions include: do secondary channels serve as preferential avulsion pathways? Or could secondary channels evolve to create a multi-channeled anabranching system? Furthermore, under what hydrologic and sedimentologic conditions would a river/floodplain system evolve to one state or another?

Energy-Efficient Channel Handoff for Sensor Network-Assisted Cognitive Radio Network

PubMed Central

Usman, Muhammad; Sajjad Khan, Muhammad; Vu-Van, Hiep; Insoo, Koo

2015-01-01

The visiting and less-privileged status of the secondary users (SUs) in a cognitive radio network obligates them to release the occupied channel instantly when it is reclaimed by the primary user. The SU has a choice to make: either wait for the channel to become free, thus conserving energy at the expense of delayed transmission and delivery, or find and switch to a vacant channel, thereby avoiding delay in transmission at the expense of increased energy consumption. An energy-efficient decision that considers the tradeoff between energy consumption and continuous transmission needs to be taken as to whether to switch the channels. In this work, we consider a sensor network-assisted cognitive radio network and propose a backup channel, which is sensed by the SU in parallel with the operating channel that is being sensed by the sensor nodes. Imperfect channel sensing and residual energy of the SU are considered in order to develop an energy-efficient handoff strategy using the partially observable Markov decision process (POMDP), which considers beliefs about the operating and backup channels and the remaining energy of the SU in order to take an optimal channel handoff decision on the question “Should we switch the channel?” The objective is to dynamically decide in each time slot whether the SU should switch the channel or not in order to maximize throughput by utilizing energy efficiently. Extensive simulations were performed to show the effectiveness of the proposed channel handoff strategy, which was demonstrated in the form of throughput with respect to various parameters, i.e., detection probability, the channel idle probabilities of the operating and backup channels, and the maximum energy of the SU. PMID:26213936

Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

PubMed Central

Lin, Kai; Wang, Di; Hu, Long

2016-01-01

With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC). The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S) evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods. PMID:27376302

Reorganization of river networks under changing spatiotemporal precipitation patterns: An optimal channel network approach

NASA Astrophysics Data System (ADS)

Abed-Elmdoust, Armaghan; Miri, Mohammad-Ali; Singh, Arvind

2016-11-01

We investigate the impact of changing nonuniform spatial and temporal precipitation patterns on the evolution of river networks. To achieve this, we develop a two-dimensional optimal channel network (OCN) model with a controllable rainfall distribution to simulate the evolution of river networks, governed by the principle of minimum energy expenditure, inside a prescribed boundary. We show that under nonuniform precipitation conditions, river networks reorganize significantly toward new patterns with different geomorphic and hydrologic signatures. This reorganization is mainly observed in the form of migration of channels of different orders, widening or elongation of basins as well as formation and extinction of channels and basins. In particular, when the precipitation gradient is locally increased, the higher-order channels, including the mainstream river, migrate toward regions with higher precipitation intensity. Through pertinent examples, the reorganization of the drainage network is quantified via stream parameters such as Horton-Strahler and Tokunaga measures, order-based channel total length and river long profiles obtained via simulation of three-dimensional basin topography, while the hydrologic response of the evolved network is investigated using metrics such as hydrograph and power spectral density of simulated streamflows at the outlet of the network. In addition, using OCNs, we investigate the effect of orographic precipitation patterns on multicatchment landscapes composed of several interacting basins. Our results show that network-inspired methods can be utilized as insightful and versatile models for directly exploring the effects of climate change on the evolution of river drainage systems.

Reconstructing paleo-discharge from geometries of fluvial sinuous ridges on Earth and Mars

NASA Astrophysics Data System (ADS)

Hayden, A.; Lamb, M. P.; Mohrig, D. C.; Williams, R. M. E.; Myrow, P.; Ewing, R. C.; Cardenas, B. T.; Findlay, C. P., III

2017-12-01

Sinuous, branching networks of topographic ridges resembling river networks are common across Mars, and show promise for quantifying ancient martian surface hydrology. There are two leading formation mechanisms for ridges with a fluvial origin. Inverted channels are ridges that represent casts (e.g., due to lava fill) of relict river channel topography, whereas exhumed channel deposits are eroded remnants of a more extensive fluvial deposit, such as a channel belt. The inverted channel model is often assumed on Mars; however, we currently lack the ability to distinguish these ridge formation mechanisms, motivating the need for Earth-analog study. To address this issue, we studied the extensive networks of sinuous ridges in the Ebro basin of northeast Spain. The Ebro ridges stand 3-15 meters above the surrounding plains and are capped by a cliff-forming sandstone unit 3-10 meters thick and 20-50 meters in breadth. The caprock sandstone bodies contain bar-scale cross stratification, point-bar deposits, levee deposits, and lenses of mudstone, indicating that these are channel-belt deposits, rather than casts of channels formed from lateral channel migration, avulsion and reoccupation. In plan view, ridges form segments branching outward to the north resembling a distributary network; however, crosscutting relationships indicate that ridges cross at different stratigraphic levels. Thus, the apparent network in planview reflects non-uniform exhumation of channel-belt deposits from multiple stratigraphic positions, rather than an inverted coeval river network. As compared to the inverted channel model, exhumed fluvial deposits indicate persistent fluvial activity over geologic timescales, indicating the potential for long-lived surface water on ancient Mars.

Overland flow erosion inferred from Martian channel network geometry

NASA Astrophysics Data System (ADS)

Seybold, Hansjörg; Kirchner, James

2016-04-01

The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian The controversy about the origin of Mars' channel networks is almost as old as their discovery 150 years ago. Over the last few decades, new Mars probes have revealed more detailed structures in Martian drainage networks, and new studies suggest that Mars once had large volumes of surface water. But how this water flowed, and how it could have carved the channels, remains unclear. Simple scaling arguments show that networks formed by similar mechanisms should have similar branching angles on Earth and Mars, suggesting that Earth analogues can be informative here. A recent analysis of high-resolution data for the continental United States shows that climate leaves a characteristic imprint in the branching geometry of stream networks. Networks growing in humid regions have an average branching angle of α = 2π/5 = 72° [1], which is characteristic of network growth by groundwater sapping [2]. Networks in arid regions, where overland flow erosion is more dominant, show much smaller branching angles. Here we show that the channel networks on Mars have branching angles that resemble those created by surficial flows on Earth. This result implies that the growth of Martian channel networks was dominated by near-surface flow, and suggests that deeper infiltration was inhibited, potentially by permafrost or by impermeable weathered soils. [1] Climate's Watermark in the Geometry of River Networks, Seybold et al.; under review [2] Ramification of stream networks, Devauchelle et al.; PNAS (2012)

Minimum Interference Channel Assignment Algorithm for Multicast in a Wireless Mesh Network.

PubMed

Choi, Sangil; Park, Jong Hyuk

2016-12-02

Wireless mesh networks (WMNs) have been considered as one of the key technologies for the configuration of wireless machines since they emerged. In a WMN, wireless routers provide multi-hop wireless connectivity between hosts in the network and also allow them to access the Internet via gateway devices. Wireless routers are typically equipped with multiple radios operating on different channels to increase network throughput. Multicast is a form of communication that delivers data from a source to a set of destinations simultaneously. It is used in a number of applications, such as distributed games, distance education, and video conferencing. In this study, we address a channel assignment problem for multicast in multi-radio multi-channel WMNs. In a multi-radio multi-channel WMN, two nearby nodes will interfere with each other and cause a throughput decrease when they transmit on the same channel. Thus, an important goal for multicast channel assignment is to reduce the interference among networked devices. We have developed a minimum interference channel assignment (MICA) algorithm for multicast that accurately models the interference relationship between pairs of multicast tree nodes using the concept of the interference factor and assigns channels to tree nodes to minimize interference within the multicast tree. Simulation results show that MICA achieves higher throughput and lower end-to-end packet delay compared with an existing channel assignment algorithm named multi-channel multicast (MCM). In addition, MICA achieves much lower throughput variation among the destination nodes than MCM.

Minimum Interference Channel Assignment Algorithm for Multicast in a Wireless Mesh Network

PubMed Central

Choi, Sangil; Park, Jong Hyuk

2016-01-01

Wireless mesh networks (WMNs) have been considered as one of the key technologies for the configuration of wireless machines since they emerged. In a WMN, wireless routers provide multi-hop wireless connectivity between hosts in the network and also allow them to access the Internet via gateway devices. Wireless routers are typically equipped with multiple radios operating on different channels to increase network throughput. Multicast is a form of communication that delivers data from a source to a set of destinations simultaneously. It is used in a number of applications, such as distributed games, distance education, and video conferencing. In this study, we address a channel assignment problem for multicast in multi-radio multi-channel WMNs. In a multi-radio multi-channel WMN, two nearby nodes will interfere with each other and cause a throughput decrease when they transmit on the same channel. Thus, an important goal for multicast channel assignment is to reduce the interference among networked devices. We have developed a minimum interference channel assignment (MICA) algorithm for multicast that accurately models the interference relationship between pairs of multicast tree nodes using the concept of the interference factor and assigns channels to tree nodes to minimize interference within the multicast tree. Simulation results show that MICA achieves higher throughput and lower end-to-end packet delay compared with an existing channel assignment algorithm named multi-channel multicast (MCM). In addition, MICA achieves much lower throughput variation among the destination nodes than MCM. PMID:27918438

Self-organization of linear nanochannel networks

NASA Astrophysics Data System (ADS)

Annabattula, R. K.; Veenstra, J. M.; Mei, Y. F.; Schmidt, O. G.; Onck, P. R.

2010-06-01

A theoretical study has been conducted to explore the mechanics of self-organizing channel networks with dimensions in the submicron range and nanorange. The channels form by the partial release and bond back of prestressed thin films. In the release phase, the film spontaneously buckles into wrinkles of a certain wavelength, followed by a bond-back phase in which the final channel geometry is established through cohesive interface attractions. Results are presented in terms of the channel spacing, height, and width as a function of the film stiffness, thickness, eigenstrain, etch width, and interface energy. We have identified two dimensionless parameters that fully quantify the network assembly, showing excellent agreement with experiments. Our results provide valuable insight for the design of submicron and nanoscale channel networks with specific geometries.

Network device interface for digitally interfacing data channels to a controller via a network

NASA Technical Reports Server (NTRS)

Konz, Daniel W. (Inventor); Ellerbrock, Philip J. (Inventor); Grant, Robert L. (Inventor); Winkelmann, Joseph P. (Inventor)

2006-01-01

The present invention provides a network device interface and method for digitally connecting a plurality of data channels, such as sensors, actuators, and subsystems, to a controller using a network bus. The network device interface interprets commands and data received from the controller and polls the data channels in accordance with these commands. Specifically, the network device interface receives digital commands and data from the controller, and based on these commands and data, communicates with the data channels to either retrieve data in the case of a sensor or send data to activate an actuator. Data retrieved from the sensor is then converted into digital signals and transmitted back to the controller. In one embodiment, the bus controller sends commands and data a defined bit rate, and the network device interface senses this bit rate and sends data back to the bus controller using the defined bit rate.

Characterizing Social Networks and Communication Channels in a Web-Based Peer Support Intervention.

PubMed

Owen, Jason E; Curran, Michaela; Bantum, Erin O'Carroll; Hanneman, Robert

2016-06-01

Web and mobile (mHealth) interventions have promise for improving health outcomes, but engagement and attrition may be reducing effect sizes. Because social networks can improve engagement, which is a key mechanism of action, understanding the structure and potential impact of social networks could be key to improving mHealth effects. This study (a) evaluates social network characteristics of four distinct communication channels (discussion board, chat, e-mail, and blog) in a large social networking intervention, (b) predicts membership in online communities, and (c) evaluates whether community membership impacts engagement. Participants were 299 cancer survivors with significant distress using the 12-week health-space.net intervention. Social networking attributes (e.g., density and clustering) were identified separately for each type of network communication (i.e., discussion board, blog, web mail, and chat). Each channel demonstrated high levels of clustering, and being a community member in one communication channel was associated with being in the same community in each of the other channels (φ = 0.56-0.89, ps < 0.05). Predictors of community membership differed across communication channels, suggesting that each channel reached distinct types of users. Finally, membership in a discussion board, chat, or blog community was strongly associated with time spent engaging with coping skills exercises (Ds = 1.08-1.84, ps < 0.001) and total time of intervention (Ds = 1.13-1.80, ps < 0.001). mHealth interventions that offer multiple channels for communication allow participants to expand the number of individuals with whom they are communicating, create opportunities for communicating with different individuals in distinct channels, and likely enhance overall engagement.

Characterizing Social Networks and Communication Channels in a Web-Based Peer Support Intervention

PubMed Central

Curran, Michaela; Bantum, Erin O'Carroll; Hanneman, Robert

2016-01-01

Abstract Web and mobile (mHealth) interventions have promise for improving health outcomes, but engagement and attrition may be reducing effect sizes. Because social networks can improve engagement, which is a key mechanism of action, understanding the structure and potential impact of social networks could be key to improving mHealth effects. This study (a) evaluates social network characteristics of four distinct communication channels (discussion board, chat, e-mail, and blog) in a large social networking intervention, (b) predicts membership in online communities, and (c) evaluates whether community membership impacts engagement. Participants were 299 cancer survivors with significant distress using the 12-week health-space.net intervention. Social networking attributes (e.g., density and clustering) were identified separately for each type of network communication (i.e., discussion board, blog, web mail, and chat). Each channel demonstrated high levels of clustering, and being a community member in one communication channel was associated with being in the same community in each of the other channels (φ = 0.56–0.89, ps < 0.05). Predictors of community membership differed across communication channels, suggesting that each channel reached distinct types of users. Finally, membership in a discussion board, chat, or blog community was strongly associated with time spent engaging with coping skills exercises (Ds = 1.08–1.84, ps < 0.001) and total time of intervention (Ds = 1.13–1.80, ps < 0.001). mHealth interventions that offer multiple channels for communication allow participants to expand the number of individuals with whom they are communicating, create opportunities for communicating with different individuals in distinct channels, and likely enhance overall engagement. PMID:27327066

Bidirectional Teleportation Protocol in Quantum Wireless Multi-hop Network

NASA Astrophysics Data System (ADS)

Cai, Rui; Yu, Xu-Tao; Zhang, Zai-Chen

2018-06-01

We propose a bidirectional quantum teleportation protocol based on a composite GHZ-Bell state. In this protocol, the composite GHZ-Bell state channel is transformed into two-Bell state channel through gate operations and single qubit measurements. The channel transformation will lead to different kinds of quantum channel states, so a method is proposed to help determine the unitary matrices effectively under different quantum channels. Furthermore, we discuss the bidirectional teleportation protocol in the quantum wireless multi-hop network. This paper is aimed to provide a bidirectional teleportation protocol and study the bidirectional multi-hop teleportation in the quantum wireless communication network.

Bidirectional Teleportation Protocol in Quantum Wireless Multi-hop Network

NASA Astrophysics Data System (ADS)

Cai, Rui; Yu, Xu-Tao; Zhang, Zai-Chen

2018-02-01

We propose a bidirectional quantum teleportation protocol based on a composite GHZ-Bell state. In this protocol, the composite GHZ-Bell state channel is transformed into two-Bell state channel through gate operations and single qubit measurements. The channel transformation will lead to different kinds of quantum channel states, so a method is proposed to help determine the unitary matrices effectively under different quantum channels. Furthermore, we discuss the bidirectional teleportation protocol in the quantum wireless multi-hop network. This paper is aimed to provide a bidirectional teleportation protocol and study the bidirectional multi-hop teleportation in the quantum wireless communication network.

Influence of dendrite network defects on channel segregate growth

NASA Technical Reports Server (NTRS)

Simpson, M.; Yerebakan, M.; Flemings, M. C.

1985-01-01

The solidifying ingot interdendritic flow analysis in which channel segregates are assumed to be produced by interdendritic fluid flow dissolving channels in the primary dendrite network is presently refined by examining the flow through a dendrite network possessing a small defect. Attention is given to the section of the mushy zone in a solidifying casting. Since defects such as that presently treated are unavoidable in a real casting, a more reliable indication may be furnished of the occurrence of channel segregates.

Opportunistic quantum network coding based on quantum teleportation

NASA Astrophysics Data System (ADS)

Shang, Tao; Du, Gang; Liu, Jian-wei

2016-04-01

It seems impossible to endow opportunistic characteristic to quantum network on the basis that quantum channel cannot be overheard without disturbance. In this paper, we propose an opportunistic quantum network coding scheme by taking full advantage of channel characteristic of quantum teleportation. Concretely, it utilizes quantum channel for secure transmission of quantum states and can detect eavesdroppers by means of quantum channel verification. What is more, it utilizes classical channel for both opportunistic listening to neighbor states and opportunistic coding by broadcasting measurement outcome. Analysis results show that our scheme can reduce the times of transmissions over classical channels for relay nodes and can effectively defend against classical passive attack and quantum active attack.

Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies

PubMed Central

López, Julio

2018-01-01

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections. PMID:29670667

Mining EEG with SVM for Understanding Cognitive Underpinnings of Math Problem Solving Strategies.

PubMed

Bosch, Paul; Herrera, Mauricio; López, Julio; Maldonado, Sebastián

2018-01-01

We have developed a new methodology for examining and extracting patterns from brain electric activity by using data mining and machine learning techniques. Data was collected from experiments focused on the study of cognitive processes that might evoke different specific strategies in the resolution of math problems. A binary classification problem was constructed using correlations and phase synchronization between different electroencephalographic channels as characteristics and, as labels or classes, the math performances of individuals participating in specially designed experiments. The proposed methodology is based on using well-established procedures of feature selection, which were used to determine a suitable brain functional network size related to math problem solving strategies and also to discover the most relevant links in this network without including noisy connections or excluding significant connections.

A Change in the Ion Selectivity of Ligand-Gated Ion Channels Provides a Mechanism to Switch Behavior.

PubMed

Pirri, Jennifer K; Rayes, Diego; Alkema, Mark J

2015-01-01

Behavioral output of neural networks depends on a delicate balance between excitatory and inhibitory synaptic connections. However, it is not known whether network formation and stability is constrained by the sign of synaptic connections between neurons within the network. Here we show that switching the sign of a synapse within a neural circuit can reverse the behavioral output. The inhibitory tyramine-gated chloride channel, LGC-55, induces head relaxation and inhibits forward locomotion during the Caenorhabditis elegans escape response. We switched the ion selectivity of an inhibitory LGC-55 anion channel to an excitatory LGC-55 cation channel. The engineered cation channel is properly trafficked in the native neural circuit and results in behavioral responses that are opposite to those produced by activation of the LGC-55 anion channel. Our findings indicate that switches in ion selectivity of ligand-gated ion channels (LGICs) do not affect network connectivity or stability and may provide an evolutionary and a synthetic mechanism to change behavior.

Airborne radar imaging of subaqueous channel evolution in Wax Lake Delta, Louisiana, USA

NASA Astrophysics Data System (ADS)

Shaw, John B.; Ayoub, Francois; Jones, Cathleen E.; Lamb, Michael P.; Holt, Benjamin; Wagner, R. Wayne; Coffey, Thomas S.; Chadwick, J. Austin; Mohrig, David

2016-05-01

Shallow coastal regions are among the fastest evolving landscapes but are notoriously difficult to measure with high spatiotemporal resolution. Using Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data, we demonstrate that high signal-to-noise L band synthetic aperture radar (SAR) can reveal subaqueous channel networks at the distal ends of river deltas. Using 27 UAVSAR images collected between 2009 and 2015 from the Wax Lake Delta in coastal Louisiana, USA, we show that under normal tidal conditions, planform geometry of the distributary channel network is frequently resolved in the UAVSAR images, including ~700 m of seaward network extension over 5 years for one channel. UAVSAR also reveals regions of subaerial and subaqueous vegetation, streaklines of biogenic surfactants, and what appear to be small distributary channels aliased by the survey grid, all illustrating the value of fine resolution, low noise, L band SAR for mapping the nearshore subaqueous delta channel network.

Modeling multi-process connectivity in river deltas: extending the single layer network analysis to a coupled multilayer network framework

NASA Astrophysics Data System (ADS)

Tejedor, A.; Longjas, A.; Foufoula-Georgiou, E.

2017-12-01

Previous work [e.g. Tejedor et al., 2016 - GRL] has demonstrated the potential of using graph theory to study key properties of the structure and dynamics of river delta channel networks. Although the distribution of fluxes in river deltas is mostly driven by the connectivity of its channel network a significant part of the fluxes might also arise from connectivity between the channels and islands due to overland flow and seepage. This channel-island-subsurface interaction creates connectivity pathways which facilitate or inhibit transport depending on their degree of coupling. The question we pose here is how to collectively study system connectivity that emerges from the aggregated action of different processes (different in nature, intensity and time scales). Single-layer graphs as those introduced for delta channel networks are inadequate as they lack the ability to represent coupled processes, and neglecting across-process interactions can lead to mis-representation of the overall system dynamics. We present here a framework that generalizes the traditional representation of networks (single-layer graphs) to the so-called multi-layer networks or multiplex. A multi-layer network conceptualizes the overall connectivity arising from different processes as distinct graphs (layers), while allowing at the same time to represent interactions between layers by introducing interlayer links (across process interactions). We illustrate this framework using a study of the joint connectivity that arises from the coupling of the confined flow on the channel network and the overland flow on islands, on a prototype delta. We show the potential of the multi-layer framework to answer quantitatively questions related to the characteristic time scales to steady-state transport in the system as a whole when different levels of channel-island coupling are modulated by different magnitudes of discharge rates.

Distinctive fingerprints of erosional regimes in terrestrial channel networks

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.

2017-12-01

Satellite imagery and digital elevation maps capture the large scale morphology of channel networks attributed to long term erosional processes, such as fluvial, glacial, groundwater sapping and subglacial erosion. Characteristic morphologies associated with each of these styles of erosion have been studied in detail, but there exists a knowledge gap related to their parameterization and quantification. This knowledge gap prevents a rigorous analysis of the dominant processes that shaped a particular landscape, and a comparison across styles of erosion. To address this gap, we use previous morphological descriptions of glaciers, rivers, sapping valleys and tunnel valleys to identify and measure quantitative metrics diagnostic of these distinctive styles of erosion. From digital elevation models, we identify four geometric metrics: The minimum channel width, channel aspect ratio (longest length to channel width at the outlet), presence of undulating longitudinal profiles, and tributary junction angle. We also parameterize channel network complexity in terms of its stream order and fractal dimension. We then perform a statistical classification of the channel networks using a Principal Component Analysis on measurements of these six metrics on a dataset of 70 channelized systems. We show that rivers, glaciers, groundwater seepage and subglacial meltwater erode the landscape in rigorously distinguishable ways. Our methodology can more generally be applied to identify the contributions of different processes involved in carving a channel network. In particular, we are able to identify transitions from fluvial to glaciated landscapes or vice-versa.

Evaluation of urban drainage network based geographycal information system (GIS) in Sumenep City

NASA Astrophysics Data System (ADS)

Agrianto, F.; Hadiani, R.; Purwana, Y. M.

2017-02-01

Sumenep City frequently hit by floods. Drainage network conditions greatly affect the performance of her maid, especially those aspects that affect the capacity of the drainage channel. Aspects that affect the capacity of the drainage channel in the form of sedimentation rate and complementary buildings on drainage channels, for example, the presence of street inlet and trash rack. The method used is a drainage channel capacity level approach that level assessment of each segment drainage network conditions by calculating the ratio of the channel cross-sectional area that is filled with sediment to the total cross-sectional area wet and the existence of complementary buildings. Having obtained the condition index value of each segment, the subsequent analysis is spatial analysis using ArcGIS applications to obtain a map of the drainage network information. The analysis showed that the level condition of drainage network in the city of Sumenep in 2016 that of the total 428 drainage network there are 43 sections belonging to the state level “Good”, 198 drainage network belong to the state level “Enough”, 115 drainage network belong to the state “Mild Damaged”, 50 sections belonging to the state “Heavy Damage” and 22 drainage network belong to the state of “Dysfunction”.

Extension of a GIS procedure for calculating the RUSLE equation LS factor

NASA Astrophysics Data System (ADS)

Zhang, Hongming; Yang, Qinke; Li, Rui; Liu, Qingrui; Moore, Demie; He, Peng; Ritsema, Coen J.; Geissen, Violette

2013-03-01

The Universal Soil Loss Equation (USLE) and revised USLE (RUSLE) are often used to estimate soil erosion at regional landscape scales, however a major limitation is the difficulty in extracting the LS factor. The geographic information system-based (GIS-based) methods which have been developed for estimating the LS factor for USLE and RUSLE also have limitations. The unit contributing area-based estimation method (UCA) converts slope length to unit contributing area for considering two-dimensional topography, however is not able to predict the different zones of soil erosion and deposition. The flowpath and cumulative cell length-based method (FCL) overcomes this disadvantage but does not consider channel networks and flow convergence in two-dimensional topography. The purpose of this research was to overcome these limitations and extend the FCL method through inclusion of channel networks and convergence flow. We developed LS-TOOL in Microsoft's.NET environment using C♯ with a user-friendly interface. Comparing the LS factor calculated with the three methodologies (UCA, FCL and LS-TOOL), LS-TOOL delivers encouraging results. In particular, LS-TOOL uses breaks in slope identified from the DEM to locate soil erosion and deposition zones, channel networks and convergence flow areas. Comparing slope length and LS factor values generated using LS-TOOL with manual methods, LS-TOOL corresponds more closely with the reality of the Xiannangou catchment than results using UCA or FCL. The LS-TOOL algorithm can automatically calculate slope length, slope steepness, L factor, S factor, and LS factors, providing the results as ASCII files which can be easily used in some GIS software. This study is an important step forward in conducting more accurate large area erosion evaluation.

MAPPING AND MONITORING OF SALT MARSH VEGETATION AND TIDAL CHANNEL NETWORK FROM HIGH RESOLUTION IMAGERY (1975-2006). EXAMPLE OF THE MONT-SAINT-MICHEL BAY (FRANCE)

NASA Astrophysics Data System (ADS)

Puissant, A. P.; Kellerer, D.; Gluard, L.; Levoy, F.

2009-12-01

Coastal landscapes are severely affected by environmental and social pressures. Their long term development is controlled by both physical and anthropogenic factors, which spatial dynamics and interactions may be analysed by Earth Observation data. The Mont-Saint-Michel Bay (Normandy, France) is one of the European coastal systems with a very high tidal range (approximately 15m during spring tides) because of its geological, geomorphological and hydrodynamical contexts at the estuary of the Couesnon, Sée and Sélune rivers. It is also an important touristic place with the location of the Mont-Saint-Michel Abbey, and an invaluable ecosystem of wetlands forming a transition between the sea and the land. Since 2006, engineering works are performed with the objective of restoring the maritime character of the Bay. These works will lead to many changes in the spatial dynamics of the Bay which can be monitored with two indicators: the sediment budget and the wetland vegetation surfaces. In this context, the aim of this paper is to map and monitor the tidal channel network and the extension of the salt marsh vegetation formation in the tidal zone of the Mont-Saint-Michel Bay by using satellite images. The spatial correlation between the network location of the three main rivers and the development of salt marsh is analysed with multitemporal medium (60m) to high spatial resolution (from 10 to 30 m) satellite images over the period 1975-2006. The method uses a classical supervised algorithm based on a maximum likelihood classification of eleven satellites images. The salt-marsh surfaces and the tidal channel network are then integrated in a GIS. Results of extraction are assessed by qualitative (visual interpretation) and quantitative indicators (confusion matrix). The multi-temporal analysis between 1975 and 2006 highlights that in 1975 when the study area is 26000 ha, salt marshes cover 16% (3000ha), the sandflat (slikke) and the water represent respectively 59% and 25% of the area. In 2006, salt marshes represent more than 3900 ha. Then, in thirty years, salt marshes have increased in average of 29 ha.yr-1. Several periods with different speed can be identified. Moreover, if the global tendency is a progression of salt-marshes, three period of accretion are noticed. Some hypothesis can be formulated about the tidal channel migrations using various data sources as tide levels, wind wave and meteorological data and river discharges. This analysis showed that satellite images are an important information source to locate morphological coastal changes and allows to perform the understanding of a dynamic and complex system such as the Mont-Saint-Michel Bay. It is possible to extract and to monitor coastal objects over a long time series with heterogeneous data such as satellite images with different spatial and spectral resolutions. With the multiplication of very high spatial resolution images, the detection of salt marshes surfaces and tidal channel could ever be more accurate.

High fidelity wireless network evaluation for heterogeneous cognitive radio networks

NASA Astrophysics Data System (ADS)

Ding, Lei; Sagduyu, Yalin; Yackoski, Justin; Azimi-Sadjadi, Babak; Li, Jason; Levy, Renato; Melodia, Tammaso

2012-06-01

We present a high fidelity cognitive radio (CR) network emulation platform for wireless system tests, measure- ments, and validation. This versatile platform provides the configurable functionalities to control and repeat realistic physical channel effects in integrated space, air, and ground networks. We combine the advantages of scalable simulation environment with reliable hardware performance for high fidelity and repeatable evaluation of heterogeneous CR networks. This approach extends CR design only at device (software-defined-radio) or lower-level protocol (dynamic spectrum access) level to end-to-end cognitive networking, and facilitates low-cost deployment, development, and experimentation of new wireless network protocols and applications on frequency- agile programmable radios. Going beyond the channel emulator paradigm for point-to-point communications, we can support simultaneous transmissions by network-level emulation that allows realistic physical-layer inter- actions between diverse user classes, including secondary users, primary users, and adversarial jammers in CR networks. In particular, we can replay field tests in a lab environment with real radios perceiving and learning the dynamic environment thereby adapting for end-to-end goals over distributed spectrum coordination channels that replace the common control channel as a single point of failure. CR networks offer several dimensions of tunable actions including channel, power, rate, and route selection. The proposed network evaluation platform is fully programmable and can reliably evaluate the necessary cross-layer design solutions with configurable op- timization space by leveraging the hardware experiments to represent the realistic effects of physical channel, topology, mobility, and jamming on spectrum agility, situational awareness, and network resiliency. We also provide the flexibility to scale up the test environment by introducing virtual radios and establishing seamless signal-level interactions with real radios. This holistic wireless evaluation approach supports a large-scale, het- erogeneous, and dynamic CR network architecture and allows developing cross-layer network protocols under high fidelity, repeatable, and scalable wireless test scenarios suitable for heterogeneous space, air, and ground networks.

Plasma extraction rate enhancement scheme for a real-time and continuous blood plasma separation device using a sheathless cell concentrator

NASA Astrophysics Data System (ADS)

Kang, Dong-Hyun; Kim, Kyongtae; Kim, Yong-Jun

2018-02-01

Microfluidic devices for plasma extraction are popular because they offer the advantage of smaller reagent consumption compared to conventional centrifugations. The plasma yield (volume percentage of plasma that can be extracted) is an important factor for diagnoses in microdevices with small reagent consumptions. However, recently designed microfluidic devices tend to have a low plasma yield because they have been optimized to improve the purity of extracted plasma. Thus, these devices require large amounts of reagents, and this complexity has eliminated the advantage of microfluidic devices that can operate with only small amounts of reagents. We therefore propose a continuous, real-time, blood plasma separation device, for plasma extraction rate enhancements. Moreover, a blood plasma separation device was designed to achieve improved plasma yields with high-purity efficiency. To obtain a high plasma yield, microstructures were placed on the bottom side of the channel to increase the concentration of blood cells. Plasma separation was then accomplished via microfluidic networks based on the Zweifach-Fung effect. The proposed device was fabricated based on the polydimethylsiloxane molding process using the SU-8 microfluidic channel for the fabrication of the mold and bottom structures. Human blood diluted in a phosphate buffered saline solution (25% hematocrit) was injected into the inlet of the device. The purity efficiencies were approximately equal to 96% with a maximum of 96.75% at a flow rate of 2 µl min-1, while the plasma yield was approximately 59% with a maximum of 59.92% at a flow rate of 4 µl min-1. Compared to results obtained using other devices, our proposed device could obtain comparable or higher plasma purity and a high plasma yield.

RAC-multi: reader anti-collision algorithm for multichannel mobile RFID networks.

PubMed

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks.

RAC-Multi: Reader Anti-Collision Algorithm for Multichannel Mobile RFID Networks

PubMed Central

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks. PMID:22315528

Detection of retinal changes from illumination normalized fundus images using convolutional neural networks

NASA Astrophysics Data System (ADS)

Adal, Kedir M.; van Etten, Peter G.; Martinez, Jose P.; Rouwen, Kenneth; Vermeer, Koenraad A.; van Vliet, Lucas J.

2017-03-01

Automated detection and quantification of spatio-temporal retinal changes is an important step to objectively assess disease progression and treatment effects for dynamic retinal diseases such as diabetic retinopathy (DR). However, detecting retinal changes caused by early DR lesions such as microaneurysms and dot hemorrhages from longitudinal pairs of fundus images is challenging due to intra and inter-image illumination variation between fundus images. This paper explores a method for automated detection of retinal changes from illumination normalized fundus images using a deep convolutional neural network (CNN), and compares its performance with two other CNNs trained separately on color and green channel fundus images. Illumination variation was addressed by correcting for the variability in the luminosity and contrast estimated from a large scale retinal regions. The CNN models were trained and evaluated on image patches extracted from a registered fundus image set collected from 51 diabetic eyes that were screened at two different time-points. The results show that using normalized images yield better performance than color and green channel images, suggesting that illumination normalization greatly facilitates CNNs to quickly and correctly learn distinctive local image features of DR related retinal changes.

Performance Analysis of Modified Accelerative Preallocation MAC Protocol for Passive Star-Coupled WDMA Networks

NASA Astrophysics Data System (ADS)

Yun, Changho; Kim, Kiseon

2006-04-01

For the passive star-coupled wavelength-division multiple-access (WDMA) network, a modified accelerative preallocation WDMA (MAP-WDMA) media access control (MAC) protocol is proposed, which is based on AP-WDMA. To show the advantages of MAP-WDMA as an adequate MAC protocol for the network over AP-WDMA, the channel utilization, the channel-access delay, and the latency of MAP-WDMA are investigated and compared with those of AP-WDMA under various data traffic patterns, including uniform, quasi-uniform type, disconnected type, mesh type, and ring type data traffics, as well as the assumption that a given number of network stations is equal to that of channels, in other words, without channel sharing. As a result, the channel utilization of MAP-WDMA can be competitive with respect to that of AP-WDMA at the expense of insignificantly higher latency. Namely, if the number of network stations is small, MAP-WDMA provides better channel utilization for uniform, quasi-uniform-type, and disconnected-type data traffics at all data traffic loads, as well as for mesh and ring-type data traffics at low data traffic loads. Otherwise, MAP-WDMA only outperforms AP-WDMA for the first three data traffics at higher data traffic loads. In the aspect of channel-access delay, MAP-WDMA gives better performance than AP-WDMA, regardless of data traffic patterns and the number of network stations.

Tests of peak flow scaling in simulated self-similar river networks

USGS Publications Warehouse

Menabde, M.; Veitzer, S.; Gupta, V.; Sivapalan, M.

2001-01-01

The effect of linear flow routing incorporating attenuation and network topology on peak flow scaling exponent is investigated for an instantaneously applied uniform runoff on simulated deterministic and random self-similar channel networks. The flow routing is modelled by a linear mass conservation equation for a discrete set of channel links connected in parallel and series, and having the same topology as the channel network. A quasi-analytical solution for the unit hydrograph is obtained in terms of recursion relations. The analysis of this solution shows that the peak flow has an asymptotically scaling dependence on the drainage area for deterministic Mandelbrot-Vicsek (MV) and Peano networks, as well as for a subclass of random self-similar channel networks. However, the scaling exponent is shown to be different from that predicted by the scaling properties of the maxima of the width functions. ?? 2001 Elsevier Science Ltd. All rights reserved.

Future optical communication networks beyond 160 Gbit/s based on OTDM

NASA Astrophysics Data System (ADS)

Prati, Giancarlo; Bogoni, Antonella; Poti, Luca

2005-01-01

The virtually unlimited bandwidth of optical fibers has caused a great increase in data transmission speed over the past decade and, hence, stimulated high-demand multimedia services such as distance learning, video-conferencing and peer to peer applications. For this reason data traffic is exceeding telephony traffic, and this trend is driving the convergence of telecommunications and computer communications. In this scenario Internet Protocol (IP) is becoming the dominant protocol for any traffic, shifting the attention of the network designers from a circuit switching approach to a packet switching approach. A role of paramount importance in packet switching networks is played by the router that must implement the functionalities to set up and maintain the inter-nodal communications. The main functionalities a router must implement are routing, forwarding, switching, synchronization, contention resolution, and buffering. Nowadays, opto-electronic conversion is still required at each network node to process the incoming signal before routing that to the right output port. However, when the single channel bit rate increases beyond electronic speed limit, Optical Time Division Multiplexing (OTDM) becomes a forced choice, and all-optical processing must be performed to extract the information from the incoming packet. In this paper enabling techniques for ultra-fast all-optical network will be addressed. First a 160 Gbit/s complete transmission system will be considered. As enabling technique, an overview for all-optical logics will be discussed and experimental results will be presented using a particular reconfigurable NOLM based on Self-Phase-Modulation (SPM) or Cross-Phase-Modulation (XPM). Finally, a rough experiment on label extraction, all-optical switching and packet forwarding is shown.

Definition and evaluation of the data-link layer of PACnet

NASA Astrophysics Data System (ADS)

Alsafadi, Yasser H.; Martinez, Ralph; Sanders, William H.

1991-07-01

PACnet is a 200-500 Mbps dual-ring fiber optic network designed to implement a picture archiving and communication system (PACS) in a hospital environment. The network consists of three channels: an image transfer channel, a command and control channel, and a real-time data channel. An initial network interface unit (NIU) design for PACnet consisted of a functional description of the protocols and NIU major components. In order to develop a demonstration prototype, additional definition of protocol algorithms of each channel is necessary. Using the International Standards Organization/Open Systems Interconnection (ISO/OSI) reference model as a guide, the definition of the data link layer is extended. This definition covers interface service specifications for the two constituent sublayers: logical link control (LLC) and medium access control (MAC). Furthermore, it describes procedures for data transfer, mechanisms of error detection and fault recovery. A performance evaluation study was then made to determine how the network performs under various application scenarios. The performance evaluation study was performed using stochastic activity networks, which can formally describe the network behavior. The results of the study demonstrate the feasibility of PACnet as an integrated image, data, and voice network for PACS.

Allometric relationships between traveltime channel networks, convex hulls, and convexity measures

NASA Astrophysics Data System (ADS)

Tay, Lea Tien; Sagar, B. S. Daya; Chuah, Hean Teik

2006-06-01

The channel network (S) is a nonconvex set, while its basin [C(S)] is convex. We remove open-end points of the channel connectivity network iteratively to generate a traveltime sequence of networks (Sn). The convex hulls of these traveltime networks provide an interesting topological quantity, which has not been noted thus far. We compute lengths of shrinking traveltime networks L(Sn) and areas of corresponding convex hulls C(Sn), the ratios of which provide convexity measures CM(Sn) of traveltime networks. A statistically significant scaling relationship is found for a model network in the form L(Sn) ˜ A[C(Sn)]0.57. From the plots of the lengths of these traveltime networks and the areas of their corresponding convex hulls as functions of convexity measures, new power law relations are derived. Such relations for a model network are CM(Sn) ˜ ? and CM(Sn) ˜ ?. In addition to the model study, these relations for networks derived from seven subbasins of Cameron Highlands region of Peninsular Malaysia are provided. Further studies are needed on a large number of channel networks of distinct sizes and topologies to understand the relationships of these new exponents with other scaling exponents that define the scaling structure of river networks.

Sedimentary Facies Mapping Based on Tidal Channel Network and Topographic Features

NASA Astrophysics Data System (ADS)

Ryu, J. H.; Lee, Y. K.; Kim, K.; Kim, B.

2015-12-01

Tidal flats on the west coast of Korea suffer intensive changes in their surface sedimentary facies as a result of the influence of natural and artificial changes. Spatial relationships between surface sedimentary facies distribution and benthic environments were estimated for the open-type Ganghwa tidal flat and semi closed-type Hwangdo tidal flat, Korea. In this study, we standardized the surface sedimentary facies and tidal channel index of the channel density, distance, thickness and order. To extract tidal channel information, we used remotely sensed data, such as those from the Korea Multi-Purpose Satellite (KOMPSAT)-2, KOMPSAT-3, and aerial photographs. Surface sedimentary facies maps were generated based on field data using an interpolation method.The tidal channels in each sediment facies had relatively constant meandering patterns, but the density and complexity were distinguishable. The second fractal dimension was 1.7-1.8 in the mud flat, about 1.4 in the mixed flat, and about 1.3 in the sand flat. The channel density was 0.03-0.06 m/m2 in the mud flat and less than 0.02 m/m2 in the mixed and sand flat areas of the two test areas. Low values of the tidal channel index, which indicated a simple pattern of tidal channel distribution, were identified at areas having low elevation and coarse-grained sediments. By contrast, high values of the tidal channel index, which indicated a dendritic pattern of tidal channel distribution, were identified at areas having high elevation and fine-grained sediments. Surface sediment classification based on remotely sensed data must circumspectly consider an effective critical grain size, water content, local topography, and intertidal structures.

A statistical method to predict flow permanence in dryland streams from time series of stream temperature

USGS Publications Warehouse

Arismendi, Ivan; Dunham, Jason B.; Heck, Michael; Schultz, Luke; Hockman-Wert, David

2017-01-01

Intermittent and ephemeral streams represent more than half of the length of the global river network. Dryland freshwater ecosystems are especially vulnerable to changes in human-related water uses as well as shifts in terrestrial climates. Yet, the description and quantification of patterns of flow permanence in these systems is challenging mostly due to difficulties in instrumentation. Here, we took advantage of existing stream temperature datasets in dryland streams in the northwest Great Basin desert, USA, to extract critical information on climate-sensitive patterns of flow permanence. We used a signal detection technique, Hidden Markov Models (HMMs), to extract information from daily time series of stream temperature to diagnose patterns of stream drying. Specifically, we applied HMMs to time series of daily standard deviation (SD) of stream temperature (i.e., dry stream channels typically display highly variable daily temperature records compared to wet stream channels) between April and August (2015–2016). We used information from paired stream and air temperature data loggers as well as co-located stream temperature data loggers with electrical resistors as confirmatory sources of the timing of stream drying. We expanded our approach to an entire stream network to illustrate the utility of the method to detect patterns of flow permanence over a broader spatial extent. We successfully identified and separated signals characteristic of wet and dry stream conditions and their shifts over time. Most of our study sites within the entire stream network exhibited a single state over the entire season (80%), but a portion of them showed one or more shifts among states (17%). We provide recommendations to use this approach based on a series of simple steps. Our findings illustrate a successful method that can be used to rigorously quantify flow permanence regimes in streams using existing records of stream temperature.

Medium Access Control for Opportunistic Concurrent Transmissions under Shadowing Channels

PubMed Central

Son, In Keun; Mao, Shiwen; Hur, Seung Min

2009-01-01

We study the problem of how to alleviate the exposed terminal effect in multi-hop wireless networks in the presence of log-normal shadowing channels. Assuming node location information, we propose an extension of the IEEE 802.11 MAC protocol that sched-ules concurrent transmissions in the presence of log-normal shadowing, thus mitigating the exposed terminal problem and improving network throughput and delay performance. We observe considerable improvements in throughput and delay achieved over the IEEE 802.11 MAC under various network topologies and channel conditions in ns-2 simulations, which justify the importance of considering channel randomness in MAC protocol design for multi-hop wireless networks. PMID:22408556

Fluid extraction across pumping and permeable walls in the viscous limit

NASA Astrophysics Data System (ADS)

Herschlag, G.; Liu, J.-G.; Layton, A. T.

2016-04-01

In biological transport mechanisms such as insect respiration and renal filtration, fluid travels along a leaky channel allowing material exchange with systems exterior to the channel. The channels in these systems may undergo peristaltic pumping which is thought to enhance the material exchange. To date, little analytic work has been done to study the effect of pumping on material extraction across the channel walls. In this paper, we examine a fluid extraction model in which fluid flowing through a leaky channel is exchanged with fluid in a reservoir. The channel walls are allowed to contract and expand uniformly, simulating a pumping mechanism. In order to efficiently determine solutions of the model, we derive a formal power series solution for the Stokes equations in a finite channel with uniformly contracting/expanding permeable walls. This flow has been well studied in the case in which the normal velocity at the channel walls is proportional to the wall velocity. In contrast we do not assume flow that is proportional to the wall velocity, but flow that is driven by hydrostatic pressure, and we use Darcy's law to close our system for normal wall velocity. We incorporate our flow solution into a model that tracks the material pressure exterior to the channel. We use this model to examine flux across the channel-reservoir barrier and demonstrate that pumping can either enhance or impede fluid extraction across channel walls. We find that associated with each set of physical flow and pumping parameters, there are optimal reservoir conditions that maximize the amount of material flowing from the channel into the reservoir.

From Fractal Trees to Deltaic Networks

NASA Astrophysics Data System (ADS)

Cazanacli, D.; Wolinsky, M. A.; Sylvester, Z.; Cantelli, A.; Paola, C.

2013-12-01

Geometric networks that capture many aspects of natural deltas can be constructed from simple concepts from graph theory and normal probability distributions. Fractal trees with symmetrical geometries are the result of replicating two simple geometric elements, line segments whose lengths decrease and bifurcation angles that are commonly held constant. Branches could also have a thickness, which in the case of natural distributary systems is the equivalent of channel width. In river- or wave-dominated natural deltas, the channel width is a function of discharge. When normal variations around the mean values for length, bifurcating angles, and discharge are applied, along with either pruning of 'clashing' branches or merging (equivalent to channel confluence), fractal trees start resembling natural deltaic networks, except that the resulting channels are unnaturally straight. Introducing a bifurcation probability fewer, naturally curved channels are obtained. If there is no bifurcation, the direction of each new segment depends on the direction the previous segment upstream (correlated random walk) and, to a lesser extent, on a general direction of growth (directional bias). When bifurcation occurs, the resulting two directions also depend on the bifurcation angle and the discharge split proportions, with the dominant branch following the direction of the upstream parent channel closely. The bifurcation probability controls the channel density and, in conjunction with the variability of the directional angles, the overall curvature of the channels. The growth of the network in effect is associated with net delta progradation. The overall shape and shape evolution of the delta depend mainly on the bifurcation angle average size and angle variability coupled with the degree of dominant direction dependency (bias). The proposed algorithm demonstrates how, based on only a few simple rules, a wide variety of channel networks resembling natural deltas, can be replicated. Network Example

Creation of defined single cell resolution neuronal circuits on microelectrode arrays

NASA Astrophysics Data System (ADS)

Pirlo, Russell Kirk

2009-12-01

The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20mum clear-through holes and 2-3mum deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x10 5 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be created with clearly defined circuitry and a one-to-one neuron-electrode ratio. The techniques and processes described here may be used in future research to create defined neuronal circuits to model in vivo circuits and study neuronal network processing.

Faithful qubit transmission in a quantum communication network with heterogeneous channels

NASA Astrophysics Data System (ADS)

Chen, Na; Zhang, Lin Xi; Pei, Chang Xing

2018-04-01

Quantum communication networks enable long-distance qubit transmission and distributed quantum computation. In this paper, a quantum communication network with heterogeneous quantum channels is constructed. A faithful qubit transmission scheme is presented. Detailed calculations and performance analyses show that even in a low-quality quantum channel with serious decoherence, only modest number of locally prepared target qubits are required to achieve near-deterministic qubit transmission.

Quantitative metrics that describe river deltas and their channel networks

NASA Astrophysics Data System (ADS)

Edmonds, Douglas A.; Paola, Chris; Hoyal, David C. J. D.; Sheets, Ben A.

2011-12-01

Densely populated river deltas are losing land at an alarming rate and to successfully restore these environments we must understand the details of their morphology. Toward this end we present a set of five metrics that describe delta morphology: (1) the fractal dimension, (2) the distribution of island sizes, (3) the nearest-edge distance, (4) a synthetic distribution of sediment fluxes at the shoreline, and (5) the nourishment area. The nearest-edge distance is the shortest distance to channelized or unchannelized water from a given location on the delta and is analogous to the inverse of drainage density in tributary networks. The nourishment area is the downstream delta area supplied by the sediment coming through a given channel cross section and is analogous to catchment area in tributary networks. As a first step, we apply these metrics to four relatively simple, fluvially dominated delta networks. For all these deltas, the average nearest-edge distances are remarkably constant moving down delta suggesting that the network organizes itself to maintain a consistent distance to the nearest channel. Nourishment area distributions can be predicted from a river mouth bar model of delta growth, and also scale with the width of the channel and with the length of the longest channel, analogous to Hack's law for drainage basins. The four delta channel networks are fractal, but power laws and scale invariance appear to be less pervasive than in tributary networks. Thus, deltas may occupy an advantageous middle ground between complete similarity and complete dissimilarity, where morphologic differences indicate different behavior.

Aggregating quantum repeaters for the quantum internet

NASA Astrophysics Data System (ADS)

Azuma, Koji; Kato, Go

2017-09-01

The quantum internet holds promise for accomplishing quantum teleportation and unconditionally secure communication freely between arbitrary clients all over the globe, as well as the simulation of quantum many-body systems. For such a quantum internet protocol, a general fundamental upper bound on the obtainable entanglement or secret key has been derived [K. Azuma, A. Mizutani, and H.-K. Lo, Nat. Commun. 7, 13523 (2016), 10.1038/ncomms13523]. Here we consider its converse problem. In particular, we present a universal protocol constructible from any given quantum network, which is based on running quantum repeater schemes in parallel over the network. For arbitrary lossy optical channel networks, our protocol has no scaling gap with the upper bound, even based on existing quantum repeater schemes. In an asymptotic limit, our protocol works as an optimal entanglement or secret-key distribution over any quantum network composed of practical channels such as erasure channels, dephasing channels, bosonic quantum amplifier channels, and lossy optical channels.

Observation of entanglement between itinerant microwave photons and a superconducting qubit.

PubMed

Eichler, C; Lang, C; Fink, J M; Govenius, J; Filipp, S; Wallraff, A

2012-12-14

A localized qubit entangled with a propagating quantum field is well suited to study nonlocal aspects of quantum mechanics and may also provide a channel to communicate between spatially separated nodes in a quantum network. Here, we report the on-demand generation and characterization of Bell-type entangled states between a superconducting qubit and propagating microwave fields composed of zero-, one-, and two-photon Fock states. Using low noise linear amplification and efficient data acquisition we extract all relevant correlations between the qubit and the photon states and demonstrate entanglement with high fidelity.

Wireless Computing Architecture III

DTIC Science & Technology

2013-09-01

MIMO Multiple-Input and Multiple-Output MIMO /CON MIMO with concurrent hannel access and estimation MU- MIMO Multiuser MIMO OFDM Orthogonal...compressive sensing \\; a design for concurrent channel estimation in scalable multiuser MIMO networking; and novel networking protocols based on machine...Network, Antenna Arrays, UAV networking, Angle of Arrival, Localization MIMO , Access Point, Channel State Information, Compressive Sensing 16

A neural network approach for enhancing information extraction from multispectral image data

USGS Publications Warehouse

Liu, J.; Shao, G.; Zhu, H.; Liu, S.

2005-01-01

A back-propagation artificial neural network (ANN) was applied to classify multispectral remote sensing imagery data. The classification procedure included four steps: (i) noisy training that adds minor random variations to the sampling data to make the data more representative and to reduce the training sample size; (ii) iterative or multi-tier classification that reclassifies the unclassified pixels by making a subset of training samples from the original training set, which means the neural model can focus on fewer classes; (iii) spectral channel selection based on neural network weights that can distinguish the relative importance of each channel in the classification process to simplify the ANN model; and (iv) voting rules that adjust the accuracy of classification and produce outputs of different confidence levels. The Purdue Forest, located west of Purdue University, West Lafayette, Indiana, was chosen as the test site. The 1992 Landsat thematic mapper imagery was used as the input data. High-quality airborne photographs of the same Lime period were used for the ground truth. A total of 11 land use and land cover classes were defined, including water, broadleaved forest, coniferous forest, young forest, urban and road, and six types of cropland-grassland. The experiment, indicated that the back-propagation neural network application was satisfactory in distinguishing different land cover types at US Geological Survey levels II-III. The single-tier classification reached an overall accuracy of 85%. and the multi-tier classification an overall accuracy of 95%. For the whole test, region, the final output of this study reached an overall accuracy of 87%. ?? 2005 CASI.

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

PubMed Central

Zhu, Xuqi; Liu, Yu; Zhang, Lin

2009-01-01

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency. PMID:22408560

GABA receptors and T-type Ca2+ channels crosstalk in thalamic networks.

PubMed

Leresche, Nathalie; Lambert, Régis C

2017-06-07

Although the thalamus presents a rather limited repertoire of GABAergic cell types compare to other CNS area, this structure is a privileged system to study how GABA impacts neuronal network excitability. Indeed both glutamatergic thalamocortical (TC) and GABAergic nucleus reticularis thalami (NRT) neurons present a high expression of T-type voltage-dependent Ca 2+ channels whose activation that shapes the output of the thalamus critically depends upon a preceding hyperpolarisation. Because of this strict dependence, a tight functional link between GABA mediated hyperpolarization and T-currents characterizes the thalamic network excitability. In this review we summarize a number of studies showing that the relationships between the various thalamic GABA A/B receptors and T-channels are complex and bidirectional. We discuss how this dynamic interaction sets the global intrathalamic network activity and its long-term plasticity and highlight how the functional relationship between GABA release and T-channel-dependent excitability is finely tuned by the T-channel activation itself. Finally, we illustrate how an impaired balance between T-channels and GABA receptors can lead to pathologically abnormal cellular and network behaviours. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural network classification of myoelectric signal for prosthesis control.

PubMed

Kelly, M F; Parker, P A; Scott, R N

1991-12-01

An alternate approach to deriving control for multidegree of freedom prosthetic arms is considered. By analyzing a single-channel myoelectric signal (MES), we can extract information that can be used to identify different contraction patterns in the upper arm. These contraction patterns are generated by subjects without previous training and are naturally associated with specific functions. Using a set of normalized MES spectral features, we can identify contraction patterns for four arm functions, specifically extension and flexion of the elbow and pronation and supination of the forearm. Performing identification independent of signal power is advantageous because this can then be used as a means for deriving proportional rate control for a prosthesis. An artificial neural network implementation is applied in the classification task. By using three single-layer perceptron networks, the MES is classified, with the spectral representations as input features. Trials performed on five subjects with normal limbs resulted in an average classification performance level of 85% for the four functions. Copyright © 1991. Published by Elsevier Ltd.

Pattern Recognition of Momentary Mental Workload Based on Multi-Channel Electrophysiological Data and Ensemble Convolutional Neural Networks.

PubMed

Zhang, Jianhua; Li, Sunan; Wang, Rubin

2017-01-01

In this paper, we deal with the Mental Workload (MWL) classification problem based on the measured physiological data. First we discussed the optimal depth (i.e., the number of hidden layers) and parameter optimization algorithms for the Convolutional Neural Networks (CNN). The base CNNs designed were tested according to five classification performance indices, namely Accuracy, Precision, F-measure, G-mean, and required training time. Then we developed an Ensemble Convolutional Neural Network (ECNN) to enhance the accuracy and robustness of the individual CNN model. For the ECNN design, three model aggregation approaches (weighted averaging, majority voting and stacking) were examined and a resampling strategy was used to enhance the diversity of individual CNN models. The results of MWL classification performance comparison indicated that the proposed ECNN framework can effectively improve MWL classification performance and is featured by entirely automatic feature extraction and MWL classification, when compared with traditional machine learning methods.

Segmentation and feature extraction of retinal vascular morphology

NASA Astrophysics Data System (ADS)

Leopold, Henry A.; Orchard, Jeff; Zelek, John; Lakshminarayanan, Vasudevan

2017-02-01

Analysis of retinal fundus images is essential for physicians, optometrists and ophthalmologists in the diagnosis, care and treatment of patients. The first step of almost all forms of automated fundus analysis begins with the segmentation and subtraction of the retinal vasculature, while analysis of that same structure can aid in the diagnosis of certain retinal and cardiovascular conditions, such as diabetes or stroke. This paper investigates the use of a Convolutional Neural Network as a multi-channel classifier of retinal vessels using DRIVE, a database of fundus images. The result of the network with the application of a confidence threshold was slightly below the 2nd observer and gold standard, with an accuracy of 0.9419 and ROC of 0.9707. The output of the network with on post-processing boasted the highest sensitivity found in the literature with a score of 0.9568 and a good ROC score of 0.9689. The high sensitivity of the system makes it suitable for longitudinal morphology assessments, disease detection and other similar tasks.

Avoiding disentanglement of multipartite entangled optical beams with a correlated noisy channel

PubMed Central

Deng, Xiaowei; Tian, Caixing; Su, Xiaolong; Xie, Changde

2017-01-01

A quantum communication network can be constructed by distributing a multipartite entangled state to space-separated nodes. Entangled optical beams with highest flying speed and measurable brightness can be used as carriers to convey information in quantum communication networks. Losses and noises existing in real communication channels will reduce or even totally destroy entanglement. The phenomenon of disentanglement will result in the complete failure of quantum communication. Here, we present the experimental demonstrations on the disentanglement and the entanglement revival of tripartite entangled optical beams used in a quantum network. We experimentally demonstrate that symmetric tripartite entangled optical beams are robust in pure lossy but noiseless channels. In a noisy channel, the excess noise will lead to the disentanglement and the destroyed entanglement can be revived by the use of a correlated noisy channel (non-Markovian environment). The presented results provide useful technical references for establishing quantum networks. PMID:28295024

An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm

PubMed Central

Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

2015-01-01

A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction. PMID:26287193

An Efficient VLSI Architecture for Multi-Channel Spike Sorting Using a Generalized Hebbian Algorithm.

PubMed

Chen, Ying-Lun; Hwang, Wen-Jyi; Ke, Chi-En

2015-08-13

A novel VLSI architecture for multi-channel online spike sorting is presented in this paper. In the architecture, the spike detection is based on nonlinear energy operator (NEO), and the feature extraction is carried out by the generalized Hebbian algorithm (GHA). To lower the power consumption and area costs of the circuits, all of the channels share the same core for spike detection and feature extraction operations. Each channel has dedicated buffers for storing the detected spikes and the principal components of that channel. The proposed circuit also contains a clock gating system supplying the clock to only the buffers of channels currently using the computation core to further reduce the power consumption. The architecture has been implemented by an application-specific integrated circuit (ASIC) with 90-nm technology. Comparisons to the existing works show that the proposed architecture has lower power consumption and hardware area costs for real-time multi-channel spike detection and feature extraction.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

PubMed

Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo

2017-10-28

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

Flow control using audio tones in resonant microfluidic networks: towards cell-phone controlled lab-on-a-chip devices.

PubMed

Phillips, Reid H; Jain, Rahil; Browning, Yoni; Shah, Rachana; Kauffman, Peter; Dinh, Doan; Lutz, Barry R

2016-08-16

Fluid control remains a challenge in development of portable lab-on-a-chip devices. Here, we show that microfluidic networks driven by single-frequency audio tones create resonant oscillating flow that is predicted by equivalent electrical circuit models. We fabricated microfluidic devices with fluidic resistors (R), inductors (L), and capacitors (C) to create RLC networks with band-pass resonance in the audible frequency range available on portable audio devices. Microfluidic devices were fabricated from laser-cut adhesive plastic, and a "buzzer" was glued to a diaphragm (capacitor) to integrate the actuator on the device. The AC flowrate magnitude was measured by imaging oscillation of bead tracers to allow direct comparison to the RLC circuit model across the frequency range. We present a systematic build-up from single-channel systems to multi-channel (3-channel) networks, and show that RLC circuit models predict complex frequency-dependent interactions within multi-channel networks. Finally, we show that adding flow rectifying valves to the network creates pumps that can be driven by amplified and non-amplified audio tones from common audio devices (iPod and iPhone). This work shows that RLC circuit models predict resonant flow responses in multi-channel fluidic networks as a step towards microfluidic devices controlled by audio tones.

Medical reliable network using concatenated channel codes through GSM network.

PubMed

Ahmed, Emtithal; Kohno, Ryuji

2013-01-01

Although the 4(th) generation (4G) of global mobile communication network, i.e. Long Term Evolution (LTE) coexisting with the 3(rd) generation (3G) has successfully started; the 2(nd) generation (2G), i.e. Global System for Mobile communication (GSM) still playing an important role in many developing countries. Without any other reliable network infrastructure, GSM can be applied for tele-monitoring applications, where high mobility and low cost are necessary. A core objective of this paper is to introduce the design of a more reliable and dependable Medical Network Channel Code system (MNCC) through GSM Network. MNCC design based on simple concatenated channel code, which is cascade of an inner code (GSM) and an extra outer code (Convolution Code) in order to protect medical data more robust against channel errors than other data using the existing GSM network. In this paper, the MNCC system will provide Bit Error Rate (BER) equivalent to the BER for medical tele monitoring of physiological signals, which is 10(-5) or less. The performance of the MNCC has been proven and investigated using computer simulations under different channels condition such as, Additive White Gaussian Noise (AWGN), Rayleigh noise and burst noise. Generally the MNCC system has been providing better performance as compared to GSM.

Tunable thin film filters for intelligent WDM networks

NASA Astrophysics Data System (ADS)

Cahill, Michael; Bartolini, Glenn; Lourie, Mark; Domash, Lawrence

2006-08-01

Optical transmission systems have evolved rapidly in recent years with the emergence of new technologies for gain management, wavelength multiplexing, tunability, and switching. WDM networks are increasingly expected to be agile, flexible, and reconfigurable which in turn has led to a need for monitoring to be more widely distributed within the network. Automation of many actions performed on these networks, such as channel provisioning and power balancing, can only be realized by the addition of optical channel monitors (OCMs). These devices provide information about the optical transmission system including the number of optical channels, channel identification, wavelength, power, and in some cases optical signal-to-noise ratio (OSNR). Until recently OCMs were costly and bulky and thus the number of OCMs used in optical networks was often kept to a minimum. We describe a family of tunable thin film filters which have greatly reduced the cost and physical footprint of channel monitors, making possible 'monitoring everywhere' for intelligent optical networks which can serve long haul, metro and access requirements from a single technology platform. As examples of specific applications we discuss network issues such as auto provisioning, wavelength collision avoidance, power balancing, OSNR balancing, gain equalization, alien wavelength recognition, interoperability, and other requirements assigned to the emerging concept of an Optical Control Plane.

Robust Rate Maximization for Heterogeneous Wireless Networks under Channel Uncertainties

PubMed Central

Xu, Yongjun; Hu, Yuan; Li, Guoquan

2018-01-01

Heterogeneous wireless networks are a promising technology in next generation wireless communication networks, which has been shown to efficiently reduce the blind area of mobile communication and improve network coverage compared with the traditional wireless communication networks. In this paper, a robust power allocation problem for a two-tier heterogeneous wireless networks is formulated based on orthogonal frequency-division multiplexing technology. Under the consideration of imperfect channel state information (CSI), the robust sum-rate maximization problem is built while avoiding sever cross-tier interference to macrocell user and maintaining the minimum rate requirement of each femtocell user. To be practical, both of channel estimation errors from the femtocells to the macrocell and link uncertainties of each femtocell user are simultaneously considered in terms of outage probabilities of users. The optimization problem is analyzed under no CSI feedback with some cumulative distribution function and partial CSI with Gaussian distribution of channel estimation error. The robust optimization problem is converted into the convex optimization problem which is solved by using Lagrange dual theory and subgradient algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm by the impact of channel uncertainties on the system performance. PMID:29466315

The Role of Surface Water for the Branching Geometry of Mars' Channel Networks

NASA Astrophysics Data System (ADS)

Seybold, H. F.; Rothman, D.; Kirchner, J. W.

2016-12-01

The controversy over the origin of Mars' channel networks is almost as old as their discovery 150 years ago. In recent decades, new Mars probe missions have revealed detailed network structures, and new studies suggest that Mars once had an active hydrologic cycle. But how this water flowed and how it could have carved these huge channel networks remains unclear. A recent analysis of high-resolution data for the Continental United States suggests that climate leaves a characteristic imprint in the branching geometry of stream networks: arid regions dominated by overland or near-surface flows have much narrower branching angles than humid regions with greater groundwater recharge. Based on this result we analyze the channel networks of Mars, and find that their geometry resembles those created by near-surface and overland flows on Earth. This result gives additional support to the hypothesis that Mars once had a more active hydrologic cycle, with liquid water flowing over its surface.

The formation mechanism of defects, spiral wave in the network of neurons.

PubMed

Wu, Xinyi; Ma, Jun

2013-01-01

A regular network of neurons is constructed by using the Morris-Lecar (ML) neuron with the ion channels being considered, and the potential mechnism of the formation of a spiral wave is investigated in detail. Several spiral waves are initiated by blocking the target wave with artificial defects and/or partial blocking (poisoning) in ion channels. Furthermore, possible conditions for spiral wave formation and the effect of partial channel blocking are discussed completely. Our results are summarized as follows. 1) The emergence of a target wave depends on the transmembrane currents with diversity, which mapped from the external forcing current and this kind of diversity is associated with spatial heterogeneity in the media. 2) Distinct spiral wave could be induced to occupy the network when the target wave is broken by partially blocking the ion channels of a fraction of neurons (local poisoned area), and these generated spiral waves are similar with the spiral waves induced by artificial defects. It is confirmed that partial channel blocking of some neurons in the network could play a similar role in breaking a target wave as do artificial defects; 3) Channel noise and additive Gaussian white noise are also considered, and it is confirmed that spiral waves are also induced in the network in the presence of noise. According to the results mentioned above, we conclude that appropriate poisoning in ion channels of neurons in the network acts as 'defects' on the evolution of the spatiotemporal pattern, and accounts for the emergence of a spiral wave in the network of neurons. These results could be helpful to understand the potential cause of the formation and development of spiral waves in the cortex of a neuronal system.

The Formation Mechanism of Defects, Spiral Wave in the Network of Neurons

PubMed Central

Wu, Xinyi; Ma, Jun

2013-01-01

A regular network of neurons is constructed by using the Morris-Lecar (ML) neuron with the ion channels being considered, and the potential mechnism of the formation of a spiral wave is investigated in detail. Several spiral waves are initiated by blocking the target wave with artificial defects and/or partial blocking (poisoning) in ion channels. Furthermore, possible conditions for spiral wave formation and the effect of partial channel blocking are discussed completely. Our results are summarized as follows. 1) The emergence of a target wave depends on the transmembrane currents with diversity, which mapped from the external forcing current and this kind of diversity is associated with spatial heterogeneity in the media. 2) Distinct spiral wave could be induced to occupy the network when the target wave is broken by partially blocking the ion channels of a fraction of neurons (local poisoned area), and these generated spiral waves are similar with the spiral waves induced by artificial defects. It is confirmed that partial channel blocking of some neurons in the network could play a similar role in breaking a target wave as do artificial defects; 3) Channel noise and additive Gaussian white noise are also considered, and it is confirmed that spiral waves are also induced in the network in the presence of noise. According to the results mentioned above, we conclude that appropriate poisoning in ion channels of neurons in the network acts as ‘defects’ on the evolution of the spatiotemporal pattern, and accounts for the emergence of a spiral wave in the network of neurons. These results could be helpful to understand the potential cause of the formation and development of spiral waves in the cortex of a neuronal system. PMID:23383179

A complex valued radial basis function network for equalization of fast time varying channels.

PubMed

Gan, Q; Saratchandran, P; Sundararajan, N; Subramanian, K R

1999-01-01

This paper presents a complex valued radial basis function (RBF) network for equalization of fast time varying channels. A new method for calculating the centers of the RBF network is given. The method allows fixing the number of RBF centers even as the equalizer order is increased so that a good performance is obtained by a high-order RBF equalizer with small number of centers. Simulations are performed on time varying channels using a Rayleigh fading channel model to compare the performance of our RBF with an adaptive maximum-likelihood sequence estimator (MLSE) consisting of a channel estimator and a MLSE implemented by the Viterbi algorithm. The results show that the RBF equalizer produces superior performance with less computational complexity.

A numerical solution to define channel heads and hillslope parameters from digital topography of glacially conditioned catchments

NASA Astrophysics Data System (ADS)

Salcher, Bernhard; Baumann, Sebastian; Kober, Florian; Robl, Jörg; Heiniger, Lukas

2016-04-01

The analysis of the slope-area relationship in bedrock streams is a common way for discriminating the channel from the hillslope domain and associated landscape processes. Spatial variations of these domains are important indicators of landscape change. In fluvial catchments, this relationship is a function of contributing drainage area, channel slope and the threshold drainage area for fluvial erosion. The resulting pattern is related to climate, tectonic and underlying bedrock. These factors may become secondary in catchments affected by glacial erosion, as it is the case in many mid- to high-latitude mountain belts. The perturbation (i.e. the destruction) of an initial steady state fluvial bedrock morphology (where uplift is balanced by surface lowering rates) will tend to become successively larger if the repeated action of glacial processes exceeds the potential of fluvial readjustment during deglaciated periods. Topographic change is associated with a decrease and fragmentation of the channel network and an extension of the hillslope domain. In case of glacially conditioned catchments discrimination of the two domains remains problematic and a discrimination inconsistent. A definition is therefore highly needed considering that (i) a spatial shift in the domains affect the process and rate of erosion and (ii) topographic classifications of alpine catchments often base on channel and hillslope parameters (i.e.channel or hillslope relief). Here we propose a novel numerical approach to topographically define channel heads from digital topography in glacially conditioned mountain range catchments in order to discriminate the channel from the hillslope domain. We analyzed the topography of the southern European Central Alps, a region which (i) has been glaciated multiple times during the Quaternary, shows (ii) little lithological variations, is (iii) home of very low erodible rocks and is (iv) known as a region were tectonic processes have largely ceased. The region shows a distinct increase of mean elevation from the major overdeepend valleys near the Foreland to the alpine main divide at around 4000 m.a.s.l. within a distance of only 150 km. To define channel heads we first analyzed the variations to fine-scale topography of catchments by calculating the plan curvature at low topographic wavelengths. Higher elevated catchments more frequently impacted by glacial erosion show a higher degree in topographic flattening than catchments with a lower mean elevation where rougher fluvial (steady state) channels dominate. We found that this process of glacial destruction of fine-scale topography can well be analyzed by extracting the plan curvature from a DEM (1-30 m resolution). We furthermore found that the plan curvature frequency depends on the mean elevation of a catchment. Accordingly, the correlation between mean elevation of basins and the related density of pixels with a certain curvature is highly controlled by the used curvature threshold (e.g. used range of curvature pixels). A statistically derived optimum of the negative plan curvature was taken to define a threshold for the concavity of channels. The resulting fragmented network of channel segments was then fully integrated by utilizing a steepest descent algorithm. The upstream-most point of this fully integrated network was then defined as channel head. Our approach offers not only a consistent method to derive (i) hillslope and channel parameters in formerly glaciated catchments but also to (ii) measure the degree in glacial conditioning and therefore (iii) separating non-glacial from glacial catchments.

TDM interrogation of intensity-modulated USFBGs network based on multichannel lasers.

PubMed

Rohollahnejad, Jalal; Xia, Li; Cheng, Rui; Ran, Yanli; Rahubadde, Udaya; Zhou, Jiaao; Zhu, Lin

2017-01-23

We report a large-scale multi-channel fiber sensing network, where ultra-short FBGs (USFBGs) instead of conventional narrow-band ultra-weak FBGs are used as the sensors. In the time division multiplexing scheme of the network, each grating response is resolved as three adjacent discrete peaks. The central wavelengths of USFBGs are tracked with the differential detection, which is achieved by calculating the peak-to-peak ratio of two maximum peaks. Compared with previous large-scale hybrid multiplexing sensing networks (e.g., WDM/TDM) which typically have relatively low interrogation speed and very high complexity, the proposed system can achieve interrogation of all channel sensors through very fast and simple intensity measurements with a broad dynamic range. A proof-of-concept experiment with twenty USFBGs, at two wavelength channels, was performed and a fast static strain measurements were demonstrated, with a high average sensitivity of ~0.54dB/µƐ and wide dynamic range of over ~3000µƐ. The channel to channel switching time was 10ms and total network interrogation time was 50ms.

A Network Steganography Lab on Detecting TCP/IP Covert Channels

ERIC Educational Resources Information Center

Zseby, Tanja; Vázquez, Félix Iglesias; Bernhardt, Valentin; Frkat, Davor; Annessi, Robert

2016-01-01

This paper presents a network security laboratory to teach data analysis for detecting TCP/IP covert channels. The laboratory is mainly designed for students of electrical engineering, but is open to students of other technical disciplines with similar background. Covert channels provide a method for leaking data from protected systems, which is a…

Information origins of the chemical bond: Bond descriptors from molecular communication channels in orbital resolution

NASA Astrophysics Data System (ADS)

Nalewajski, Roman F.

The flow of information in the molecular communication networks in the (condensed) atomic orbital (AO) resolution is investigated and the plane-wave (momentum-space) interpretation of the average Fisher information in the molecular information system is given. It is argued using the quantum-mechanical superposition principle that, in the LCAO MO theory the squares of corresponding elements of the Charge and Bond-Order (CBO) matrix determine the conditional probabilities between AO, which generate the molecular communication system of the Orbital Communication Theory (OCT) of the chemical bond. The conditional-entropy ("noise," information-theoretic "covalency") and the mutual-information (information flow, information-theoretic "ionicity") descriptors of these molecular channels are related to Wiberg's covalency indices of chemical bonds. The illustrative application of OCT to the three-orbital model of the chemical bond X-Y, which is capable of describing the forward- and back-donations as well as the atom promotion accompanying the bond formation, is reported. It is demonstrated that the entropy/information characteristics of these separate bond-effects can be extracted by an appropriate reduction of the output of the molecular information channel, carried out by combining several exits into a single (condensed) one. The molecular channels in both the AO and hybrid orbital representations are examined for both the molecular and representative promolecular input probabilities.

Super-channel oriented routing, spectrum and core assignment under crosstalk limit in spatial division multiplexing elastic optical networks

NASA Astrophysics Data System (ADS)

Zhao, Yongli; Zhu, Ye; Wang, Chunhui; Yu, Xiaosong; Liu, Chuan; Liu, Binglin; Zhang, Jie

2017-07-01

With the capacity increasing in optical networks enabled by spatial division multiplexing (SDM) technology, spatial division multiplexing elastic optical networks (SDM-EONs) attract much attention from both academic and industry. Super-channel is an important type of service provisioning in SDM-EONs. This paper focuses on the issue of super-channel construction in SDM-EONs. Mixed super-channel oriented routing, spectrum and core assignment (MS-RSCA) algorithm is proposed in SDM-EONs considering inter-core crosstalk. Simulation results show that MS-RSCA can improve spectrum resource utilization and reduce blocking probability significantly compared with the baseline RSCA algorithms.

Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks

PubMed Central

Dutkiewicz, Eryk; Zheng, Guanglou

2016-01-01

As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner’s bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings. PMID:26844888

Graphene-based battery electrodes having continuous flow paths

DOEpatents

Zhang, Jiguang; Xiao, Jie; Liu, Jun; Xu, Wu; Li, Xiaolin; Wang, Deyu

2014-05-24

Some batteries can exhibit greatly improved performance by utilizing electrodes having randomly arranged graphene nanosheets forming a network of channels defining continuous flow paths through the electrode. The network of channels can provide a diffusion pathway for the liquid electrolyte and/or for reactant gases. Metal-air batteries can benefit from such electrodes. In particular Li-air batteries show extremely high capacities, wherein the network of channels allow oxygen to diffuse through the electrode and mesopores in the electrode can store discharge products.

Development of spiral wave in a regular network of excitatory neurons due to stochastic poisoning of ion channels

NASA Astrophysics Data System (ADS)

Wu, Xinyi; Ma, Jun; Li, Fan; Jia, Ya

2013-12-01

Some experimental evidences show that spiral wave could be observed in the cortex of brain, and the propagation of this spiral wave plays an important role in signal communication as a pacemaker. The profile of spiral wave generated in a numerical way is often perfect while the observed profile in experiments is not perfect and smooth. In this paper, formation and development of spiral wave in a regular network of Morris-Lecar neurons, which neurons are placed on nodes uniformly in a two-dimensional array and each node is coupled with nearest-neighbor type, are investigated by considering the effect of stochastic ion channels poisoning and channel noise. The formation and selection of spiral wave could be detected as follows. (1) External forcing currents with diversity are imposed on neurons in the network of excitatory neurons with nearest-neighbor connection, a target-like wave emerges and its potential mechanism is discussed; (2) artificial defects and local poisoned area are selected in the network to induce new wave to interact with the target wave; (3) spiral wave can be induced to occupy the network when the target wave is blocked by the artificial defects or poisoned area with regular border lines; (4) the stochastic poisoning effect is introduced by randomly modifying the border lines (areas) of specific regions in the network. It is found that spiral wave can be also developed to occupy the network under appropriate poisoning ratio. The process of growth for the poisoned area of ion channels poisoning is measured, the effect of channels noise is also investigated. It is confirmed that perfect spiral wave emerges in the network under gradient poisoning even if the channel noise is considered.

Massively parallel processor networks with optical express channels

DOEpatents

Deri, R.J.; Brooks, E.D. III; Haigh, R.E.; DeGroot, A.J.

1999-08-24

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination. 3 figs.

Massively parallel processor networks with optical express channels

DOEpatents

Deri, Robert J.; Brooks, III, Eugene D.; Haigh, Ronald E.; DeGroot, Anthony J.

1999-01-01

An optical method for separating and routing local and express channel data comprises interconnecting the nodes in a network with fiber optic cables. A single fiber optic cable carries both express channel traffic and local channel traffic, e.g., in a massively parallel processor (MPP) network. Express channel traffic is placed on, or filtered from, the fiber optic cable at a light frequency or a color different from that of the local channel traffic. The express channel traffic is thus placed on a light carrier that skips over the local intermediate nodes one-by-one by reflecting off of selective mirrors placed at each local node. The local-channel-traffic light carriers pass through the selective mirrors and are not reflected. A single fiber optic cable can thus be threaded throughout a three-dimensional matrix of nodes with the x,y,z directions of propagation encoded by the color of the respective light carriers for both local and express channel traffic. Thus frequency division multiple access is used to hierarchically separate the local and express channels to eliminate the bucket brigade latencies that would otherwise result if the express traffic had to hop between every local node to reach its ultimate destination.

Aperiodic linear networked control considering variable channel delays: application to robots coordination.

PubMed

Santos, Carlos; Espinosa, Felipe; Santiso, Enrique; Mazo, Manuel

2015-05-27

One of the main challenges in wireless cyber-physical systems is to reduce the load of the communication channel while preserving the control performance. In this way, communication resources are liberated for other applications sharing the channel bandwidth. The main contribution of this work is the design of a remote control solution based on an aperiodic and adaptive triggering mechanism considering the current network delay of multiple robotics units. Working with the actual network delay instead of the maximum one leads to abandoning this conservative assumption, since the triggering condition is fixed depending on the current state of the network. This way, the controller manages the usage of the wireless channel in order to reduce the channel delay and to improve the availability of the communication resources. The communication standard under study is the widespread IEEE 802.11g, whose channel delay is clearly uncertain. First, the adaptive self-triggered control is validated through the TrueTime simulation tool configured for the mentioned WiFi standard. Implementation results applying the aperiodic linear control laws on four P3-DX robots are also included. Both of them demonstrate the advantage of this solution in terms of network accessing and control performance with respect to periodic and non-adaptive self-triggered alternatives.

Networks of channels for self-healing composite materials

NASA Astrophysics Data System (ADS)

Bejan, A.; Lorente, S.; Wang, K.-M.

2006-08-01

This is a fundamental study of how to vascularize a self-healing composite material so that healing fluid reaches all the crack sites that may occur randomly through the material. The network of channels is built into the material and is filled with pressurized healing fluid. When a crack forms, the pressure drops at the crack site and fluid flows from the network into the crack. The objective is to discover the network configuration that is capable of delivering fluid to all the cracks the fastest. The crack site dimension and the total volume of the channels are fixed. It is argued that the network must be configured as a grid and not as a tree. Two classes of grids are considered and optimized: (i) grids with one channel diameter and regular polygonal loops (square, triangle, hexagon) and (ii) grids with two channel sizes. The best architecture of type (i) is the grid with triangular loops. The best architecture of type (ii) has a particular (optimal) ratio of diameters that departs from 1 as the crack length scale becomes smaller than the global scale of the vascularized structure from which the crack draws its healing fluid. The optimization of the ratio of channel diameters cuts in half the time of fluid delivery to the crack.

Mesoporous-silica nanofluidic channels for quick enrichment/extraction of trace pesticide molecules

NASA Astrophysics Data System (ADS)

Xu, Pengcheng; Chen, Chuanzhao; Li, Xinxin

2015-11-01

As nanofluidic channels, uniaxially oriented mesoporous-silica is, for the first time, in-situ self-assembled in a microfluidic chip for quick enrichment/extraction of ng L-1(ppt)-level organo-phosphorous (OP) pesticide residue from aqueous solution to ethanol. This micro/nano combined pre-treatment chip is essential for following gas chromatography-mass spectrometry (GC-MS) quantitative analysis. Featuring huge surface area and dense silanol groups at the inwall surface, the mesoporous-silica is uniaxially self-assembled in a micro-reservoir to form a pile of nanofluidic channels (diameter = 2.1 nm). The captured/enriched pesticide molecules in the nanochannels can be efficiently extracted by much smaller volume of ethanol due to its much higher solubility to OP. In our affirming experiment, three mixed OP pesticides of dichlorvos, paraoxon and chlorpyrifos (in water) are captured/enriched by the nano-channels and eluted/extracted by only 0.6 mL ethanol. The whole process only takes 16 min. The GC-MS quantitative results for the extracted three pesticides indicate that the extraction recovery achieves 80%. The achieved limit of quantification (LOQ) and the limit of detection (LOD) are 100 ng L-1 and 30 ng L-1, respectively. The nanofluidic-channel pre-treatment technique is promising in various application fields like agriculture and food safety security.

A picoliter-volume mixer for microfluidic analytical systems.

PubMed

He, B; Burke, B J; Zhang, X; Zhang, R; Regnier, F E

2001-05-01

Mixing confluent liquid streams is an important, but difficult operation in microfluidic systems. This paper reports the construction and characterization of a 100-pL mixer for liquids transported by electroosmotic flow. Mixing was achieved in a microfabricated device with multiple intersecting channels of varying lengths and a bimodal width distribution. All channels running parallel to the direction of flow were 5 microm in width whereas larger 27-microm-width channels ran back and forth through the parallel channel network at a 45 degrees angle. The channel network composing the mixer was approximately 10 microm deep. It was observed that little mixing of the confluent solvent streams occurred in the 100-microm-wide, 300-microm-long mixer inlet channel where mixing would be achieved almost exclusively by diffusion. In contrast, after passage through the channel network in the approximately 200-microm-length static mixer bed, mixing was complete as determined by confocal microscopy and CCD detection. Theoretical simulations were also performed in an attempt to describe the extent of mixing in microfabricated systems.

Geomorphological origin of recession curves

NASA Astrophysics Data System (ADS)

Biswal, Basudev; Marani, Marco

2010-12-01

We identify a previously undetected link between the river network morphology and key recession curves properties through a conceptual-physical model of the drainage process of the riparian unconfined aquifer. We show that the power-law exponent, α, of -dQ/dt vs. Q curves is related to the power-law exponent of N(l) vs. G(l) curves (which we show to be connected to Hack's law), where l is the downstream distance from the channel heads, N(l) is the number of channel reaches exactly located at a distance l from their channel head, and G(l) is the total length of the network located at a distance greater or equal to l from channel heads. Using Digital Terrain Models and daily discharge observations from 67 US basins we find that geomorphologic α estimates match well the values obtained from recession curves analyses. Finally, we argue that the link between recession flows and network morphology points to an important role of low-flow discharges in shaping the channel network.

Nonlinear channel equalization for QAM signal constellation using artificial neural networks.

PubMed

Patra, J C; Pal, R N; Baliarsingh, R; Panda, G

1999-01-01

Application of artificial neural networks (ANN's) to adaptive channel equalization in a digital communication system with 4-QAM signal constellation is reported in this paper. A novel computationally efficient single layer functional link ANN (FLANN) is proposed for this purpose. This network has a simple structure in which the nonlinearity is introduced by functional expansion of the input pattern by trigonometric polynomials. Because of input pattern enhancement, the FLANN is capable of forming arbitrarily nonlinear decision boundaries and can perform complex pattern classification tasks. Considering channel equalization as a nonlinear classification problem, the FLANN has been utilized for nonlinear channel equalization. The performance of the FLANN is compared with two other ANN structures [a multilayer perceptron (MLP) and a polynomial perceptron network (PPN)] along with a conventional linear LMS-based equalizer for different linear and nonlinear channel models. The effect of eigenvalue ratio (EVR) of input correlation matrix on the equalizer performance has been studied. The comparison of computational complexity involved for the three ANN structures is also provided.

Apparatus and method for data communication in an energy distribution network

DOEpatents

Hussain, Mohsin; LaPorte, Brock; Uebel, Udo; Zia, Aftab

2014-07-08

A system for communicating information on an energy distribution network is disclosed. In one embodiment, the system includes a local supervisor on a communication network, wherein the local supervisor can collect data from one or more energy generation/monitoring devices. The system also includes a command center on the communication network, wherein the command center can generate one or more commands for controlling the one or more energy generation devices. The local supervisor can periodically transmit a data signal indicative of the data to the command center via a first channel of the communication network at a first interval. The local supervisor can also periodically transmit a request for a command to the command center via a second channel of the communication network at a second interval shorter than the first interval. This channel configuration provides effective data communication without a significant increase in the use of network resources.

Geologic and physiographic controls on bed-material yield, transport, and channel morphology for alluvial and bedrock rivers, western Oregon

NASA Astrophysics Data System (ADS)

O'Connor, J. E.; Wallick, R.; Mangano, J.; Anderson, S. W.; Jones, K. L.; Keith, M. K.

2012-12-01

The rivers of western Oregon have channel beds ranging from fully alluvial to bedrock. A local history of in-stream gravel mining in conjunction with ongoing permitting concerns with respect to future extraction have prompted a series of investigations of bed-material production, transport and channel morphology across this spectrum of channel types. In western Oregon, it appears that the distribution of alluvial and bedrock channels (and many aspects of river morphology and behavior) are largely controlled by regional lithologies and the downstream consequences of different rates of bed-material supply and clast comminution. In particular, the Klamath Terrane has elevated erosion rates, steep slopes, and rock types resistant to abrasion, resulting in gravel-bed alluvial channels with high bed-material transport rates. By contrast, Coast Range drainages underlain by large areas of soft sedimentary rocks have bedrock channels owing to exceptionally rapid rates of bed-material attrition during transport. The resulting spatially distributed network controls on the distribution of alluvial and non-alluvial channels likely complicate linkages between rock uplift, bedrock incision, bed-material grain size, and profile concavity. Additionally, the alluvial channels have distinct morphologic characteristics, some of which relate strongly to transport rates. In particular, bar area correlates with estimates of bed-material flux, and this correlation is an upper bound for bar-area observations for non-alluvial reaches. Similarly, an index for transport capacity scaled by bed-material grain size correlates with estimated bed-material flux for alluvial rivers, but not for the non-alluvial rivers. Bedrock and mixed-bed channels in western Oregon have few evident broad-scale patterns or relations among reach-scale morphologic measurements or with estimated transport rates, perhaps indicating that very local lithologic, hydraulic and bed-material supply conditions exert more control on channel morphology.

Hydrodynamics and Connectivity of Channelized Floodplains: Insights from the Meandering East Fork White River, Indiana, USA

NASA Astrophysics Data System (ADS)

Czuba, J. A.; David, S. R.; Edmonds, D. A.

2017-12-01

High resolution topography reveals that meandering river floodplains in Indiana commonly have networks of channels. These floodplain channel networks are most prevalent in agricultural, low-gradient, wide floodplains. It appears that these networks are formed when floodplain channels connect oxbows to each other and the main river channel. Collectively, the channels in the floodplain create an interconnected network of pathways that convey water beginning at flows less than bankfull, and as stage increases, more of the floodplain becomes dissected by floodplain channels. In this work, we quantify the hydrodynamics and connectivity of the flow on the floodplain and in the main channel of the East Fork White River near Seymour, Indiana, USA. We constructed a two-dimensional numerical model using HECRAS of the river-floodplain system from LiDAR data and from main-channel river bathymetry to elucidate the behaviour of these floodplain channels across a range of flows. Model calibration and verification data included stage from a USGS gage, high-water marks at a high and medium flow, and an aerial photograph of inundation in the floodplain channels. The numerical model simulated flow depth and velocity, which was used to quantify connectivity of the floodplain channels, exchange between the main channel and floodplain channels, and residence time of water on the floodplain. Model simulations suggest that the floodplain channels convey roughly 50% of the total flow at what is typically considered "bankfull" flow. Overall, we present a process-based approach for analyzing complex floodplain-river systems where an individual floodplain-river system can be distilled down to a set of characteristic curves. Notably, we map the East Fork White River system to exchange-residence time space and argue that this characterization forms the basis for thinking about morphologic evolution (e.g., sediment deposition and erosion) and biogeochemistry (e.g., nitrate removal) in floodplain-river systems.

Speech enhancement based on neural networks improves speech intelligibility in noise for cochlear implant users.

PubMed

Goehring, Tobias; Bolner, Federico; Monaghan, Jessica J M; van Dijk, Bas; Zarowski, Andrzej; Bleeck, Stefan

2017-02-01

Speech understanding in noisy environments is still one of the major challenges for cochlear implant (CI) users in everyday life. We evaluated a speech enhancement algorithm based on neural networks (NNSE) for improving speech intelligibility in noise for CI users. The algorithm decomposes the noisy speech signal into time-frequency units, extracts a set of auditory-inspired features and feeds them to the neural network to produce an estimation of which frequency channels contain more perceptually important information (higher signal-to-noise ratio, SNR). This estimate is used to attenuate noise-dominated and retain speech-dominated CI channels for electrical stimulation, as in traditional n-of-m CI coding strategies. The proposed algorithm was evaluated by measuring the speech-in-noise performance of 14 CI users using three types of background noise. Two NNSE algorithms were compared: a speaker-dependent algorithm, that was trained on the target speaker used for testing, and a speaker-independent algorithm, that was trained on different speakers. Significant improvements in the intelligibility of speech in stationary and fluctuating noises were found relative to the unprocessed condition for the speaker-dependent algorithm in all noise types and for the speaker-independent algorithm in 2 out of 3 noise types. The NNSE algorithms used noise-specific neural networks that generalized to novel segments of the same noise type and worked over a range of SNRs. The proposed algorithm has the potential to improve the intelligibility of speech in noise for CI users while meeting the requirements of low computational complexity and processing delay for application in CI devices. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

High fidelity quantum teleportation assistance with quantum neural network

NASA Astrophysics Data System (ADS)

Huang, Chunhui; Wu, Bichun

2014-09-01

In this paper, a high fidelity scheme of quantum teleportation based on quantum neural network (QNN) is proposed. The QNN is composed of multi-bit control-not gates. The quantum teleportation of a qubit state via two-qubit entangled channels is investigated by solving the master equation in Lindblad operators with a noisy environment. To ensure the security of quantum teleportation, the indirect training of QNN is employed. Only 10% of teleported information is extracted for the training of QNN parameters. Then the outputs are corrected by the other QNN at Bob's side. We build a random series of numbers ranged in [0, π] as inputs and simulate the properties of our teleportation scheme. The results show that the fidelity of quantum teleportation system is significantly improved to approach 1 by the error-correction of QNN. It illustrates that the distortion can be eliminated perfectly and the high fidelity of quantum teleportation could be implemented.

A model for simulation of flow in singular and interconnected channels

USGS Publications Warehouse

Schaffranek, Raymond W.; Baltzer, R.A.; Goldberg, D.E.

1981-01-01

A one-dimensional numerical model is presented for simulating the unsteady flow in singular riverine or estuarine reaches and in networks of reaches composed of interconnected channels. The model is both general and flexible in that it can be used to simulate a wide range of flow conditions for various channel configurations. The channel geometry of the network to be modeled should be sufficiently simple so as to lend itself to characterization in one spatial dimension. The flow must be substantially homogenous in density, and hydrostatic pressure must prevail everywhere in the network channels. The slope of each channel bottom ought to be mild and reasonably constant over its length so that the flow remains subcritical. The model accommodates tributary inflows and diversions and includes the effects of wind shear on the water surface as a forcing function in the flow equations. Water-surface elevations and flow discharges are computed at channel junctions, as well as at specified intermediate locations within the network channels. The one-dimensional branch-network flow model uses a four-point, implicit, finite-difference approximation of the unsteady-flow equations. The flow equations are linearized over a time step, and branch transformations are formulated that describe the relationship between the unknowns at the end points of the channels. The resultant matrix of branch-transformation equations and required boundary-condition equations is solved by Gaussian elimination using maximum pivot strategy. Five example applications of the flow model are illustrated. The applications cover such diverse conditions as a singular upland river reach in which unsteady flow results from hydropower regulations, coastal rivers composed of sequentially connected reaches subject to unsteady tide-driven flow, and a multiply connected network of channels whose flow is principally governed by wind tides and seiches in adjoining lakes. The report includes a listing of the FORTRAN IV computer program and a description of the input data requirements. Model supporting programs for the processing and input of initial and boundary-value data are identified, various model output formats are illustrated, and instructions are given to permit the production of graphical output using the line printer, electromechanical pen plotters, cathode-ray-tube display units, or microfilm recorders.

Audio Watermark Embedding Technique Applying Auditory Stream Segregation: "G-encoder Mark" Able to Be Extracted by Mobile Phone

NASA Astrophysics Data System (ADS)

Modegi, Toshio

We are developing audio watermarking techniques which enable extraction of embedded data by cell phones. For that we have to embed data onto frequency ranges, where our auditory response is prominent, therefore data embedding will cause much auditory noises. Previously we have proposed applying a two-channel stereo play-back feature, where noises generated by a data embedded left-channel signal will be reduced by the other right-channel signal. However, this proposal has practical problems of restricting extracting terminal location. In this paper, we propose synthesizing the noise reducing right-channel signal with the left-signal and reduces noises completely by generating an auditory stream segregation phenomenon to users. This newly proposed makes the noise reducing right-channel signal unnecessary and supports monaural play-back operations. Moreover, we propose a wide-band embedding method causing dual auditory stream segregation phenomena, which enables data embedding on whole public phone frequency ranges and stable extractions with 3-G mobile phones. From these proposals, extraction precisions become higher than those by the previously proposed method whereas the quality damages of embedded signals become smaller. In this paper we present an abstract of our newly proposed method and experimental results comparing with those by the previously proposed method.

Sterile Reverse Osmosis Water Combined with Friction Are Optimal for Channel and Lever Cavity Sample Collection of Flexible Duodenoscopes.

PubMed

Alfa, Michelle J; Singh, Harminder; Nugent, Zoann; Duerksen, Donald; Schultz, Gale; Reidy, Carol; DeGagne, Patricia; Olson, Nancy

2017-01-01

Simulated-use buildup biofilm (BBF) model was used to assess various extraction fluids and friction methods to determine the optimal sample collection method for polytetrafluorethylene channels. In addition, simulated-use testing was performed for the channel and lever cavity of duodenoscopes. BBF was formed in polytetrafluorethylene channels using Enterococcus faecalis, Escherichia coli , and Pseudomonas aeruginosa . Sterile reverse osmosis (RO) water, and phosphate-buffered saline with and without Tween80 as well as two neutralizing broths (Letheen and Dey-Engley) were each assessed with and without friction. Neutralizer was added immediately after sample collection and samples concentrated using centrifugation. Simulated-use testing was done using TJF-Q180V and JF-140F Olympus duodenoscopes. Despite variability in the bacterial CFU in the BBF model, none of the extraction fluids tested were significantly better than RO. Borescope examination showed far less residual material when friction was part of the extraction protocol. The RO for flush-brush-flush (FBF) extraction provided significantly better recovery of E. coli ( p  = 0.02) from duodenoscope lever cavities compared to the CDC flush method. We recommend RO with friction for FBF extraction of the channel and lever cavity of duodenoscopes. Neutralizer and sample concentration optimize recovery of viable bacteria on culture.

Beamspace Multiple Input Multiple Output. Part II: Steerable Antennas in Mobile Ad Hoc Networks

DTIC Science & Technology

2016-09-01

to the transmitter with half the channel transfer function power , since the actual receiver dwells on each channel only half the time. Fourth diagram...steering in a wireless network to maximize signal power and minimize interference [8–10]. The ability to switch beams adds another diversity dimension to...channel transfer function power , since the actual receiver dwells on each channel only half the time. Fourth diagram: The transmit array sends four

Diffusion in random networks

DOE PAGES

Zhang, Duan Z.; Padrino, Juan C.

2017-06-01

The ensemble averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of pockets connected by tortuous channels. Inside a channel, fluid transport is assumed to be governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pocket mass density. The so-called dual-porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem,more » we consider the one-dimensional mass diffusion in a semi-infinite domain. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt $-$1/4 rather than xt $-$1/2 as in the traditional theory. We found this early time similarity can be explained by random walk theory through the network.« less

Optimal design of mixed-media packet-switching networks - Routing and capacity assignment

NASA Technical Reports Server (NTRS)

Huynh, D.; Kuo, F. F.; Kobayashi, H.

1977-01-01

This paper considers a mixed-media packet-switched computer communication network which consists of a low-delay terrestrial store-and-forward subnet combined with a low-cost high-bandwidth satellite subnet. We show how to route traffic via ground and/or satellite links by means of static, deterministic procedures and assign capacities to channels subject to a given linear cost such that the network average delay is minimized. Two operational schemes for this network model are investigated: one is a scheme in which the satellite channel is used as a slotted ALOHA channel; the other is a new multiaccess scheme we propose in which whenever a channel collision occurs, retransmission of the involved packets will route through ground links to their destinations. The performance of both schemes is evaluated and compared in terms of cost and average packet delay tradeoffs for some examples. The results offer guidelines for the design and optimal utilization of mixed-media networks.

Reconstruction of an infrared band of meteorological satellite imagery with abductive networks

NASA Technical Reports Server (NTRS)

Singer, Harvey A.; Cockayne, John E.; Versteegen, Peter L.

1995-01-01

As the current fleet of meteorological satellites age, the accuracy of the imagery sensed on a spectral channel of the image scanning system is continually and progressively degraded by noise. In time, that data may even become unusable. We describe a novel approach to the reconstruction of the noisy satellite imagery according to empirical functional relationships that tie the spectral channels together. Abductive networks are applied to automatically learn the empirical functional relationships between the data sensed on the other spectral channels to calculate the data that should have been sensed on the corrupted channel. Using imagery unaffected by noise, it is demonstrated that abductive networks correctly predict the noise-free observed data.

In-service communication channel sensing based on reflectometry for TWDM-PON systems

NASA Astrophysics Data System (ADS)

Iida, Daisuke; Kuwano, Shigeru; Terada, Jun

2014-05-01

Many base stations are accommodated in TWDM-PON based mobile backhaul and fronthaul networks for future radio access, and failed connections in an optical network unit (ONU) wavelength channel severely degrade system performance. A cost effective in-service ONU wavelength channel monitor is essential to ensure proper system operation without failed connections. To address this issue we propose a reflectometry-based remote sensing method that provides wavelength channel information with the optical line terminal (OLT)-ONU distance. The method realizes real-time monitoring of ONU wavelength channels without signal quality degradation. Experimental results show it achieves wavelength channel distinction with high distance resolution.

Multiple-access relaying with network coding: iterative network/channel decoding with imperfect CSI

NASA Astrophysics Data System (ADS)

Vu, Xuan-Thang; Renzo, Marco Di; Duhamel, Pierre

2013-12-01

In this paper, we study the performance of the four-node multiple-access relay channel with binary Network Coding (NC) in various Rayleigh fading scenarios. In particular, two relay protocols, decode-and-forward (DF) and demodulate-and-forward (DMF) are considered. In the first case, channel decoding is performed at the relay before NC and forwarding. In the second case, only demodulation is performed at the relay. The contributions of the paper are as follows: (1) two joint network/channel decoding (JNCD) algorithms, which take into account possible decoding error at the relay, are developed in both DF and DMF relay protocols; (2) both perfect channel state information (CSI) and imperfect CSI at receivers are studied. In addition, we propose a practical method to forward the relays error characterization to the destination (quantization of the BER). This results in a fully practical scheme. (3) We show by simulation that the number of pilot symbols only affects the coding gain but not the diversity order, and that quantization accuracy affects both coding gain and diversity order. Moreover, when compared with the recent results using DMF protocol, our proposed DF protocol algorithm shows an improvement of 4 dB in fully interleaved Rayleigh fading channels and 0.7 dB in block Rayleigh fading channels.

A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks.

PubMed

Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

2016-10-12

Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel.

A Novel Dynamic Spectrum Access Framework Based on Reinforcement Learning for Cognitive Radio Sensor Networks

PubMed Central

Lin, Yun; Wang, Chao; Wang, Jiaxing; Dou, Zheng

2016-01-01

Cognitive radio sensor networks are one of the kinds of application where cognitive techniques can be adopted and have many potential applications, challenges and future research trends. According to the research surveys, dynamic spectrum access is an important and necessary technology for future cognitive sensor networks. Traditional methods of dynamic spectrum access are based on spectrum holes and they have some drawbacks, such as low accessibility and high interruptibility, which negatively affect the transmission performance of the sensor networks. To address this problem, in this paper a new initialization mechanism is proposed to establish a communication link and set up a sensor network without adopting spectrum holes to convey control information. Specifically, firstly a transmission channel model for analyzing the maximum accessible capacity for three different polices in a fading environment is discussed. Secondly, a hybrid spectrum access algorithm based on a reinforcement learning model is proposed for the power allocation problem of both the transmission channel and the control channel. Finally, extensive simulations have been conducted and simulation results show that this new algorithm provides a significant improvement in terms of the tradeoff between the control channel reliability and the efficiency of the transmission channel. PMID:27754316

Entanglement of spin waves among four quantum memories.

PubMed

Choi, K S; Goban, A; Papp, S B; van Enk, S J; Kimble, H J

2010-11-18

Quantum networks are composed of quantum nodes that interact coherently through quantum channels, and open a broad frontier of scientific opportunities. For example, a quantum network can serve as a 'web' for connecting quantum processors for computation and communication, or as a 'simulator' allowing investigations of quantum critical phenomena arising from interactions among the nodes mediated by the channels. The physical realization of quantum networks generically requires dynamical systems capable of generating and storing entangled states among multiple quantum memories, and efficiently transferring stored entanglement into quantum channels for distribution across the network. Although such capabilities have been demonstrated for diverse bipartite systems, entangled states have not been achieved for interconnects capable of 'mapping' multipartite entanglement stored in quantum memories to quantum channels. Here we demonstrate measurement-induced entanglement stored in four atomic memories; user-controlled, coherent transfer of the atomic entanglement to four photonic channels; and characterization of the full quadripartite entanglement using quantum uncertainty relations. Our work therefore constitutes an advance in the distribution of multipartite entanglement across quantum networks. We also show that our entanglement verification method is suitable for studying the entanglement order of condensed-matter systems in thermal equilibrium.

Rock Tea extract (Jasonia glutinosa) relaxes rat aortic smooth muscle by inhibition of L-type Ca(2+) channels.

PubMed

Valero, Marta Sofía; Oliván-Viguera, Aida; Garrido, Irene; Langa, Elisa; Berzosa, César; López, Víctor; Gómez-Rincón, Carlota; Murillo, María Divina; Köhler, Ralf

2015-12-01

In traditional herbal medicine, Rock Tea (Jasonia glutinosa) is known for its prophylactic and therapeutic value in various disorders including arterial hypertension. However, the mechanism by which Rock Tea exerts blood pressure-lowering actions has not been elucidated yet. Our aim was to demonstrate vasorelaxing effects of Rock Tea extract and to reveal its possible action mechanism. Isometric myography was conducted on high-K+-precontracted rings from rat thoracic aorta and tested extracts at concentrations of 0.5-5 mg/ml. Whole-cell patch-clamp experiments were performed in rat aortic vascular smooth muscle cells (line A7r5) to determine blocking effects on L-type Ca(2+) channels. Rock Tea extract relaxed the aorta contracted by high [K+] concentration dependently with an EC50 of ≈2.4 mg/ml and produced ≈75 % relaxation at the highest concentration tested. The L-type Ca(2+) channel blocker, verapamil (10(-6) M), had similar effects. Rock Tea extract had no effect in nominally Ca(2+)-free high-K(+) buffer but significantly inhibited contractions to re-addition of Ca(2+). Rock Tea extract inhibited the contractions induced by the L-type Ca(2+) channel activator Bay K 8644 (10(-5) M) and by phenylephrine (10(-6) M). Rock Tea extract and Y-27632 (10(-6) M), Rho-kinase inhibitor, had similar effects and the respective effects were not additive. Patch-clamp experiments demonstrated that Rock Tea extract (2.5 mg/ml) virtually abolished L-type Ca(2+) currents in A7r5. We conclude that Rock Tea extract produced vasorelaxation of rat aorta and that this relaxant effect is mediated by inhibition of L-type Ca(2+) channels. Rock Tea extracts may be of phytomedicinal value for prevention and adjuvant treatment of hypertension and other cardiovascular diseases.

Channel characterization using multiple-point geostatistics, neural network, and modern analogy: A case study from a carbonate reservoir, southwest Iran

NASA Astrophysics Data System (ADS)

Hashemi, Seyyedhossein; Javaherian, Abdolrahim; Ataee-pour, Majid; Tahmasebi, Pejman; Khoshdel, Hossein

2014-12-01

In facies modeling, the ideal objective is to integrate different sources of data to generate a model that has the highest consistency to reality with respect to geological shapes and their facies architectures. Multiple-point (geo)statistics (MPS) is a tool that gives the opportunity of reaching this goal via defining a training image (TI). A facies modeling workflow was conducted on a carbonate reservoir located southwest Iran. Through a sequence stratigraphic correlation among the wells, it was revealed that the interval under a modeling process was deposited in a tidal flat environment. Bahamas tidal flat environment which is one of the most well studied modern carbonate tidal flats was considered to be the source of required information for modeling a TI. In parallel, a neural network probability cube was generated based on a set of attributes derived from 3D seismic cube to be applied into the MPS algorithm as a soft conditioning data. Moreover, extracted channel bodies and drilled well log facies came to the modeling as hard data. Combination of these constraints resulted to a facies model which was greatly consistent to the geological scenarios. This study showed how analogy of modern occurrences can be set as the foundation for generating a training image. Channel morphology and facies types currently being deposited, which are crucial for modeling a training image, was inferred from modern occurrences. However, there were some practical considerations concerning the MPS algorithm used for facies simulation. The main limitation was the huge amount of RAM and CPU-time needed to perform simulations.

An optofluidic channel model for in vivo nanosensor networks in human blood

NASA Astrophysics Data System (ADS)

Johari, Pedram; Jornet, Josep M.

2017-05-01

In vivo Wireless Nanosensor Networks (iWNSNs) consist of nano-sized communicating devices with unprece- dented sensing and actuation capabilities, which are able to operate inside the human body. iWNSNs are a disruptive technology that enables the monitoring and control of biological processes at the cellular and sub- cellular levels. Compared to ex vivo measurements, which are conducted on samples extracted from the human body, iWNSNs can track (sub) cellular processes when and where they occur. Major progress in the field of na- noelectronics, nanophotonics and wireless communication is enabling the interconnection of nanosensors. Among others, plasmonic nanolasers with sub-micrometric footprint, plasmonic nano-antennas able to confine light in nanometric structures, and single-photon detectors with unrivaled sensitivity, enable the communication among implanted nanosensors in the near infrared and optical transmission windows. Motivated by these results, in this paper, an optofluidic channel model is developed to investigate the communication properties and temporal dynamics between a pair of in vivo nanosensors in the human blood. The developed model builds upon the authors' recent work on light propagation modeling through multi-layered single cells and cell assemblies and takes into account the geometric, electromagnetic and microfluidic properties of red blood cells in the human circulatory system. The proposed model guides the development of practical communication strategies among nanosensors, and paves the way through new nano-biosensing strategies able to identify diseases by detecting the slight changes in the channel impulse response, caused by either the change in shape of the blood cells or the presence of pathogens.

The optical potential on the lattice

DOE PAGES

Agadjanov, Dimitri; Doring, Michael; Mai, Maxim; ...

2016-06-08

The extraction of hadron-hadron scattering parameters from lattice data by using the Luscher approach becomes increasingly complicated in the presence of inelastic channels. We propose a method for the direct extraction of the complex hadron-hadron optical potential on the lattice, which does not require the use of the multi-channel Luscher formalism. Furthermore, this method is applicable without modifications if some inelastic channels contain three or more particles.

Optimal Performance Monitoring of Hybrid Mid-Infrared Wavelength MIMO Free Space Optical and RF Wireless Networks in Fading Channels

NASA Astrophysics Data System (ADS)

Schmidt, Barnet Michael

An optimal performance monitoring metric for a hybrid free space optical and radio-frequency (RF) wireless network, the Outage Capacity Objective Function, is analytically developed and studied. Current and traditional methods of performance monitoring of both optical and RF wireless networks are centered on measurement of physical layer parameters, the most common being signal-to-noise ratio, error rate, Q factor, and eye diagrams, occasionally combined with link-layer measurements such as data throughput, retransmission rate, and/or lost packet rate. Network management systems frequently attempt to predict or forestall network failures by observing degradations of these parameters and to attempt mitigation (such as offloading traffic, increasing transmitter power, reducing the data rate, or combinations thereof) prior to the failure. These methods are limited by the frequent low sensitivity of the physical layer parameters to the atmospheric optical conditions (measured by optical signal-to-noise ratio) and the radio frequency fading channel conditions (measured by signal-to-interference ratio). As a result of low sensitivity, measurements of this type frequently are unable to predict impending failures sufficiently in advance for the network management system to take corrective action prior to the failure. We derive and apply an optimal measure of hybrid network performance based on the outage capacity of the hybrid optical and RF channel, the outage capacity objective function. The objective function provides high sensitivity and reliable failure prediction, and considers both the effects of atmospheric optical impairments on the performance of the free space optical segment as well as the effect of RF channel impairments on the radio frequency segment. The radio frequency segment analysis considers the three most common RF channel fading statistics: Rayleigh, Ricean, and Nakagami-m. The novel application of information theory to the underlying physics of the gamma-gamma optical channel and radio fading channels in determining the joint hybrid channel outage capacity provides the best performance estimate under any given set of operating conditions. It is shown that, unlike traditional physical layer performance monitoring techniques, the objective function based upon the outage capacity of the hybrid channel at any combination of OSNR and SIR, is able to predict channel degradation and failure well in advance of the actual outage. An outage in the information-theoretic definition occurs when the offered load exceeds the outage capacity under the current conditions of OSNR and SIR. The optical channel is operated at the "long" mid-infrared wavelength of 10000 nm. which provides improved resistance to scattering compared to shorter wavelengths such as 1550 nm.

Which DEM is best for analyzing fluvial landscape development in mountainous terrains?

NASA Astrophysics Data System (ADS)

Boulton, Sarah J.; Stokes, Martin

2018-06-01

Regional studies of fluvial landforms and long-term (Quaternary) landscape development in remote mountain landscapes routinely use satellite-derived DEM data sets. The SRTM and ASTER DEMs are the most commonly utilised because of their longer availability, free cost, and ease of access. However, rapid technological developments mean that newer and higher resolution DEM data sets such as ALOS World 3D (AW3D) and TanDEM-X are being released to the scientific community. Geomorphologists are thus faced with an increasingly problematic challenge of selecting an appropriate DEM for their landscape analyses. Here, we test the application of four medium resolution DEM products (30 m = SRTM, ASTER, AW3D; 12 m = TanDEM-X) for qualitative and quantitative analysis of a fluvial mountain landscape using the Dades River catchment (High Atlas Mountains, Morocco). This landscape comprises significant DEM remote sensing challenges, notably a high mountain relief, steep slopes, and a deeply incised high sinuosity drainage network with narrow canyon/gorge reaches. Our goal was to see which DEM produced the most representative best fit drainage network and meaningful quantification. To achieve this, we used ArcGIS and Stream Profiler platforms to generate catchment hillshade and slope rasters and to extract drainage network, channel long profile and channel slope, and area data. TanDEM-X produces the clearest landscape representation but with channel routing errors in localised high relief areas. Thirty-metre DEMs are smoother and less detailed, but the AW3D shows the closest fit to the real drainage network configuration. The TanDEM-X elevation values are the closest to field-derived GPS measurements. Long profiles exhibit similar shapes but with minor differences in length, elevation, and the degree of noise/smoothing, with AW3D producing the best representation. Slope-area plots display similarly positioned slope-break knickpoints with modest differences in steepness and concavity indices, but again best represented by AW3D. Collectively, our study shows that despite the higher effective resolution of TanDEM-X (12 m), the AW3D (30 m) data performs strongly across all analyses suggesting that it currently offers the greatest potential for regional mountain geomorphological analyses.

Application of a neural network for reflectance spectrum classification

NASA Astrophysics Data System (ADS)

Yang, Gefei; Gartley, Michael

2017-05-01

Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasari, Venkat; Sadlier, Ronald J; Geerhart, Mr. Billy

Well-defined and stable quantum networks are essential to realize functional quantum applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. We develop new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

An improved approximate network blocking probability model for all-optical WDM Networks with heterogeneous link capacities

NASA Astrophysics Data System (ADS)

Khan, Akhtar Nawaz

2017-11-01

Currently, analytical models are used to compute approximate blocking probabilities in opaque and all-optical WDM networks with the homogeneous link capacities. Existing analytical models can also be extended to opaque WDM networking with heterogeneous link capacities due to the wavelength conversion at each switch node. However, existing analytical models cannot be utilized for all-optical WDM networking with heterogeneous structure of link capacities due to the wavelength continuity constraint and unequal numbers of wavelength channels on different links. In this work, a mathematical model is extended for computing approximate network blocking probabilities in heterogeneous all-optical WDM networks in which the path blocking is dominated by the link along the path with fewer number of wavelength channels. A wavelength assignment scheme is also proposed for dynamic traffic, termed as last-fit-first wavelength assignment, in which a wavelength channel with maximum index is assigned first to a lightpath request. Due to heterogeneous structure of link capacities and the wavelength continuity constraint, the wavelength channels with maximum indexes are utilized for minimum hop routes. Similarly, the wavelength channels with minimum indexes are utilized for multi-hop routes between source and destination pairs. The proposed scheme has lower blocking probability values compared to the existing heuristic for wavelength assignments. Finally, numerical results are computed in different network scenarios which are approximately equal to values obtained from simulations. Since January 2016, he is serving as Head of Department and an Assistant Professor in the Department of Electrical Engineering at UET, Peshawar-Jalozai Campus, Pakistan. From May 2013 to June 2015, he served Department of Telecommunication Engineering as an Assistant Professor at UET, Peshawar-Mardan Campus, Pakistan. He also worked as an International Internship scholar in the Fukuda Laboratory, National Institute of Informatics, Tokyo, Japan on the topic large-scale simulation for internet topology analysis. His research interests include design and analysis of optical WDM networks, network algorithms, network routing, and network resource optimization problems.

Microfluidic process monitor for industrial solvent extraction system

DOEpatents

Gelis, Artem; Pereira, Candido; Nichols, Kevin Paul Flood

2016-01-12

The present invention provides a system for solvent extraction utilizing a first electrode with a raised area formed on its surface, which defines a portion of a microfluidic channel; a second electrode with a flat surface, defining another portion of the microfluidic channel that opposes the raised area of the first electrode; a reversibly deformable substrate disposed between the first electrode and second electrode, adapted to accommodate the raised area of the first electrode and having a portion that extends beyond the raised area of the first electrode, that portion defining the remaining portions of the microfluidic channel; and an electrolyte of at least two immiscible liquids that flows through the microfluidic channel. Also provided is a system for performing multiple solvent extractions utilizing several microfluidic chips or unit operations connected in series.

A New Hybrid Scheme for Preventing Channel Interference and Collision in Mobile Networks

NASA Astrophysics Data System (ADS)

Kim, Kyungjun; Han, Kijun

This paper proposes a new hybrid scheme based on a given set of channels for preventing channel interference and collision in mobile networks. The proposed scheme is designed for improving system performance, focusing on enhancement of performance related to path breakage and channel interference. The objective of this scheme is to improve the performance of inter-node communication. Simulation results from this paper show that the new hybrid scheme can reduce a more control message overhead than a conventional random scheme.

Complex Networks/Foundations of Information Systems

DTIC Science & Technology

2013-03-06

the benefit of feedback or dynamic correlations in coding and protocol. Using Renyi correlation analysis and entropy to model this wider class of...dynamic heterogeneous conditions. Lizhong Zheng, MIT Renyi Channel Correlation Analysis (connected to geometric curvature) Network Channel

Geomorphic analyses from space imagery

NASA Technical Reports Server (NTRS)

Morisawa, M.

1985-01-01

One of the most obvious applications of space imagery to geomorphological analyses is in the study of drainage patterns and channel networks. LANDSAT, high altitude photography and other types of remote sensing imagery are excellent for depicting stream networks on a regional scale because of their broad coverage in a single image. They offer a valuable tool for comparing and analyzing drainage patterns and channel networks all over the world. Three aspects considered in this geomorphological study are: (1) the origin, evolution and rates of development of drainage systems; (2) the topological studies of network and channel arrangements; and (3) the adjustment of streams to tectonic events and geologic structure (i.e., the mode and rate of adjustment).

A fast button surface defects detection method based on convolutional neural network

NASA Astrophysics Data System (ADS)

Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

2018-01-01

Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

In silico determination of the effect of multi-target drugs on calcium dynamics signaling network underlying sea urchin spermatozoa motility.

PubMed

Espinal-Enríquez, Jesús; Darszon, Alberto; Guerrero, Adán; Martínez-Mekler, Gustavo

2014-01-01

The motility of spermatozoa of both Lytechinus pictus and Strongylocentrotus purpuratus sea urchin species is modulated by the egg-derived decapeptide speract via an oscillatory [Ca2+]-dependent signaling pathway. Comprehension of this pathway is hence directly related to the understanding of regulated sperm swimming. Niflumic acid (NFA), a nonsteroidal anti-inflammatory drug alters several ion channels. Though unspecific, NFA profoundly affects how sea urchin sperm respond to speract, increasing the [Ca2+]i oscillation period, amplitude, peak and average level values of the responses in immobilized and swimming cells. A previous logical network model we developed for the [Ca2+] dynamics of speract signaling cascade in sea urchin sperm allows integrated dissection of individual and multiple actions of NFA. Among the channels affected by NFA are: hyperpolarization-activated and cyclic nucleotide gated Na+ channels (HCN), [Ca2+]-dependent Cl- channels (CaCC) and [Ca2+]-dependent K+ channels (CaKC), all present in the sea urchin genome. Here, using our model we investigated the effect of blocking in silico HCN and CaCC channels suggested by experiments. Regarding CaKC channels, arguments can be provided for either their blockage or activation by NFA. Our study yielded two scenarios compliant with experimental observations: i) under CaKC inhibition, this [Ca2+]-dependent K+ channel should be different from the Slo1 channel and ii) under activation of the CaKC channel, another [Ca2+] channel not considered previously in the network is required, such as the pH-dependent CatSper channel. Additionally, our findings predict cause-effect relations resulting from a selective inhibition of those channels. Knowledge of these relations may be of consequence for a variety of electrophysiological studies and have an impact on drug related investigations. Our study contributes to a better grasp of the network dynamics and suggests further experimental work.

In Silico Determination of the Effect of Multi-Target Drugs on Calcium Dynamics Signaling Network Underlying Sea Urchin Spermatozoa Motility

PubMed Central

Espinal-Enríquez, Jesús; Darszon, Alberto; Guerrero, Adán; Martínez-Mekler, Gustavo

2014-01-01

The motility of spermatozoa of both Lytechinus pictus and Strongylocentrotus purpuratus sea urchin species is modulated by the egg-derived decapeptide speract via an oscillatory [Ca2+]-dependent signaling pathway. Comprehension of this pathway is hence directly related to the understanding of regulated sperm swimming. Niflumic acid (NFA), a nonsteroidal anti-inflammatory drug alters several ion channels. Though unspecific, NFA profoundly affects how sea urchin sperm respond to speract, increasing the [Ca2+]i oscillation period, amplitude, peak and average level values of the responses in immobilized and swimming cells. A previous logical network model we developed for the [Ca2+] dynamics of speract signaling cascade in sea urchin sperm allows integrated dissection of individual and multiple actions of NFA. Among the channels affected by NFA are: hyperpolarization-activated and cyclic nucleotide gated Na+ channels (HCN), [Ca2+]-dependent Cl− channels (CaCC) and [Ca2+]-dependent K+ channels (CaKC), all present in the sea urchin genome. Here, using our model we investigated the effect of blocking in silico HCN and CaCC channels suggested by experiments. Regarding CaKC channels, arguments can be provided for either their blockage or activation by NFA. Our study yielded two scenarios compliant with experimental observations: i) under CaKC inhibition, this [Ca2+]-dependent K+ channel should be different from the Slo1 channel and ii) under activation of the CaKC channel, another [Ca2+] channel not considered previously in the network is required, such as the pH-dependent CatSper channel. Additionally, our findings predict cause-effect relations resulting from a selective inhibition of those channels. Knowledge of these relations may be of consequence for a variety of electrophysiological studies and have an impact on drug related investigations. Our study contributes to a better grasp of the network dynamics and suggests further experimental work. PMID:25162222

Architectures and protocols for an integrated satellite-terrestrial mobile system

NASA Technical Reports Server (NTRS)

Delre, E.; Dellipriscoli, F.; Iannucci, P.; Menolascino, R.; Settimo, F.

1993-01-01

This paper aims to depict some basic concepts related to the definition of an integrated system for mobile communications, consisting of a satellite network and a terrestrial cellular network. In particular three aspects are discussed: (1) architecture definition for the satellite network; (2) assignment strategy of the satellite channels; and (3) definition of 'internetworking procedures' between cellular and satellite network, according to the selected architecture and the satellite channel assignment strategy.

A generalized optimization principle for asymmetric branching in fluidic networks

PubMed Central

Stephenson, David

2016-01-01

When applied to a branching network, Murray’s law states that the optimal branching of vascular networks is achieved when the cube of the parent channel radius is equal to the sum of the cubes of the daughter channel radii. It is considered integral to understanding biological networks and for the biomimetic design of artificial fluidic systems. However, despite its ubiquity, we demonstrate that Murray’s law is only optimal (i.e. maximizes flow conductance per unit volume) for symmetric branching, where the local optimization of each individual channel corresponds to the global optimum of the network as a whole. In this paper, we present a generalized law that is valid for asymmetric branching, for any cross-sectional shape, and for a range of fluidic models. We verify our analytical solutions with the numerical optimization of a bifurcating fluidic network for the examples of laminar, turbulent and non-Newtonian fluid flows. PMID:27493583

Improved Iterative Decoding of Network-Channel Codes for Multiple-Access Relay Channel.

PubMed

Majumder, Saikat; Verma, Shrish

2015-01-01

Cooperative communication using relay nodes is one of the most effective means of exploiting space diversity for low cost nodes in wireless network. In cooperative communication, users, besides communicating their own information, also relay the information of other users. In this paper we investigate a scheme where cooperation is achieved using a common relay node which performs network coding to provide space diversity for two information nodes transmitting to a base station. We propose a scheme which uses Reed-Solomon error correcting code for encoding the information bit at the user nodes and convolutional code as network code, instead of XOR based network coding. Based on this encoder, we propose iterative soft decoding of joint network-channel code by treating it as a concatenated Reed-Solomon convolutional code. Simulation results show significant improvement in performance compared to existing scheme based on compound codes.

Comparative study of mobility extraction methods in p-type polycrystalline silicon thin film transistors

NASA Astrophysics Data System (ADS)

Liu, Kai; Liu, Yuan; Liu, Yu-Rong; En, Yun-Fei; Li, Bin

2017-07-01

Channel mobility in the p-type polycrystalline silicon thin film transistors (poly-Si TFTs) is extracted using Hoffman method, linear region transconductance method and multi-frequency C-V method. Due to the non-negligible errors when neglecting the dependence of gate-source voltage on the effective mobility, the extracted mobility results are overestimated using linear region transconductance method and Hoffman method, especially in the lower gate-source voltage region. By considering of the distribution of localized states in the band-gap, the frequency independent capacitance due to localized charges in the sub-gap states and due to channel free electron charges in the conduction band were extracted using multi-frequency C-V method. Therefore, channel mobility was extracted accurately based on the charge transport theory. In addition, the effect of electrical field dependent mobility degradation was also considered in the higher gate-source voltage region. In the end, the extracted mobility results in the poly-Si TFTs using these three methods are compared and analyzed.

Martian channels and valleys - Their characteristics, distribution, and age

NASA Technical Reports Server (NTRS)

Carr, M. H.; Clow, G. D.

1981-01-01

The distribution and ages of Martian channels and valleys, which are generally believed to have been cut by running water, are examined with particular emphasis on the small branching networks referred to as runoff channels or valley networks. Valleys at latitudes from 65 deg S to 65 deg N were surveyed on Viking images at resolutions between 125 and 300 m. Almost all of the valleys are found in the old cratered terrain, in areas characterized by high elevations, low albedos and low violet/red ratios. The networks are deduced to have formed early in the history of the planet, with a formation rate declining rapidly shortly after the decline of the cratering rate 3.9 billion years ago. Two types of outflow channels are distinguished: unconfined, in which broad swaths of terrain are scoured, and confined, in which flow is restricted to discrete channels. Both types start at local sources, and have formed episodically throughout Martian history. Fretted channels, found mainly in two latitude belts characterized by relatively rapid erosion along escarpments, are explained by the lateral enlargement of other channels by mass wasting.

A computational study on convolutional feature combination strategies for grade classification in colon cancer using fluorescence microscopy data

NASA Astrophysics Data System (ADS)

Chowdhury, Aritra; Sevinsky, Christopher J.; Santamaria-Pang, Alberto; Yener, Bülent

2017-03-01

The cancer diagnostic workflow is typically performed by highly specialized and trained pathologists, for which analysis is expensive both in terms of time and money. This work focuses on grade classification in colon cancer. The analysis is performed over 3 protein markers; namely E-cadherin, beta actin and colagenIV. In addition, we also use a virtual Hematoxylin and Eosin (HE) stain. This study involves a comparison of various ways in which we can manipulate the information over the 4 different images of the tissue samples and come up with a coherent and unified response based on the data at our disposal. Pre- trained convolutional neural networks (CNNs) is the method of choice for feature extraction. The AlexNet architecture trained on the ImageNet database is used for this purpose. We extract a 4096 dimensional feature vector corresponding to the 6th layer in the network. Linear SVM is used to classify the data. The information from the 4 different images pertaining to a particular tissue sample; are combined using the following techniques: soft voting, hard voting, multiplication, addition, linear combination, concatenation and multi-channel feature extraction. We observe that we obtain better results in general than when we use a linear combination of the feature representations. We use 5-fold cross validation to perform the experiments. The best results are obtained when the various features are linearly combined together resulting in a mean accuracy of 91.27%.

A Neutral Network based Early Eathquake Warning model in California region

NASA Astrophysics Data System (ADS)

Xiao, H.; MacAyeal, D. R.

2016-12-01

Early Earthquake Warning systems could reduce loss of lives and other economic impact resulted from natural disaster or man-made calamity. Current systems could be further enhanced by neutral network method. A 3 layer neural network model combined with onsite method was deployed in this paper to improve the recognition time and detection time for large scale earthquakes.The 3 layer neutral network early earthquake warning model adopted the vector feature design for sample events happened within 150 km radius of the epicenters. Dataset used in this paper contained both destructive events and small scale events. All the data was extracted from IRIS database to properly train the model. In the training process, backpropagation algorithm was used to adjust the weight matrices and bias matrices during each iteration. The information in all three channels of the seismometers served as the source in this model. Through designed tests, it was indicated that this model could identify approximately 90 percent of the events' scale correctly. And the early detection could provide informative evidence for public authorities to make further decisions. This indicated that neutral network model could have the potential to strengthen current early warning system, since the onsite method may greatly reduce the responding time and save more lives in such disasters.

Networks of Interacting Processes: Relationships Between Drivers and Deltaic Variables to Understand Water and Sediment Transport in Wax Lake Delta, Coastal Louisiana

NASA Astrophysics Data System (ADS)

Sendrowski, A.; Passalacqua, P.; Wagner, W.; Mohrig, D. C.; Meselhe, E. A.; Sadid, K. M.; Castañeda-Moya, E.; Twilley, R.

2017-12-01

Studying distributary channel networks in river deltaic systems provides important insight into deltaic functioning and evolution. This view of networks highlights the physical connection along channels and can also encompass the structural link between channels and deltaic islands (termed structural connectivity). An alternate view of the deltaic network is one composed of interacting processes, such as relationships between external drivers (e.g., river discharge, tides, and wind) and internal deltaic response variables (e.g., water level and sediment concentration). This network, also referred to as process connectivity, is dynamic across space and time, often comprises nonlinear relationships, and contributes to the development of complex channel networks and ecologically rich island platforms. The importance of process connectivity has been acknowledged, however, few studies have directly quantified these network interactions. In this work, we quantify process connections in Wax Lake Delta (WLD), coastal Louisiana. WLD is a naturally prograding delta that serves as an analogue for river diversion projects, thus it provides an excellent setting for understanding the influence of river discharge, tides, and wind on water and sediment in a delta. Time series of water level and sediment concentration were collected in three channels from November 2013 to February 2014, while water level and turbidity were collected on an island from April 2014 to August 2015. Additionally, a model run on WLD bathymetry generated two years of sediment concentration time series in multiple channels. River discharge, tide, and wind measurements were collected from the USGS and NOAA, respectively. We analyze this data with information theory (IT), a set of statistics that measure uncertainty in signals and communication between signals. Using IT, the timescale, strength, and direction of network links are quantified by measuring the synchronization and direct influence from one variable to another. We compare channel and island process connections, which show distinct differences. Our study captures the temporal evolution of variable transport at multiple locations. While WLD is river dominated, tides and wind show unique transport signatures related to tidal spring and neap transitions and wind events.

Maja Valley and the Chryse outflow complex sites

NASA Technical Reports Server (NTRS)

Rice, Jim W.

1994-01-01

This candidate landing site is located at 19 deg N, 53.5 deg W near the mouth of a major outflow channel. Maja Valles, and two 'valley network' channel systems, Maumee and Vedra Valles. The following objectives are to be analyzed in this region: (1) origin and paleohydrology of outflow and valley network channels; (2) fan delta complex composition (the deposit located in this area is one of the few identified at the mouth s of any channels on the planet); and (3) analysis of any paleolake sediments (carbonates, evaporites). The primary objectives of the Chryse Outflow Complex region (Ares, Tiu, Mawrth, Simud, and Shalbatana Valles) would be outflow channel dynamics (paleohydrology) of five different channel systems.

Stream classification of the Apalachicola-Chattahoochee-Flint River System to support modeling of aquatic habitat response to climate change

USGS Publications Warehouse

Elliott, Caroline M.; Jacobson, Robert B.; Freeman, Mary C.

2014-01-01

A stream classification and associated datasets were developed for the Apalachicola-Chattahoochee-Flint River Basin to support biological modeling of species response to climate change in the southeastern United States. The U.S. Geological Survey and the Department of the Interior’s National Climate Change and Wildlife Science Center established the Southeast Regional Assessment Project (SERAP) which used downscaled general circulation models to develop landscape-scale assessments of climate change and subsequent effects on land cover, ecosystems, and priority species in the southeastern United States. The SERAP aquatic and hydrologic dynamics modeling efforts involve multiscale watershed hydrology, stream-temperature, and fish-occupancy models, which all are based on the same stream network. Models were developed for the Apalachicola-Chattahoochee-Flint River Basin and subbasins in Alabama, Florida, and Georgia, and for the Upper Roanoke River Basin in Virginia. The stream network was used as the spatial scheme through which information was shared across the various models within SERAP. Because these models operate at different scales, coordinated pair versions of the network were delineated, characterized, and parameterized for coarse- and fine-scale hydrologic and biologic modeling. The stream network used for the SERAP aquatic models was extracted from a 30-meter (m) scale digital elevation model (DEM) using standard topographic analysis of flow accumulation. At the finer scale, reaches were delineated to represent lengths of stream channel with fairly homogenous physical characteristics (mean reach length = 350 m). Every reach in the network is designated with geomorphic attributes including upstream drainage basin area, channel gradient, channel width, valley width, Strahler and Shreve stream order, stream power, and measures of stream confinement. The reach network was aggregated from tributary junction to tributary junction to define segments for the benefit of hydrological, soil erosion, and coarser ecological modeling. Reach attributes are summarized for each segment. In six subbasins segments are assigned additional attributes about barriers (usually impoundments) to fish migration and stream isolation. Segments in the six sub-basins are also attributed with percent urban area for the watershed upstream from the stream segment for each decade from 2010–2100 from models of urban growth. On a broader scale, for application in a coarse-scale species-response model, the stream-network information is aggregated and summarized by 256 drainage subbasins (Hydrologic Response Units) used for watershed hydrologic and stream-temperature models. A model of soil erodibility based on the Revised Universal Soil Loss Equation also was developed at this scale to parameterize a model to evaluate stream condition. The reach-scale network was classified using multivariate clustering based on modeled channel width, valley width, and mean reach gradient as variables. The resulting classification consists of a 6-cluster and a 12-cluster classification for every reach in the Apalachicola-Chattahoochee-Flint Basin. We present an example of the utility of the classification that was tested using the occurrence of two species of darters and two species of minnows in the Apalachicola-Chattahoochee-Flint River Basin, the blackbanded darter and Halloween darter, and the bluestripe shiner and blacktail shiner.

Review: The state-of-art of sparse channel models and their applicability to performance assessment of radioactive waste repositories in fractured crystalline formations

NASA Astrophysics Data System (ADS)

Figueiredo, Bruno; Tsang, Chin-Fu; Niemi, Auli; Lindgren, Georg

2016-11-01

Laboratory and field experiments done on fractured rock show that flow and solute transport often occur along flow channels. `Sparse channels' refers to the case where these channels are characterised by flow in long flow paths separated from each other by large spacings relative to the size of flow domain. A literature study is presented that brings together information useful to assess whether a sparse-channel network concept is an appropriate representation of the flow system in tight fractured rock of low transmissivity, such as that around a nuclear waste repository in deep crystalline rocks. A number of observations are made in this review. First, conventional fracture network models may lead to inaccurate results for flow and solute transport in tight fractured rocks. Secondly, a flow dimension of 1, as determined by the analysis of pressure data in well testing, may be indicative of channelised flow, but such interpretation is not unique or definitive. Thirdly, in sparse channels, the percolation may be more influenced by the fracture shape than the fracture size and orientation but further studies are needed. Fourthly, the migration of radionuclides from a waste canister in a repository to the biosphere may be strongly influenced by the type of model used (e.g. discrete fracture network, channel model). Fifthly, the determination of appropriateness of representing an in situ flow system by a sparse-channel network model needs parameters usually neglected in site characterisation, such as the density of channels or fracture intersections.

Potassium channels and prostacyclin contribute to vasorelaxant activities of Tridax procumbens crude aqueous leaf extract in rat superior mesenteric arteries.

PubMed

Salahdeen, H M; Adebari, A O; Murtala, B A; Alada, A R A

2015-03-01

Previous studies have shown that aqueous extract of the leaf of Tridax procuinbens is capable of lowering blood pressure through its vasodilatory effects. In the present study attempt was made to examine the biological active components of T procuinbens leaf using GC-MS methods. We further investigated the role of K+ channels in the vasorelaxation effects of Tridax procumbens using rat isolated mesenteric artery. The superior mesenteric artery isolated from healthy, young adult Wistar rats (250-300 g) were precontracted with phenylephrine (PE) (10(-7) M) and potassium chloride (KCl) (60 mM) and were treated with Various concentrations of aqueous extract ofT procumbens (0.9.0 mg/ml). The changes in arterial tension were recorded using a force-displacement transducer (Model 7004; Ugo Basil Varese, Italy) coupled to data capsule acquisition system. The results of GG-MS revealed the presence of linoleic acid. The T. procumbens extract (TPE) ranging from 0.5-9.0 mg/mI significantly (p<0.05) reduced the, contraction induced by (PE) and (KCl) in a concentration-dependent manner. The extract also antagonised the calcium-induced vasoconstriction (1(-9) - 10(-5)) in calcium-free with high concentration of potassium as well as. in calcium- and potassium free physiological solutions. The vasorelaxing effect caused by TPE was significantly (p<0.05) attenuated with preincubation of potassium channels blockers (Barium chloride and apamin), NO synthaseinhibitor (L-NAME), prostacyclin inhibitor (indomethacin), atropine; propranolol, and methylene blue while it was not affected by preincubation with glibenclamide and tetra ethyl ammonium, 4-aminopyridine (4-AP) and oxadiazolo quinoxalin (ODQ). The results of this study demonstrate that T procumbens extract causes vasodilatory effects by blocking calcium channels and the vasodilatory effect of the extract may also be due to stimulation of prostacyclin production and opening of small-conductance Ga2+ activated potassium channels. The observed effect of this extract may be probably due to the presence of linoleic acid in this extract.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

An ultra low power feature extraction and classification system for wearable seizure detection.

PubMed

Page, Adam; Pramod Tim Oates, Siddharth; Mohsenin, Tinoosh

2015-01-01

In this paper we explore the use of a variety of machine learning algorithms for designing a reliable and low-power, multi-channel EEG feature extractor and classifier for predicting seizures from electroencephalographic data (scalp EEG). Different machine learning classifiers including k-nearest neighbor, support vector machines, naïve Bayes, logistic regression, and neural networks are explored with the goal of maximizing detection accuracy while minimizing power, area, and latency. The input to each machine learning classifier is a 198 feature vector containing 9 features for each of the 22 EEG channels obtained over 1-second windows. All classifiers were able to obtain F1 scores over 80% and onset sensitivity of 100% when tested on 10 patients. Among five different classifiers that were explored, logistic regression (LR) proved to have minimum hardware complexity while providing average F-1 score of 91%. Both ASIC and FPGA implementations of logistic regression are presented and show the smallest area, power consumption, and the lowest latency when compared to the previous work.

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

1997-04-01

The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics of convergence rate and call blocking. Genetic algorithms (GAs) are also considered in PCS networks as a means to overcome the known weakness of Hopfield NNAs in determining global minima. The resulting GAs for DCA in PCS networks are compared to improved DCA algorithms based on Hopfield NNs for stationary cellular networks. Algorithm performance is compared on the basis of rate of convergence, blocking probability, analytic complexity, and parametric sensitivity to transient traffic demands and channel interference.

Optimization-based channel constrained data aggregation routing algorithms in multi-radio wireless sensor networks.

PubMed

Yen, Hong-Hsu

2009-01-01

In wireless sensor networks, data aggregation routing could reduce the number of data transmissions so as to achieve energy efficient transmission. However, data aggregation introduces data retransmission that is caused by co-channel interference from neighboring sensor nodes. This kind of co-channel interference could result in extra energy consumption and significant latency from retransmission. This will jeopardize the benefits of data aggregation. One possible solution to circumvent data retransmission caused by co-channel interference is to assign different channels to every sensor node that is within each other's interference range on the data aggregation tree. By associating each radio with a different channel, a sensor node could receive data from all the children nodes on the data aggregation tree simultaneously. This could reduce the latency from the data source nodes back to the sink so as to meet the user's delay QoS. Since the number of radios on each sensor node and the number of non-overlapping channels are all limited resources in wireless sensor networks, a challenging question here is to minimize the total transmission cost under limited number of non-overlapping channels in multi-radio wireless sensor networks. This channel constrained data aggregation routing problem in multi-radio wireless sensor networks is an NP-hard problem. I first model this problem as a mixed integer and linear programming problem where the objective is to minimize the total transmission subject to the data aggregation routing, channel and radio resources constraints. The solution approach is based on the Lagrangean relaxation technique to relax some constraints into the objective function and then to derive a set of independent subproblems. By optimally solving these subproblems, it can not only calculate the lower bound of the original primal problem but also provide useful information to get the primal feasible solutions. By incorporating these Lagrangean multipliers as the link arc weight, the optimization-based heuristics are proposed to get energy-efficient data aggregation tree with better resource (channel and radio) utilization. From the computational experiments, the proposed optimization-based approach is superior to existing heuristics under all tested cases.

Effects of ginger and its pungent constituents on transient receptor potential channels.

PubMed

Kim, Young-Soo; Hong, Chan Sik; Lee, Sang Weon; Nam, Joo Hyun; Kim, Byung Joo

2016-12-01

Ginger extract is used as an analeptic in herbal medicine and has been reported to exert antioxidant effects. Transient receptor potential (TRP) canonical 5 (TRPC5), TRP cation channel, subfamily M, member 7 (TRPM7; melastatin 7), and TRP cation channel, subfamily A, member 1 (TRPA1; ankyrin 1) are non-selective cation channels that are modulated by reactive oxygen/nitrogen species (ROS/RNS) and subsequently control various cellular processes. The aim of this study was to evaluate whether ginger and its pungent constituents modulate these channels and exert antioxidant effects. It was found that TRPC5 and TRPA1 currents were modulated by ginger extract and by its pungent constituents, [6]-gingerol, zingerone and [6]-shogaol. In particular, [6]-shogaol markedly and dose-dependently inhibited TRPC5 currents with an IC50 of value of ~18.3 µM. Furthermore, the strong dose-dependent activation of TRPA1 currents by [6]-shogaol was abolished by A‑967079 (a selective TRPA1 inhibitor). However, ginger extract and its pungent constituents had no effect on TRPM7 currents. These results suggest the antioxidant effects of ginger extract and its pungent constituents are mediated through TRPC5 and TRPA1, and that [6]-shogaol is predominantly responsible for the regulation of TRPC5 and TRPA1 currents by ginger extract.

Channel MAC Protocol for Opportunistic Communication in Ad Hoc Wireless Networks

NASA Astrophysics Data System (ADS)

Ashraf, Manzur; Jayasuriya, Aruna; Perreau, Sylvie

2008-12-01

Despite significant research effort, the performance of distributed medium access control methods has failed to meet theoretical expectations. This paper proposes a protocol named "Channel MAC" performing a fully distributed medium access control based on opportunistic communication principles. In this protocol, nodes access the channel when the channel quality increases beyond a threshold, while neighbouring nodes are deemed to be silent. Once a node starts transmitting, it will keep transmitting until the channel becomes "bad." We derive an analytical throughput limit for Channel MAC in a shared multiple access environment. Furthermore, three performance metrics of Channel MAC—throughput, fairness, and delay—are analysed in single hop and multihop scenarios using NS2 simulations. The simulation results show throughput performance improvement of up to 130% with Channel MAC over IEEE 802.11. We also show that the severe resource starvation problem (unfairness) of IEEE 802.11 in some network scenarios is reduced by the Channel MAC mechanism.

The channels of Mars

NASA Technical Reports Server (NTRS)

Baker, Victor R.

1988-01-01

The geomorphology of Mars is discussed, focusing on the Martian channels. The great flood channels of Mars, the processes of channel erosion, and dendritic channel networks, are examined. The topography of the Channeled Scabland region of the northwestern U.S. is described and compared to the Martian channels. The importance of water in the evolution of the channel systems is considered.

Development of a general method for obtaining the geometry of microfluidic networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Razavi, Mohammad Sayed, E-mail: m.sayedrazavi@gmail.com; Salimpour, M. R.; Shirani, Ebrahim

2014-01-15

In the present study, a general method for geometry of fluidic networks is developed with emphasis on pressure-driven flows in the microfluidic applications. The design method is based on general features of network's geometry such as cross-sectional area and length of channels. Also, the method is applicable to various cross-sectional shapes such as circular, rectangular, triangular, and trapezoidal cross sections. Using constructal theory, the flow resistance, energy loss and performance of the network are optimized. Also, by this method, practical design strategies for the fabrication of microfluidic networks can be improved. The design method enables rapid prediction of fluid flowmore » in the complex network of channels and is very useful for improving proper miniaturization and integration of microfluidic networks. Minimization of flow resistance of the network of channels leads to universal constants for consecutive cross-sectional areas and lengths. For a Y-shaped network, the optimal ratios of consecutive cross-section areas (A{sub i+1}/A{sub i}) and lengths (L{sub i+1}/L{sub i}) are obtained as A{sub i+1}/A{sub i} = 2{sup −2/3} and L{sub i+1}/L{sub i} = 2{sup −1/3}, respectively. It is shown that energy loss in the network is proportional to the volume of network. It is also seen when the number of channels is increased both the hydraulic resistance and the volume occupied by the network are increased in a similar manner. Furthermore, the method offers that fabrication of multi-depth and multi-width microchannels should be considered as an integral part of designing procedures. Finally, numerical simulations for the fluid flow in the network have been performed and results show very good agreement with analytic results.« less

Human body and head characteristics as a communication medium for Body Area Network.

PubMed

Kifle, Yonatan; Hun-Seok Kim; Yoo, Jerald

2015-01-01

An in-depth investigation of the Body Channel Communication (BCC) under the environment set according to the IEEE 802.15.6 Body Area Network (BAN) standard is conducted to observe and characterize the human body as a communication medium. A thorough measurement of the human head as part of the human channel is also carried out. Human forehead, head to limb, and ear to ear channel is characterized. The channel gain of the human head follows the same bandpass profile of the human torso and limbs with the maximum channel gain occurring at 35MHz. The human body channel gain distribution histogram at given frequencies, while all the other parameters are held constant, exhibits a maximum variation of 2.2dB in the channel gain at the center frequency of the bandpass channel gain profile.

A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.

PubMed

Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

2015-01-01

In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.

A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs

PubMed Central

Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan

2015-01-01

In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network. PMID:26571042

Software-defined network abstractions and configuration interfaces for building programmable quantum networks

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Geerhart, Billy E.; Snow, Nikolai A.; Williams, Brian P.; Humble, Travis S.

2017-05-01

Well-defined and stable quantum networks are essential to realize functional quantum communication applications. Quantum networks are complex and must use both quantum and classical channels to support quantum applications like QKD, teleportation, and superdense coding. In particular, the no-cloning theorem prevents the reliable copying of quantum signals such that the quantum and classical channels must be highly coordinated using robust and extensible methods. In this paper, we describe new network abstractions and interfaces for building programmable quantum networks. Our approach leverages new OpenFlow data structures and table type patterns to build programmable quantum networks and to support quantum applications.

A network architecture for International Business Satellite communications

NASA Astrophysics Data System (ADS)

Takahata, Fumio; Nohara, Mitsuo; Takeuchi, Yoshio

Demand Assignment (DA) control is expected to be introduced in the International Business Satellte communications (IBS) network in order to cope with a growing international business traffic. The paper discusses the DA/IBS network from the viewpoints of network configuration, satellite channel configuration and DA control. The network configuration proposed here consists of one Central Station with network management function and several Network Coordination Stations with user management function. A satellite channel configuration is also presented along with a tradeoff study on transmission bit rate, high power amplifier output power requirement, and service quality. The DA control flow and protocol based on CCITT Signalling System No. 7 are also proposed.

Channel scaling and field-effect mobility extraction in amorphous InZnO thin film transistors

NASA Astrophysics Data System (ADS)

Lee, Sunghwan; Song, Yang; Park, Hongsik; Zaslavsky, A.; Paine, D. C.

2017-09-01

Amorphous oxide semiconductors (AOSs) based on indium oxides are of great interest for next generation ultra-high definition displays that require much smaller pixel driving elements. We describe the scaling behavior in amorphous InZnO thin film transistors (TFTs) with a significant decrease in the extracted field-effect mobility μFE with channel length L (from 39.3 to 9.9 cm2/V·s as L is reduced from 50 to 5 μm). Transmission line model measurements reveal that channel scaling leads to a significant μFE underestimation due to contact resistance (RC) at the metallization/channel interface. Therefore, we suggest a method of extracting correct μFE when the TFT performance is significantly affected by RC. The corrected μFE values are higher (45.4 cm2/V·s) and nearly independent of L. The results show the critical effect of contact resistance on μFE measurements and suggest strategies to determine accurate μFE when a TFT channel is scaled.

Efficient quantum transmission in multiple-source networks.

PubMed

Luo, Ming-Xing; Xu, Gang; Chen, Xiu-Bo; Yang, Yi-Xian; Wang, Xiaojun

2014-04-02

A difficult problem in quantum network communications is how to efficiently transmit quantum information over large-scale networks with common channels. We propose a solution by developing a quantum encoding approach. Different quantum states are encoded into a coherent superposition state using quantum linear optics. The transmission congestion in the common channel may be avoided by transmitting the superposition state. For further decoding and continued transmission, special phase transformations are applied to incoming quantum states using phase shifters such that decoders can distinguish outgoing quantum states. These phase shifters may be precisely controlled using classical chaos synchronization via additional classical channels. Based on this design and the reduction of multiple-source network under the assumption of restricted maximum-flow, the optimal scheme is proposed for specially quantized multiple-source network. In comparison with previous schemes, our scheme can greatly increase the transmission efficiency.

Effects of pine needle extract on pacemaker currents in interstitial cells of Cajal from the murine small intestine.

PubMed

Cheong, Hyeonsook; Paudyal, Dilli Parasad; Jun, Jae Yeoul; Yeum, Cheol Ho; Yoon, Pyung Jin; Park, Chan Guk; Kim, Man Yoo; So, Insuk; Kim, Ki Whan; Choi, Seok

2005-10-31

Extracts of pine needles (Pinus densiflora Sieb. et Zucc.) have diverse physiological and pharmacological actions. In this study we show that pine needle extract alters pacemaker currents in interstitial cells of Cajal (ICC) by modulating ATP-sensitive K+ channels and that this effect is mediated by prostaglandins. In whole cell patches at 30 degrees , ICC generated spontaneous pacemaker potentials in the current clamp mode (I = 0), and inward currents (pacemaker currents) in the voltage clamp mode at a holding potential of -70 mV. Pine needle extract hyperpolarized the membrane potential, and in voltage clamp mode decreased both the frequency and amplitude of the pacemaker currents, and increased the resting currents in the outward direction. It also inhibited the pacemaker currents in a dose-dependent manner. Because the effects of pine needle extract on pacemaker currents were the same as those of pinacidil (an ATP-sensitive K+ channel opener) we tested the effect of glibenclamide (an ATP-sensitive K+ channels blocker) on ICC exposed to pine needle extract. The effects of pine needle extract on pacemaker currents were blocked by glibenclamide. To see whether production of prostaglandins (PGs) is involved in the inhibitory effect of pine needle extract on pacemaker currents, we tested the effects of naproxen, a non-selective cyclooxygenase (COX-1 and COX-2) inhibitor, and AH6809, a prostaglandin EP1 and EP2 receptor antagonist. Naproxen and AH6809 blocked the inhibitory effects of pine needle extract on ICC. These results indicate that pine needle extract inhibits the pacemaker currents of ICC by activating ATP-sensitive K+ channels via the production of PGs.

Congruent Bifurcation Angles in River Delta and Tributary Channel Networks

NASA Astrophysics Data System (ADS)

Coffey, Thomas S.; Shaw, John B.

2017-11-01

We show that distributary channels on river deltas exhibit a mean bifurcation angle that can be understood using theory developed in tributary channel networks. In certain cases, tributary network bifurcation geometries have been demonstrated to be controlled by diffusive groundwater flow feeding incipient bifurcations, producing a characteristic angle of 72∘. We measured 25 unique distributary bifurcations in an experimental delta and 197 bifurcations in 10 natural deltas, yielding a mean angle of 70.4∘±2.6∘ (95% confidence interval) for field-scale deltas and a mean angle of 68.3∘±8.7∘ for the experimental delta, consistent with this theoretical prediction. The bifurcation angle holds for small scales relative to channel width length scales. Furthermore, the experimental data show that the mean angle is 72∘ immediately after bifurcation initiation and remains relatively constant over significant time scales. Although distributary networks do not mirror tributary networks perfectly, the similar control and expression of bifurcation angles suggests that additional morphodynamic insight may be gained from further comparative study.

Perspectives and limitations of QKD integration in metropolitan area networks.

PubMed

Aleksic, Slavisa; Hipp, Florian; Winkler, Dominic; Poppe, Andreas; Schrenk, Bernhard; Franzl, Gerald

2015-04-20

Quantum key distribution (QKD) systems have already reached a reasonable level of maturity. However, a smooth integration and a wide adoption of commercial QKD systems in metropolitan area networks has still remained challenging because of technical and economical obstacles. Mainly the need for dedicated fibers and the strong dependence of the secret key rate on both loss budget and background noise in the quantum channel hinder a practical, flexible and robust implementation of QKD in current and next-generation optical metro networks. In this paper, we discuss these obstacles and present approaches to share existing fiber infrastructures among quantum and classical channels. Particularly, a proposal for a smooth integration of QKD in optical metro networks, which implies removing spurious background photons caused by optical transmitters, amplifiers and nonlinear effects in fibers, is presented and discussed. We determine and characterize impairments on quantum channels caused by many classical telecom channels at practically used power levels coexisting within the same fiber. Extensive experimental results are presented and indicate that a practical integration of QKD in conventional optical metro networks is possible.

Extracting cross sections and water levels of vegetated ditches from LiDAR point clouds

NASA Astrophysics Data System (ADS)

Roelens, Jennifer; Dondeyne, Stefaan; Van Orshoven, Jos; Diels, Jan

2016-12-01

The hydrologic response of a catchment is sensitive to the morphology of the drainage network. Dimensions of bigger channels are usually well known, however, geometrical data for man-made ditches is often missing as there are many and small. Aerial LiDAR data offers the possibility to extract these small geometrical features. Analysing the three-dimensional point clouds directly will maintain the highest degree of information. A longitudinal and cross-sectional buffer were used to extract the cross-sectional profile points from the LiDAR point cloud. The profile was represented by spline functions fitted through the minimum envelop of the extracted points. The cross-sectional ditch profiles were classified for the presence of water and vegetation based on the normalized difference water index and the spatial characteristics of the points along the profile. The normalized difference water index was created using the RGB and intensity data coupled to the LiDAR points. The mean vertical deviation of 0.14 m found between the extracted and reference cross sections could mainly be attributed to the occurrence of water and partly to vegetation on the banks. In contrast to the cross-sectional area, the extracted width was not influenced by the environment (coefficient of determination R2 = 0.87). Water and vegetation influenced the extracted ditch characteristics, but the proposed method is still robust and therefore facilitates input data acquisition and improves accuracy of spatially explicit hydrological models.

Universal model of bias-stress-induced instability in inkjet-printed carbon nanotube networks field-effect transistors

NASA Astrophysics Data System (ADS)

Jung, Haesun; Choi, Sungju; Jang, Jun Tae; Yoon, Jinsu; Lee, Juhee; Lee, Yongwoo; Rhee, Jihyun; Ahn, Geumho; Yu, Hye Ri; Kim, Dong Myong; Choi, Sung-Jin; Kim, Dae Hwan

2018-02-01

We propose a universal model for bias-stress (BS)-induced instability in the inkjet-printed carbon nanotube (CNT) networks used in field-effect transistors (FETs). By combining two experimental methods, i.e., a comparison between air and vacuum BS tests and interface trap extraction, BS instability is explained regardless of either the BS polarity or ambient condition, using a single platform constituted by four key factors: OH- adsorption/desorption followed by a change in carrier concentration, electron concentration in CNT channel corroborated with H2O/O2 molecules in ambient, charge trapping/detrapping, and interface trap generation. Under negative BS (NBS), the negative threshold voltage shift (ΔVT) is dominated by OH- desorption, which is followed by hole trapping in the interface and/or gate insulator. Under positive BS (PBS), the positive ΔVT is dominated by OH- adsorption, which is followed by electron trapping in the interface and/or gate insulator. This instability is compensated by interface trap extraction; PBS instability is slightly more complicated than NBS instability. Furthermore, our model is verified using device simulation, which gives insights on how much each mechanism contributes to BS instability. Our result is potentially useful for the design of highly stable CNT-based flexible circuits in the Internet of Things wearable healthcare era.

New multi-scale approach to improve explanation of patterns of contemporary morphodynamics in the badland landscapes of Central Italy: the important Quaternary context

NASA Astrophysics Data System (ADS)

Vergari, Francesca; Troiani, Francesco; Della Seta, Marta; Faulkner, Hazel; Schwanghart, Wolfgang; Ciccacci, Sirio; Del Monte, Maurizio; Fredi, Paola

2016-04-01

Spatial patterns and magnitudes of short-term erosional processes are often the result of longer-term landscape-wide morphodynamics. Their combined analysis, however, is challenged by different spatial scales, data availability and resolution. Integrating both analyses has thus rarely been done though urgently needed to better understand and manage present day erosional dynamics and land degradation. In this study we aim at overcoming these shortcomings by exploring a multi-scale approach, based on a nested experimental design that integrates the traditional monitoring of erosion processes at local and short time scale, with the longer-term (over the last 103-105 yr) and basin-to-morphostructure scale analysis of landscape morphodynamics. We investigated the geomorphological behaviour of a Mediterranean active badland site located in the Upper Orcia Valley (Southern Tuscany, Italy). This choice is justified by the availability of decadal erosion monitoring datasets at a range of scales, and the rapidity of development of erosion processes. Based on the analysis of drainage network and its longitudinal and planform pattern, we tested the hypothesis that this rejuvenating, actively erosional landscape presents hotspots of denudation processes on hillslope and in channel network that are largely associated with (a) knickpoints on stream longitudinal profiles, (b) sites of strong connectivity, and (c) sites of strong divide competition with adjacent, aggressive and non-aggressive systems. To illustrate and explore this nested approach, we extracted the channel network and analysed stream longitudinal profiles using the MATLAB-based TopoToolbox program, starting from the 27x27 m Aster GDEM. The stream network morphometric analyses involved computing and mapping χ-values, a transformation that normalizes the longitudinal distance by upslope area and which serves as a proxy of the dynamic state of river basins based on the current geometry of the river network. Finally, we projected on the longitudinal profiles of the Orcia River and some of its main tributaries a full range of geomorphic features which are relevant for the interpretation of the landscape morphoevolution, connectivity and erosion/deposition dynamics: i) competitive divides; ii) sites with different degree of connectivity within the drainage system; iii) sites experiencing different erosion rates; iv) sites with in-channel depositional features and landslide deposits; v) remnants of relict geomorphic surfaces. The plano-altimetric distribution of such features, compared with the drainage network evolutionary stage, allowed to better understand the morphodynamics of badland areas and to define future scenarios in the perspective of a better management of hazardous processes.

Geomorphic Thresholds of Submarine Canyons Along the U.S. Atlantic Continental Margin

NASA Astrophysics Data System (ADS)

Brothers, D. S.; ten Brink, U. S.; Andrews, B. D.; Chaytor, J. D.

2011-12-01

Vast networks of submarine canyons and associated channels are incised into the U.S. Atlantic continental slope and rise. Submarine canyons form by differential erosion and deposition, primarily from sedimentary turbidity flows. Theoretical and laboratory studies have investigated the initiation of turbidity flows and their capacity to erode and entrain sedimentary material at distances far from the shelf edge. The results have helped understand the nature of turbidite deposits on the continental slope and rise. Nevertheless, few studies have examined the linkages between down-canyon sediment transport and the morphology of canyon/channel networks using mesoscale analyses of swath bathymetry data. We present quantitative analysis of 100-m resolution multibeam bathymetry data spanning ~616,000 km2 of the slope and rise between Georges Banks and the Blake Plateau (New England to North Carolina). Canyons are categorized as shelf-indenting or slope-confined based on spatial scale, vertical relief and connection with terrestrial river systems during sea level low stands. Shelf-indenting canyons usually represent the trunk-canyon of submerged channel networks. On the rise, shelf-indenting canyons have relatively well-developed channel-levees and sharp inner-thalwag incision suggesting much higher frequency and volume of turbidity flows. Because of the similarities between submarine canyon networks and terrestrial river systems, we apply methods originally developed to study fluvial morphology. Along-canyon profiles are extracted from the bathymetry data and the power-law relationship between thalwag gradient and drainage area is examined for more than 180 canyons along an ~1200 km stretch of the US Atlantic margin. We observe distinct thresholds in the power-law relationship between drainage area and gradient. Almost all canyons with heads on the upper slope contain at least two linear segments when plotted in log-log form. The first segment along the upper slope is flat (constant gradient, low area). The second segment dips (exponentially decreasing gradient with increasing area). We interpret the transition between the two segments to be either diffusive creep/landslide processes that evolve into turbidity flows or the boundary that separates up-canyon infilling from relic, lower-canyon incision. Furthermore, the threshold occurs at a nearly constant drainage area regardless of location and morphology of the drainage network. This suggests that time-averaged erosion rate in submarine canyons depends on frequency of turbidity flows, which in turn depends on the volume of unstable sediments deposited near canyon heads and along canyon walls. We find that the gradient-area relationship does not follow a power-law in shelf-indenting canyons, most likely due to allogenic processes of the continental shelf and linkage to terrestrial river discharge.

TOWARDS AN AUTOMATED TOOL FOR CHANNEL-NETWORK CHARACTERIZATIONS, MODELING, AND ASSESSMENT

EPA Science Inventory

Detailed characterization of channel networks for hydrologic and geomorphic models has traditionally been a difficult and expensive proposition, and lack of information has thus been a common limitation of modeling efforts. With the advent of datasets derived from high-resolutio...

SIMULATING SUB-DECADAL CHANNEL MORPHOLOGIC CHANGE IN EPHEMERAL STREAM NETWORKS

EPA Science Inventory

A distributed watershed model was modified to simulate cumulative channel morphologic
change from multiple runoff events in ephemeral stream networks. The model incorporates the general design of the event-based Kinematic Runoff and" Erosion Model (KINEROS), which describes t...

Pore network extraction from pore space images of various porous media systems

NASA Astrophysics Data System (ADS)

Yi, Zhixing; Lin, Mian; Jiang, Wenbin; Zhang, Zhaobin; Li, Haishan; Gao, Jian

2017-04-01

Pore network extraction, which is defined as the transformation from irregular pore space to a simplified network in the form of pores connected by throats, is significant to microstructure analysis and network modeling. A physically realistic pore network is not only a representation of the pore space in the sense of topology and morphology, but also a good tool for predicting transport properties accurately. We present a method to extract pore network by employing the centrally located medial axis to guide the construction of maximal-balls-like skeleton where the pores and throats are defined and parameterized. To validate our method, various rock samples including sand pack, sandstones, and carbonates were used to extract pore networks. The pore structures were compared quantitatively with the structures extracted by medial axis method or maximal ball method. The predicted absolute permeability and formation factor were verified against the theoretical solutions obtained by lattice Boltzmann method and finite volume method, respectively. The two-phase flow was simulated through the networks extracted from homogeneous sandstones, and the generated relative permeability curves were compared with the data obtained from experimental method and other numerical models. The results show that the accuracy of our network is higher than that of other networks for predicting transport properties, so the presented method is more reliable for extracting physically realistic pore network.

Extracting Message Inter-Departure Time Distributions from the Human Electroencephalogram

PubMed Central

Mišić, Bratislav; Vakorin, Vasily A.; Kovačević, Nataša; Paus, Tomáš; McIntosh, Anthony R.

2011-01-01

The complex connectivity of the cerebral cortex is a topic of much study, yet the link between structure and function is still unclear. The processing capacity and throughput of information at individual brain regions remains an open question and one that could potentially bridge these two aspects of neural organization. The rate at which information is emitted from different nodes in the network and how this output process changes under different external conditions are general questions that are not unique to neuroscience, but are of interest in multiple classes of telecommunication networks. In the present study we show how some of these questions may be addressed using tools from telecommunications research. An important system statistic for modeling and performance evaluation of distributed communication systems is the time between successive departures of units of information at each node in the network. We describe a method to extract and fully characterize the distribution of such inter-departure times from the resting-state electroencephalogram (EEG). We show that inter-departure times are well fitted by the two-parameter Gamma distribution. Moreover, they are not spatially or neurophysiologically trivial and instead are regionally specific and sensitive to the presence of sensory input. In both the eyes-closed and eyes-open conditions, inter-departure time distributions were more dispersed over posterior parietal channels, close to regions which are known to have the most dense structural connectivity. The biggest differences between the two conditions were observed at occipital sites, where inter-departure times were significantly more variable in the eyes-open condition. Together, these results suggest that message departure times are indicative of network traffic and capture a novel facet of neural activity. PMID:21673866

Predicting membrane protein types by fusing composite protein sequence features into pseudo amino acid composition.

PubMed

Hayat, Maqsood; Khan, Asifullah

2011-02-21

Membrane proteins are vital type of proteins that serve as channels, receptors, and energy transducers in a cell. Prediction of membrane protein types is an important research area in bioinformatics. Knowledge of membrane protein types provides some valuable information for predicting novel example of the membrane protein types. However, classification of membrane protein types can be both time consuming and susceptible to errors due to the inherent similarity of membrane protein types. In this paper, neural networks based membrane protein type prediction system is proposed. Composite protein sequence representation (CPSR) is used to extract the features of a protein sequence, which includes seven feature sets; amino acid composition, sequence length, 2 gram exchange group frequency, hydrophobic group, electronic group, sum of hydrophobicity, and R-group. Principal component analysis is then employed to reduce the dimensionality of the feature vector. The probabilistic neural network (PNN), generalized regression neural network, and support vector machine (SVM) are used as classifiers. A high success rate of 86.01% is obtained using SVM for the jackknife test. In case of independent dataset test, PNN yields the highest accuracy of 95.73%. These classifiers exhibit improved performance using other performance measures such as sensitivity, specificity, Mathew's correlation coefficient, and F-measure. The experimental results show that the prediction performance of the proposed scheme for classifying membrane protein types is the best reported, so far. This performance improvement may largely be credited to the learning capabilities of neural networks and the composite feature extraction strategy, which exploits seven different properties of protein sequences. The proposed Mem-Predictor can be accessed at http://111.68.99.218/Mem-Predictor. Copyright © 2010 Elsevier Ltd. All rights reserved.

Theoretical Foundations of Wireless Networks

DTIC Science & Technology

2015-07-22

Optimal transmission over a fading channel with imperfect channel state information,” in Global Telecommun. Conf., pp. 1–5, Houston TX , December 5-9...SECURITY CLASSIFICATION OF: The goal of this project is to develop a formal theory of wireless networks providing a scientific basis to understand...randomness and optimality. Randomness, in the form of fading, is a defining characteristic of wireless networks. Optimality is a suitable design

On the Probability of Error and Stochastic Resonance in Discrete Memoryless Channels

DTIC Science & Technology

2013-12-01

Information - Driven Doppler Shift Estimation and Compensation Methods for Underwater Wireless Sensor Networks ”, which is to analyze and develop... underwater wireless sensor networks . We formulated an analytic relationship that relates the average probability of error to the systems parameters, the...thesis, we studied the performance of Discrete Memoryless Channels (DMC), arising in the context of cooperative underwater wireless sensor networks

Anthropogenic changes to the tidal channel network, sediment rerouting, and social implications in southwest Bangladesh

NASA Astrophysics Data System (ADS)

Wilson, C.; Goodbred, S. L., Jr.; Sams, S.; Small, C.

2015-12-01

The tidal channel network in southwest Bangladesh has been undergoing major adjustment in response to anthropogenic modification over the past few decades. Densely inhabited, agricultural islands that have been embanked to protect against inundation by tides, river flooding, and storm surges (i.e., polders) preclude tidal exchange and sedimentation. Studies reveal this results in elevation deficits relative to mean high water, endangering local communities when embankment failures occur (e.g., during storms, lateral channel erosion). In addition, many studies suggest that the decrease in tidal prism and associated change in hydrodynamics from poldering causes shoaling in remaining tidal channels, which can cause a disruption in transportation. The widespread closure and conversion of tidal channel areas to profitable shrimp aquaculture is also prevalent in this region. In this study, we quantify the direct closure of tidal channels due to poldering and shrimp aquaculture using historical Landsat and Google Earth imagery, and analyze the morphologic adjustment of the tidal channel network due to these perturbations. In the natural Sundarbans mangrove forest, the tidal channel network has remained relatively constant since the 1970s. In contrast, construction of polders removed >1000 km of primary tidal creeks and >90 km2 has been reclaimed outside of polders through infilling and closure of formerly-active, higher order conduit channels now used for shrimp aquaculture. Field validation confirm tidal restriction by large sluice gates is prevalent, favoring local channel siltation at rates up to 20cm/yr. With the impoundment of primary creeks and closure of 30-60% of conduit channels in the study area, an estimated 1,400 x 106 m3 of water has been removed from the tidal prism and potentially redirected within remaining channels. This has significant implications for tidal amplification in this region. Further, we estimate that 12.3 x 106 MT of sediment annually infills remaining channels, which amounts to ~12% of the total annual sediment load supplied to the tidal deltaplain. This suggests that significant sediment is available in the system for elevation remediation of polders, however the hydrodynamic feasibility of reopening clogged channels and effective sediment dispersal is questionable

Nonadditivity of quantum and classical capacities for entanglement breaking multiple-access channels and the butterfly network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grudka, Andrzej; National Quantum Information Centre of Gdansk, PL-81-824 Sopot; Horodecki, Pawel

2010-06-15

We analyze quantum network primitives which are entanglement breaking. We show superadditivity of quantum and classical capacity regions for quantum multiple-access channels and the quantum butterfly network. Since the effects are especially visible at high noise they suggest that quantum information effects may be particularly helpful in the case of the networks with occasional high noise rates. The present effects provide a qualitative borderline between superadditivities of bipartite and multipartite systems.

Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

PubMed

Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

2017-04-01

We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its capability to capture the nonlinearities of the model better. Copyright © 2017 Elsevier B.V. All rights reserved.

Knowledge extraction from evolving spiking neural networks with rank order population coding.

PubMed

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.

Morphometric analysis of the Marmara Sea river basins, Turkey

NASA Astrophysics Data System (ADS)

Elbaşı, Emre; Ozdemir, Hasan

2014-05-01

The drainage basin, the fundamental unit of the fluvial landscape, has been focus of research aimed at understanding the geometric characteristics of the master channel and its tributary network. This geometry is referred to as the basin morphometry and is nicely reviewed by Abrahams (1984). A great amount of research has focused on geometric characteristic of drainage basins, including the topology of the stream networks, and quantitative description of drainage texture, pattern, shape, and relief characteristics. Evaluation of morphometric parameters necessitates the analysis of various drainage parameters such as ordering of the various streams, measurement of basin area and perimeter, length of drainage channels, drainage density (Dd), stream frequency (Fs), bifurcation ratio (Rb), texture ratio (T), basin relief (Bh), Ruggedness number (Rn), time of concentration (Tc), hypsometric curve and integral (Hc and Hi) (Horton, 1932, Schumn, 1956, Strahler, 1957; Verstappen 1983; Keller and Pinter, 2002; Ozdemir and Bird, 2009). These morphometric parameters have generally been used to predict flood peaks, to assess sediment yield, and to estimate erosion rates in the basins. River basins of the Marmara Sea, has an area of approximately 40,000 sqkm, are the most important basins in Turkey based on their dense populations, industry and transportation systems. The primary aim of this study is to determine and analyse of morphometric characteristics of the Marmara Sea river basins using 10 m resolution Digital Elevation Model (DEM) and to evaluate of the results. For these purposes, digital 10 m contour maps scaled 1:25000 and geological maps scaled 1:100000 were used as the main data sources in the study. 10 m resolution DEM data were created using the contour maps and then drainage networks and their watersheds were extracted using D8 pour point model. Finally, linear, areal and relief morphometries were applied to the river basins using Geographic Information Systems (GIS). This study shows that morphometric analysis of the basins in regional level are very important to understand general morphological characteristics of the basins. In this case, tectonic and lithological conditions of the basins have greatly affected the morphometric characteristics of the north and south basins of the Marmara Sea. References Abrahams, AD. 1984. Channel Networks: A Geomorphological Perspective. Water Resources Research, Volume 20, Issue 2, pages 161-188. Horton, R.E. 1932. Drainage basin characteristics. Trans Am Geophys Union 13:350-361. Keller, E.A., Pinter, N. 2002. Active Tectonics Earthquakes, Uplift, and Landscape, Second Edition, Prentice Hall, New Jersey. Ozdemir H., Bird D. 2009. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods, Environmental Geology, vol.56, pp.1405-1415. Schumm, S.A. 1956. Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geol Soc Am Bull 67:597-646. Strahler, A.N. 1957. Quantitative geomorphology of drainage and channel networks. In: Chow YT (ed) Handbook of appliecl hydrology. Me Graw Hill Book Company, New York. Verstappen, H.Th. 1983. Applied geomorphology. ITC, Enschede.

An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

NASA Astrophysics Data System (ADS)

Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

2018-05-01

The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

Increasing Scalability of Researcher Network Extraction from the Web

NASA Astrophysics Data System (ADS)

Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

Social networks, which describe relations among people or organizations as a network, have recently attracted attention. With the help of a social network, we can analyze the structure of a community and thereby promote efficient communications within it. We investigate the problem of extracting a network of researchers from the Web, to assist efficient cooperation among researchers. Our method uses a search engine to get the cooccurences of names of two researchers and calculates the streangth of the relation between them. Then we label the relation by analyzing the Web pages in which these two names cooccur. Research on social network extraction using search engines as ours, is attracting attention in Japan as well as abroad. However, the former approaches issue too many queries to search engines to extract a large-scale network. In this paper, we propose a method to filter superfluous queries and facilitates the extraction of large-scale networks. By this method we are able to extract a network of around 3000-nodes. Our experimental results show that the proposed method reduces the number of queries significantly while preserving the quality of the network as compared to former methods.

Microfluidic Extraction of Biomarkers using Water as Solvent

NASA Technical Reports Server (NTRS)

Amashukeli, Xenia; Manohara, Harish; Chattopadhyay, Goutam; Mehdi, Imran

2009-01-01

A proposed device, denoted a miniature microfluidic biomarker extractor (mu-EX), would extract trace amounts of chemicals of interest from samples, such as soils and rocks. Traditionally, such extractions are performed on a large scale with hazardous organic solvents; each solvent capable of dissolving only those molecules lying within narrow ranges of specific chemical and physical characteristics that notably include volatility, electric charge, and polarity. In contrast, in the mu-EX, extractions could be performed by use of small amounts (typically between 0.1 and 100 L) of water as a universal solvent. As a rule of thumb, in order to enable solvation and extraction of molecules, it is necessary to use solvents that have polarity sufficiently close to the polarity of the target molecules. The mu-EX would make selection of specific organic solvents unnecessary, because mu-EX would exploit a unique property of liquid water: the possibility of tuning its polarity to match the polarity of organic solvents appropriate for extraction of molecules of interest. The change of the permittivity of water would be achieved by exploiting interactions between the translational states of water molecules and an imposed electromagnetic field in the frequency range of 300 to 600 GHz. On a molecular level, these interactions would result in disruption of the three-dimensional hydrogen-bonding network among liquid-water molecules and subsequent solvation and hydrolysis of target molecules. The mu-EX is expected to be an efficient means of hydrolyzing chemical bonds in complex macromolecules as well and, thus, enabling analysis of the building blocks of these complex chemical systems. The mu-EX device would include a microfluidic channel, part of which would lie within a waveguide coupled to an electronically tuned source of broad-band electromagnetic radiation in the frequency range from 300 to 600 GHz (see figure). The part of the microfluidic channel lying in the waveguide would constitute an interaction volume. The dimensions of the interaction volume would be chosen in accordance with the anticipated amount of solid sample material needed to ensure extraction of sufficient amount of target molecules for detection and analysis. By means that were not specified at the time of reporting the information for this article, the solid sample material would be placed in the interaction volume. Then the electromagnetic field would be imposed within the waveguide and water would be pumped through the interaction volume to effect the extraction.

A Pre-Emptive Horizontal Channel Borrowing and Vertical Traffic Overflowing Channel Allocation Scheme for Overlay Networks

NASA Astrophysics Data System (ADS)

Zhao, Fang-Ming; Jiang, Ling-Ge; He, Chen

In this paper, a channel allocation scheme is studied for overlay wireless networks to optimize connection-level QoS. The contributions of our work are threefold. First, a channel allocation strategy using both horizontal channel borrowing and vertical traffic overflowing (HCBVTO) is presented and analyzed. When all the channels in a given macrocell are used, high-mobility real-time handoff requests can borrow channels from adjacent homogeneous cells. In case that the borrowing requests fail, handoff requests may also be overflowed to heterogeneous cells, if possible. Second, high-mobility real-time service is prioritized by allowing it to preempt channels currently used by other services. And third, to meet the high QoS requirements of some services and increase the utilization of radio resources, certain services can be transformed between real-time services and non-real-time services as necessary. Simulation results demonstrate that the proposed schemes can improve system performance.

Improved Scheduling Mechanisms for Synchronous Information and Energy Transmission.

PubMed

Qin, Danyang; Yang, Songxiang; Zhang, Yan; Ma, Jingya; Ding, Qun

2017-06-09

Wireless energy collecting technology can effectively reduce the network time overhead and prolong the wireless sensor network (WSN) lifetime. However, the traditional energy collecting technology cannot achieve the balance between ergodic channel capacity and average collected energy. In order to solve the problem of the network transmission efficiency and the limited energy of wireless devices, three improved scheduling mechanisms are proposed: improved signal noise ratio (SNR) scheduling mechanism (IS2M), improved N-SNR scheduling mechanism (INS2M) and an improved Equal Throughput scheduling mechanism (IETSM) for different channel conditions to improve the whole network performance. Meanwhile, the average collected energy of single users and the ergodic channel capacity of three scheduling mechanisms can be obtained through the order statistical theory in Rayleig, Ricean, Nakagami- m and Weibull fading channels. It is concluded that the proposed scheduling mechanisms can achieve better balance between energy collection and data transmission, so as to provide a new solution to realize synchronous information and energy transmission for WSNs.

Improved Scheduling Mechanisms for Synchronous Information and Energy Transmission

PubMed Central

Qin, Danyang; Yang, Songxiang; Zhang, Yan; Ma, Jingya; Ding, Qun

2017-01-01

Wireless energy collecting technology can effectively reduce the network time overhead and prolong the wireless sensor network (WSN) lifetime. However, the traditional energy collecting technology cannot achieve the balance between ergodic channel capacity and average collected energy. In order to solve the problem of the network transmission efficiency and the limited energy of wireless devices, three improved scheduling mechanisms are proposed: improved signal noise ratio (SNR) scheduling mechanism (IS2M), improved N-SNR scheduling mechanism (INS2M) and an improved Equal Throughput scheduling mechanism (IETSM) for different channel conditions to improve the whole network performance. Meanwhile, the average collected energy of single users and the ergodic channel capacity of three scheduling mechanisms can be obtained through the order statistical theory in Rayleig, Ricean, Nakagami-m and Weibull fading channels. It is concluded that the proposed scheduling mechanisms can achieve better balance between energy collection and data transmission, so as to provide a new solution to realize synchronous information and energy transmission for WSNs. PMID:28598395

The Electrophysiological MEMS Device with Micro Channel Array for Cellular Network Analysis

NASA Astrophysics Data System (ADS)

Tonomura, Wataru; Kurashima, Toshiaki; Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

This paper describes a new type of MCA (Micro Channel Array) for simultaneous multipoint measurement of cellular network. Presented MCA employing the measurement principles of the patch-clamp technique is designed for advanced neural network analysis which has been studied by co-authors using 64ch MEA (Micro Electrode Arrays) system. First of all, sucking and clamping of cells through channels of developed MCA is expected to improve electrophysiological signal detections. Electrophysiological sensing electrodes integrated around individual channels of MCA by using MEMS (Micro Electro Mechanical System) technologies are electrically isolated for simultaneous multipoint measurement. In this study, we tested the developed MCA using the non-cultured rat's cerebral cortical slice and the hippocampal neurons. We could measure the spontaneous action potential of the slice simultaneously at multiple points and culture the neurons on developed MCA. Herein, we describe the experimental results together with the design and fabrication of the electrophysiological MEMS device with MCA for cellular network analysis.

Quantum information to the home

NASA Astrophysics Data System (ADS)

Choi, Iris; Young, Robert J.; Townsend, Paul D.

2011-06-01

Information encoded on individual quanta will play an important role in our future lives, much as classically encoded digital information does today. Combining quantum information carried by single photons with classical signals encoded on strong laser pulses in modern fibre-to-the-home (FTTH) networks is a significant challenge, the solution to which will facilitate the global distribution of quantum information to the home and with it a quantum internet [1]. In real-world networks, spontaneous Raman scattering in the optical fibre would induce crosstalk between the high-power classical channels and a single-photon quantum channel, such that the latter is unable to operate. Here, we show that the integration of quantum and classical information on an FTTH network is possible by performing quantum key distribution (QKD) on a network while simultaneously transferring realistic levels of classical data. Our novel scheme involves synchronously interleaving a channel of quantum data with the Raman scattered photons from a classical channel, exploiting the periodic minima in the instantaneous crosstalk and thereby enabling secure QKD to be performed.

Using recurrent neural networks for adaptive communication channel equalization.

PubMed

Kechriotis, G; Zervas, E; Manolakos, E S

1994-01-01

Nonlinear adaptive filters based on a variety of neural network models have been used successfully for system identification and noise-cancellation in a wide class of applications. An important problem in data communications is that of channel equalization, i.e., the removal of interferences introduced by linear or nonlinear message corrupting mechanisms, so that the originally transmitted symbols can be recovered correctly at the receiver. In this paper we introduce an adaptive recurrent neural network (RNN) based equalizer whose small size and high performance makes it suitable for high-speed channel equalization. We propose RNN based structures for both trained adaptation and blind equalization, and we evaluate their performance via extensive simulations for a variety of signal modulations and communication channel models. It is shown that the RNN equalizers have comparable performance with traditional linear filter based equalizers when the channel interferences are relatively mild, and that they outperform them by several orders of magnitude when either the channel's transfer function has spectral nulls or severe nonlinear distortion is present. In addition, the small-size RNN equalizers, being essentially generalized IIR filters, are shown to outperform multilayer perceptron equalizers of larger computational complexity in linear and nonlinear channel equalization cases.

Efficient Quantum Transmission in Multiple-Source Networks

PubMed Central

Luo, Ming-Xing; Xu, Gang; Chen, Xiu-Bo; Yang, Yi-Xian; Wang, Xiaojun

2014-01-01

A difficult problem in quantum network communications is how to efficiently transmit quantum information over large-scale networks with common channels. We propose a solution by developing a quantum encoding approach. Different quantum states are encoded into a coherent superposition state using quantum linear optics. The transmission congestion in the common channel may be avoided by transmitting the superposition state. For further decoding and continued transmission, special phase transformations are applied to incoming quantum states using phase shifters such that decoders can distinguish outgoing quantum states. These phase shifters may be precisely controlled using classical chaos synchronization via additional classical channels. Based on this design and the reduction of multiple-source network under the assumption of restricted maximum-flow, the optimal scheme is proposed for specially quantized multiple-source network. In comparison with previous schemes, our scheme can greatly increase the transmission efficiency. PMID:24691590

Convolutional Neural Networks for 1-D Many-Channel Data

DTIC Science & Technology

Deep convolutional neural networks (CNNs) represent the state of the art in image recognition. The same properties that led to their success in that... crack detection ( 8,000 data points, 72 channels). Though the models predictive ability is limited to fitting the trend , its partial success suggests that...originally written to classify digits in the MNIST database (28 28 pixels, 1 channel), for use on 1-D acoustic data taken from experiments focused on

Modeled post-glacial landscape evolution at the southern margin of the Laurentide Ice Sheet: hydrological connection of uplands controls the pace and style of fluvial network expansion

NASA Astrophysics Data System (ADS)

Lai, J.; Anders, A. M.

2017-12-01

Landscapes of the US Midwest were repeatedly affected by the southern margin of the Laurentide Ice Sheet during the Quaternary. Glacial processes removed pre-glacial relief and left constructional landforms including low-relief till plains and high-relief moraines. As the ice retreated, meltwater was collected in subglacial or proglacial lakes and outburst floods of glacial lakes episodically carved deep valleys. These valleys provided the majority of post-glacial landscape relief. However, a significant fraction of the area of low-relief till plains was occupied by closed depressions and remained unconnected to these meltwater valleys. This area is referred to as non-contributing area (NCA) because it does not typically contribute surface runoff to stream networks. Decreasing fractions of NCA on older glacial landscape surfaces suggests that NCA becomes integrated into external drainage networks over time. We propose that this integration could occur via two different paths: 1) through capture of NCA as channel heads propagate into the upland or, 2) through erosion of a channel along a flow path that, perhaps intermittently, connects NCA to the external drainage network. We refer the two cases as "disconnected" and "connected" cases since the crucial difference between them is the hydrological connectivity on the upland. We investigate the differences in the evolution of channel networks and morphology in low relief landscapes under disconnected and connected drainage regimes through numerical simulations of fluvial and hillslope processes. We observe a substantially faster evolution of the channel network in the connected case than in the disconnected case. Modeled landscapes show that channel network in the connected case has longer, more sinuous channels. We also find that the connected case removes lower amounts of total mass than the disconnected case when the same degree of channel integration is achieved. Observed landscapes in US Midwest are more comparable to the connected case than the disconnected case. This finding suggest that the hydrological connectivity in these landscapes may not be entirely controlled by topographic drainage divides.

Construction of Large-Volume Tissue Mimics with 3D Functional Vascular Networks

PubMed Central

Kang, Tae-Yun; Hong, Jung Min; Jung, Jin Woo; Kang, Hyun-Wook; Cho, Dong-Woo

2016-01-01

We used indirect stereolithography (SL) to form inner-layered fluidic networks in a porous scaffold by introducing a hydrogel barrier on the luminal surface, then seeded the networks separately with human umbilical vein endothelial cells and human lung fibroblasts to form a tissue mimic containing vascular networks. The artificial vascular networks provided channels for oxygen transport, thus reducing the hypoxic volume and preventing cell death. The endothelium of the vascular networks significantly retarded the occlusion of channels during whole-blood circulation. The tissue mimics have the potential to be used as an in vitro platform to examine the physiologic and pathologic phenomena through vascular architecture. PMID:27228079

A Risk Based Approach to Limit the Effects of Covert Channels for Internet Sensor Data Aggregators for Sensor Privacy

NASA Astrophysics Data System (ADS)

Viecco, Camilo H.; Camp, L. Jean

Effective defense against Internet threats requires data on global real time network status. Internet sensor networks provide such real time network data. However, an organization that participates in a sensor network risks providing a covert channel to attackers if that organization’s sensor can be identified. While there is benefit for every party when any individual participates in such sensor deployments, there are perverse incentives against individual participation. As a result, Internet sensor networks currently provide limited data. Ensuring anonymity of individual sensors can decrease the risk of participating in a sensor network without limiting data provision.

A modeling study of tidal energy extraction and the associated impact on tidal circulation in a multi-inlet bay system of Puget Sound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Taiping; Yang, Zhaoqing

Previous tidal energy projects in Puget Sound have focused on major deep channels such as Admiralty Inlet that have a larger power potential but pose greater technical challenges than minor tidal channels connecting to small sub-basins. This paper focuses on the possibility of extracting energy from minor tidal channels by using a hydrodynamic model to quantify the power potential and the associated impact on tidal circulation. The study site is a multi-inlet bay system connected by two narrow inlets, Agate Pass and Rich Passage, to the Main Basin of Puget Sound. A three-dimensional hydrodynamic model was applied to the studymore » site and calibrated for tidal elevations and currents. We examined three energy extraction scenarios in which turbines were deployed in each of the two passages and concurrently in both. Extracted power rates and associated changes in tidal elevation, current, tidal flux, and residence time were examined. Maximum instantaneous power rates reached 250 kW, 1550 kW, and 1800 kW, respectively, for the three energy extraction scenarios. The model suggests that with the proposed level of energy extraction, the impact on tidal circulation is very small. It is worth investigating the feasibility of harnessing tidal energy from minor tidal channels of Puget Sound.« less

A hybrid CNN feature model for pulmonary nodule malignancy risk differentiation.

PubMed

Wang, Huafeng; Zhao, Tingting; Li, Lihong Connie; Pan, Haixia; Liu, Wanquan; Gao, Haoqi; Han, Fangfang; Wang, Yuehai; Qi, Yifan; Liang, Zhengrong

2018-01-01

The malignancy risk differentiation of pulmonary nodule is one of the most challenge tasks of computer-aided diagnosis (CADx). Most recently reported CADx methods or schemes based on texture and shape estimation have shown relatively satisfactory on differentiating the risk level of malignancy among the nodules detected in lung cancer screening. However, the existing CADx schemes tend to detect and analyze characteristics of pulmonary nodules from a statistical perspective according to local features only. Enlightened by the currently prevailing learning ability of convolutional neural network (CNN), which simulates human neural network for target recognition and our previously research on texture features, we present a hybrid model that takes into consideration of both global and local features for pulmonary nodule differentiation using the largest public database founded by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). By comparing three types of CNN models in which two of them were newly proposed by us, we observed that the multi-channel CNN model yielded the best discrimination in capacity of differentiating malignancy risk of the nodules based on the projection of distributions of extracted features. Moreover, CADx scheme using the new multi-channel CNN model outperformed our previously developed CADx scheme using the 3D texture feature analysis method, which increased the computed area under a receiver operating characteristic curve (AUC) from 0.9441 to 0.9702.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

Centralized Routing and Scheduling Using Multi-Channel System Single Transceiver in 802.16d

NASA Astrophysics Data System (ADS)

Al-Hemyari, A.; Noordin, N. K.; Ng, Chee Kyun; Ismail, A.; Khatun, S.

This paper proposes a cross-layer optimized strategy that reduces the effect of interferences from neighboring nodes within a mesh networks. This cross-layer design relies on the routing information in network layer and the scheduling table in medium access control (MAC) layer. A proposed routing algorithm in network layer is exploited to find the best route for all subscriber stations (SS). Also, a proposed centralized scheduling algorithm in MAC layer is exploited to assign a time slot for each possible node transmission. The cross-layer optimized strategy is using multi-channel single transceiver and single channel single transceiver systems for WiMAX mesh networks (WMNs). Each node in WMN has a transceiver that can be tuned to any available channel for eliminating the secondary interference. Among the considered parameters in the performance analysis are interference from the neighboring nodes, hop count to the base station (BS), number of children per node, slot reuse, load balancing, quality of services (QoS), and node identifier (ID). Results show that the proposed algorithms significantly improve the system performance in terms of length of scheduling, channel utilization ratio (CUR), system throughput, and average end to end transmission delay.

Denitrification in the Mississippi River network controlled by flow through river bedforms

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson W.; Cardenas, M. Bayani; Kiel, Brian

2015-01-01

Increasing nitrogen concentrations in the world’s major rivers have led to over-fertilization of sensitive downstream waters. Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions. However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater - hyporheic zones. Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed - and thus vertical hyporheic exchange - would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering.

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

PubMed

Chambon, Stanislas; Galtier, Mathieu N; Arnal, Pierrick J; Wainrib, Gilles; Gramfort, Alexandre

2018-04-01

Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signals such as electroencephalograms (EEGs), electrooculograms (EOGs), electrocardiograms, and electromyograms (EMGs). We introduce here the first deep learning approach for sleep stage classification that learns end-to-end without computing spectrograms or extracting handcrafted features, that exploits all multivariate and multimodal polysomnography (PSG) signals (EEG, EMG, and EOG), and that can exploit the temporal context of each 30-s window of data. For each modality, the first layer learns linear spatial filters that exploit the array of sensors to increase the signal-to-noise ratio, and the last layer feeds the learnt representation to a softmax classifier. Our model is compared to alternative automatic approaches based on convolutional networks or decisions trees. Results obtained on 61 publicly available PSG records with up to 20 EEG channels demonstrate that our network architecture yields the state-of-the-art performance. Our study reveals a number of insights on the spatiotemporal distribution of the signal of interest: a good tradeoff for optimal classification performance measured with balanced accuracy is to use 6 EEG with 2 EOG (left and right) and 3 EMG chin channels. Also exploiting 1 min of data before and after each data segment offers the strongest improvement when a limited number of channels are available. As sleep experts, our system exploits the multivariate and multimodal nature of PSG signals in order to deliver the state-of-the-art classification performance with a small computational cost.

Growth laws for delta crevasses in the Mississippi River Delta: observations and modeling

NASA Astrophysics Data System (ADS)

Yocum, T. A.; Georgiou, I. Y.

2016-02-01

River deltas are accumulations of sedimentary deposits delivered by rivers via a network of distributary channels. Worldwide they are threatened by environmental changes, including subsidence, global sea level rise and a suite of other local factors. In the Mississippi River Delta (MRD) these impacts are exemplified, and have led to proposed solutions to build land that include sediment diversions, thereby reinitiating the delta cycle. While economically efficient, there are too few analogs of small deltas aside from laboratory studies, numerical modeling studies, theoretical approaches, and limited field driven observations. Anthropogenic crevasses in the modern delta are large enough to overcome limitations of laboratory deltas, and small enough to allow for "rapid" channel and wetland development, providing an ideal setting to investigate delta development mechanics. Crevasse metrics were obtained using a combination of geospatial tools, extracting key parameters (bifurcation length and width, channel order and depth) that were non-dimensionalized and compared to river-dominated delta networks previously studied. Analysis showed that most crevasses in the MRD appear to obey delta growth laws and delta allometry relationships, suggesting that crevasses do exhibit similar planform metrics to larger Deltas; the distance to mouth bar versus bifurcation order demonstrated to be a very reasonable first order estimate of delta-top footprint. However, some crevasses exhibited different growth metrics. To better understand the hydrodynamic and geomorphic controls governing crevasse evolution in the MRD, we assess delta dynamics via a suite of field observations and numerical modeling in both well-established and newly constructed crevasses. Our analysis suggests that delta development is affected by the relative influence of external (upstream and downstream) and internal controls on the hydrodynamic and sediment transport patterns in these systems.

Modeling Stochastic Boundary Conditions in a Coastal Catchment using a Bayesian Network: An Application to the Houston Ship Channel, Texas

NASA Astrophysics Data System (ADS)

Couasnon, Anaïs; Sebastian, Antonia; Morales-Nápoles, Oswaldo

2017-04-01

Recent research has highlighted the increased risk of compound flooding in the U.S. In coastal catchments, an elevated downstream water level, resulting from high tide and/or storm surge, impedes drainage creating a backwater effect that may exacerbate flooding in the riverine environment. Catchments exposed to tropical cyclone activity along the Gulf of Mexico and Atlantic coasts are particularly vulnerable. However, conventional flood hazard models focus mainly on precipitation-induced flooding and few studies accurately represent the hazard associated with the interaction between discharge and elevated downstream water levels. This study presents a method to derive stochastic boundary conditions for a coastal watershed. Mean daily discharge and maximum daily residual water levels are used to build a non-parametric Bayesian network (BN) based on copulas. Stochastic boundary conditions for the watershed are extracted from the BN and input into a 1-D process-based hydraulic model to obtain water surface elevations in the main channel of the catchment. The method is applied to a section of the Houston Ship Channel (Buffalo Bayou) in Southeast Texas. Data at six stream gages and two tidal stations are used to build the BN and 100-year joint return period events are modeled. We find that the dependence relationship between the daily residual water level and the mean daily discharge in the catchment can be represented by a Gumbel copula (Spearman's rank correlation coefficient of 0.31) and that they result in higher water levels in the mid- to upstream reaches of the watershed than when modeled independently. This indicates that conventional (deterministic) methods may underestimate the flood hazard associated with compound flooding in the riverine environment and that such interactions should not be neglected in future coastal flood hazard studies.

Experimental demonstration of optical stealth transmission over wavelength-division multiplexing network.

PubMed

Zhu, Huatao; Wang, Rong; Pu, Tao; Fang, Tao; Xiang, Peng; Zheng, Jilin; Tang, Yeteng; Chen, Dalei

2016-08-10

We propose and experimentally demonstrate an optical stealth transmission system over a 200 GHz-grid wavelength-division multiplexing (WDM) network. The stealth signal is processed by spectral broadening, temporal spreading, and power equalizing. The public signal is suppressed by multiband notch filtering at the stealth channel receiver. The interaction between the public and stealth channels is investigated in terms of public-signal-to-stealth-signal ratio, data rate, notch-filter bandwidth, and public channel number. The stealth signal can transmit over 80 km single-mode fiber with no error. Our experimental results verify the feasibility of optical steganography used over the existing WDM-based optical network.

Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

PubMed Central

Stojmirović, Aleksandar

2012-01-01

Abstract In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway, we illustrate the versatility and stability of our new framework. PMID:22409812

Coupling the Near and Far Field Models for Performance Assessment of Repositories for Spent Nuclear Fuel

NASA Astrophysics Data System (ADS)

Liu, L.; Neretnieks, I.

2006-12-01

ABSTRACT In our conceptualisation, water flows in channels in fractures in fractured rocks such as granites. In the Swedish concept for a repository for spent nuclear fuel the canisters containing the spent fuel are embedded in a buffer in holes below the floor of tunnels. The deposition holes can be intersected by fractures with channels with flowing water. The flow in individual channels is determined by the transmissivity properties of the network of the channels. The flowrate around a deposition hole and in the excavation damaged zone around the tunnels will control the rate of mass transfer of corrosive agents and of escaping nuclides. We call the carrying capacity of the solutes an equivalent flowrate. An escaping nuclide will reach the flowing water in the channel and be transported further into the channel network, mixing with water from other channels at some channel intersections and dividing into several channels at other intersection. In order to follow a nuclide from any leaking canister to the effluent points at the ground surface we have integrated our channel network model CHAN3D with our near field mass transfer model NUCTRAN. The NUCTRAN code, based on a compartment model can calculate the release of nuclides from a defective canister through different pathways into the near field of a repository from the local flowrates in the channels near the deposition hole obtained from CHAN3D. The network model CHAN3D uses observed transmissivity distributions and flowing fracture frequencies in boreholes to set up the 3-dimensional network of stochastic fractures. Deterministic fracture zones are described as such with their hydraulic, properties, sizes, locations and extensions. When available, information on fracture length distributions e.g. power law distributions and correlations between sizes and transmissivities are included in the network model. Once flowrates in all channels in the network have been calculated all equivalent flowrates for all canister positions can be calculated. The rate of transport of corrosive agents to and the releases of nuclides from any damaged canister are then calculated. For any given canister location the channel network model is then used to calculate the paths of the nuclides from the canister through the network by particle tracking. A large number of particles are released one by one from the canister and followed from one channel intersection to the next. A mixing rule is used at an intersection to decide which exit the particle takes. We mostly assume full mixing at intersections. The residence time and the ratio of flow wetted surface to flowrate along every path the particles traverse is summed. This information is sufficient to determine the residence time distribution (RTD) of the nuclides along that path also when they are subject to retardation by surface sorption and matrix diffusion. Actually this information is also sufficient to determine the RTD of arbitrary length decay chains subject to some minor (unimportant) simplifying assumptions. In this paper, we discuss in detail the coupling concept of how to integrate the near and far field models, together with the method of how to include transmissive fractures following a power law length distribution and fracture zones into CHAN3D in order to significantly decrease the computer time without loss of important features of the far field. The simulation results regarding a hypothetical repository located at the Forsmark area, Sweden, are also presented and discussed. Our study suggests that the integrated model can be used as an efficient tool to simulate the release of nuclides, including decay chains, from a repository and the transport to recipients.

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel

PubMed Central

Sakin, Sayef Azad; Alamri, Atif; Tran, Nguyen H.

2017-01-01

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies. PMID:29215591

Self-Coexistence among IEEE 802.22 Networks: Distributed Allocation of Power and Channel.

PubMed

Sakin, Sayef Azad; Razzaque, Md Abdur; Hassan, Mohammad Mehedi; Alamri, Atif; Tran, Nguyen H; Fortino, Giancarlo

2017-12-07

Ensuring self-coexistence among IEEE 802.22 networks is a challenging problem owing to opportunistic access of incumbent-free radio resources by users in co-located networks. In this study, we propose a fully-distributed non-cooperative approach to ensure self-coexistence in downlink channels of IEEE 802.22 networks. We formulate the self-coexistence problem as a mixed-integer non-linear optimization problem for maximizing the network data rate, which is an NP-hard one. This work explores a sub-optimal solution by dividing the optimization problem into downlink channel allocation and power assignment sub-problems. Considering fairness, quality of service and minimum interference for customer-premises-equipment, we also develop a greedy algorithm for channel allocation and a non-cooperative game-theoretic framework for near-optimal power allocation. The base stations of networks are treated as players in a game, where they try to increase spectrum utilization by controlling power and reaching a Nash equilibrium point. We further develop a utility function for the game to increase the data rate by minimizing the transmission power and, subsequently, the interference from neighboring networks. A theoretical proof of the uniqueness and existence of the Nash equilibrium has been presented. Performance improvements in terms of data-rate with a degree of fairness compared to a cooperative branch-and-bound-based algorithm and a non-cooperative greedy approach have been shown through simulation studies.

The Allergen Der p3 from House Dust Mite Stimulates Store-Operated Ca2+ Channels and Mast Cell Migration through PAR4 Receptors.

PubMed

Lin, Yu-Ping; Nelson, Charmaine; Kramer, Holger; Parekh, Anant B

2018-04-19

The house dust mite is the principal source of perennial aeroallergens in man. How these allergens activate innate and adaptive immunity is unclear, and therefore, there are no therapies targeting mite allergens. Here, we show that house dust mite extract activates store-operated Ca 2+ channels, a common signaling module in numerous cell types in the lung. Activation of channel pore-forming Orai1 subunits by mite extract requires gating by STIM1 proteins. Although mite extract stimulates both protease-activated receptor type 2 (PAR2) and PAR4 receptors, Ca 2+ influx is more tightly coupled to the PAR4 pathway. We identify a major role for the serine protease allergen Der p3 in stimulating Orai1 channels and show that a therapy involving sub-maximal inhibition of both Der p3 and Orai1 channels suppresses mast cell activation to house dust mite. Our results reveal Der p3 as an important aeroallergen that activates Ca 2+ channels and suggest a therapeutic strategy for treating mite-induced asthma. Copyright © 2018 Elsevier Inc. All rights reserved.

Plant Species Identification by Bi-channel Deep Convolutional Networks

NASA Astrophysics Data System (ADS)

He, Guiqing; Xia, Zhaoqiang; Zhang, Qiqi; Zhang, Haixi; Fan, Jianping

2018-04-01

Plant species identification achieves much attention recently as it has potential application in the environmental protection and human life. Although deep learning techniques can be directly applied for plant species identification, it still needs to be designed for this specific task to obtain the state-of-art performance. In this paper, a bi-channel deep learning framework is developed for identifying plant species. In the framework, two different sub-networks are fine-tuned over their pretrained models respectively. And then a stacking layer is used to fuse the output of two different sub-networks. We construct a plant dataset of Orchidaceae family for algorithm evaluation. Our experimental results have demonstrated that our bi-channel deep network can achieve very competitive performance on accuracy rates compared to the existing deep learning algorithm.

Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay Receiver Design Issues

DTIC Science & Technology

2011-03-01

222 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 59, NO. 9, SEPTEMBER 2011 2595 Noncoherent Physical-Layer Network Coding with FSK Modulation: Relay... noncoherent reception, channel estima- tion. I. INTRODUCTION IN the two-way relay channel (TWRC), a pair of sourceterminals exchange information...2011 4. TITLE AND SUBTITLE Noncoherent Physical-Layer Network Coding with FSK Modulation:Relay Receiver Design Issues 5a. CONTRACT NUMBER 5b

Engineering anastomosis between living capillary networks and endothelial cell-lined microfluidic channels.

PubMed

Wang, Xiaolin; Phan, Duc T T; Sobrino, Agua; George, Steven C; Hughes, Christopher C W; Lee, Abraham P

2016-01-21

This paper reports a method for generating an intact and perfusable microvascular network that connects to microfluidic channels without appreciable leakage. This platform incorporates different stages of vascular development including vasculogenesis, endothelial cell (EC) lining, sprouting angiogenesis, and anastomosis in sequential order. After formation of a capillary network inside the tissue chamber via vasculogenesis, the adjacent microfluidic channels are lined with a monolayer of ECs, which then serve as the high-pressure input ("artery") and low pressure output ("vein") conduits. To promote a tight interconnection between the artery/vein and the capillary network, sprouting angiogenesis is induced, which promotes anastomosis of the vasculature inside the tissue chamber with the EC lining along the microfluidic channels. Flow of fluorescent microparticles confirms the perfusability of the lumenized microvascular network, and minimal leakage of 70 kDa FITC-dextran confirms physiologic tightness of the EC junctions and completeness of the interconnections between artery/vein and the capillary network. This versatile device design and its robust construction methodology establish a physiological transport model of interconnected perfused vessels from artery to vascularized tissue to vein. The system has utility in a wide range of organ-on-a-chip applications as it enables the physiological vascular interconnection of multiple on-chip tissue constructs that can serve as disease models for drug screening.

Design and Implementation of an Underlay Control Channel for Cognitive Radios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daryl Wasden; Hussein Moradi; Behrouz Farhang-Boroujeny

Implementation of any cognitive radio network requires an effective control channel that can operate under various modes of activity from the primary users. This paper reports the design and implementation of a filter bank multicarrier spread spectrum (FBMC-SS) system for use as the control channel in cognitive radio networks. The proposed design is based on a filtered multitone (FMT) implementation. Carrier and timing acquisition and tracking methods as well as a blind channel estimation method are developed for the proposed control channel. We also report an implementation of the proposed FBMC-SS system on a hardware platform; a FlexRIO FPGA modulemore » from National Instruments.« less

Network Structure as a Modulator of Disturbance Impacts in Streams

NASA Astrophysics Data System (ADS)

Warner, S.; Tullos, D. D.

2017-12-01

This study examines how river network structure affects the propagation of geomorphic and anthropogenic disturbances through streams. Geomorphic processes such as debris flows can alter channel morphology and modify habitat for aquatic biota. Anthropogenic disturbances such as road construction can interact with the geomorphology and hydrology of forested watersheds to change sediment and water inputs to streams. It was hypothesized that the network structure of streams within forested watersheds would influence the location and magnitude of the impacts of debris flows and road construction on sediment size and channel width. Longitudinal surveys were conducted every 50 meters for 11 kilometers of third-to-fifth order streams in the H.J. Andrews Experimental Forest in the Western Cascade Range of Oregon. Particle counts and channel geometry measurements were collected to characterize the geomorphic impacts of road crossings and debris flows as disturbances. Sediment size distributions and width measurements were plotted against the distance of survey locations through the network to identify variations in longitudinal trends of channel characteristics. Thresholds for the background variation in sediment size and channel width, based on the standard deviations of sample points, were developed for sampled stream segments characterized by location as well as geomorphic and land use history. Survey locations were classified as "disturbed" when they deviated beyond the reference thresholds in expected sediment sizes and channel widths, as well as flow-connected proximity to debris flows and road crossings. River network structure was quantified by drainage density and centrality of nodes upstream of survey locations. Drainage density and node centrality were compared between survey locations with similar channel characteristic classifications. Cluster analysis was used to assess the significance of survey location, proximity of survey location to debris flows and road crossings, drainage density and node centrality in predicting sediment size and channel width classifications for locations within the watershed. Results contribute to the understanding of susceptibility and responses of streams supporting critical habitat for aquatic species to debris flows and forest road disturbances.

CCSDS Advanced Orbiting Systems Virtual Channel Access Service for QoS MACHETE Model

NASA Technical Reports Server (NTRS)

Jennings, Esther H.; Segui, John S.

2011-01-01

To support various communications requirements imposed by different missions, interplanetary communication protocols need to be designed, validated, and evaluated carefully. Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in "Simulator of Space Communication Networks" (NPO-41373), NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. By building abstract behavioral models of network protocols, one can validate performance after identifying the appropriate metrics of interest. The innovators have extended the MACHETE model library to include a generic link-layer Virtual Channel (VC) model supporting quality-of-service (QoS) controls based on IP streams. The main purpose of this generic Virtual Channel model addition was to interface fine-grain flow-based QoS (quality of service) between the network and MAC layers of the QualNet simulator, a commercial component of MACHETE. This software model adds the capability of mapping IP streams, based on header fields, to virtual channel numbers, allowing extended QoS handling at link layer. This feature further refines the QoS v existing at the network layer. QoS at the network layer (e.g. diffserv) supports few QoS classes, so data from one class will be aggregated together; differentiating between flows internal to a class/priority is not supported. By adding QoS classification capability between network and MAC layers through VC, one maps multiple VCs onto the same physical link. Users then specify different VC weights, and different queuing and scheduling policies at the link layer. This VC model supports system performance analysis of various virtual channel link-layer QoS queuing schemes independent of the network-layer QoS systems.

OpenFlow arbitrated programmable network channels for managing quantum metadata

DOE PAGES

Dasari, Venkat R.; Humble, Travis S.

2016-10-10

Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-definedmore » network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. Here, we conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.« less

OpenFlow arbitrated programmable network channels for managing quantum metadata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasari, Venkat R.; Humble, Travis S.

Quantum networks must classically exchange complex metadata between devices in order to carry out information for protocols such as teleportation, super-dense coding, and quantum key distribution. Demonstrating the integration of these new communication methods with existing network protocols, channels, and data forwarding mechanisms remains an open challenge. Software-defined networking (SDN) offers robust and flexible strategies for managing diverse network devices and uses. We adapt the principles of SDN to the deployment of quantum networks, which are composed from unique devices that operate according to the laws of quantum mechanics. We show how quantum metadata can be managed within a software-definedmore » network using the OpenFlow protocol, and we describe how OpenFlow management of classical optical channels is compatible with emerging quantum communication protocols. We next give an example specification of the metadata needed to manage and control quantum physical layer (QPHY) behavior and we extend the OpenFlow interface to accommodate this quantum metadata. Here, we conclude by discussing near-term experimental efforts that can realize SDN’s principles for quantum communication.« less

Automated identification of stream-channel geomorphic features from high‑resolution digital elevation models in West Tennessee watersheds

USGS Publications Warehouse

Cartwright, Jennifer M.; Diehl, Timothy H.

2017-01-17

High-resolution digital elevation models (DEMs) derived from light detection and ranging (lidar) enable investigations of stream-channel geomorphology with much greater precision than previously possible. The U.S. Geological Survey has developed the DEM Geomorphology Toolbox, containing seven tools to automate the identification of sites of geomorphic instability that may represent sediment sources and sinks in stream-channel networks. These tools can be used to modify input DEMs on the basis of known locations of stormwater infrastructure, derive flow networks at user-specified resolutions, and identify possible sites of geomorphic instability including steep banks, abrupt changes in channel slope, or areas of rough terrain. Field verification of tool outputs identified several tool limitations but also demonstrated their overall usefulness in highlighting likely sediment sources and sinks within channel networks. In particular, spatial clusters of outputs from multiple tools can be used to prioritize field efforts to assess and restore eroding stream reaches.

Histological analysis of the alterations on cortical bone channels network after radiotherapy: A rabbit study.

PubMed

Rabelo, Gustavo Davi; Beletti, Marcelo Emílio; Dechichi, Paula

2010-10-01

The aim of this study was to evaluate the effects of radiotherapy in cortical bone channels network. Fourteen rabbits were divided in two groups and test group received single dose of 15 Gy cobalt-60 radiation in tibia, bilaterally. The animals were sacrificed and a segment of tibia was removed and histologically processed. Histological images were taken and had their bone channels segmented and called regions of interest (ROI). Images were analyzed through developed algorithms using the SCILAB mathematical environment, getting percentage of bone matrix, ROI areas, ROI perimeters, their standard deviations and Lacunarity. The osteocytes and empty lacunae were also counted. Data were evaluated using Kolmogorov-Smirnov, Mann Whitney, and Student's t test (P < 0.05). Significant differences in bone matrix percentage, area and perimeters of the channels, their respective standard deviations and lacunarity were found between groups. In conclusion, the radiotherapy causes reduction of bone matrix and modifies the morphology of bone channels network. © 2010 Wiley-Liss, Inc.

Energy reduction using multi-channels optical wireless communication based OFDM

NASA Astrophysics Data System (ADS)

Darwesh, Laialy; Arnon, Shlomi

2017-10-01

In recent years, an increasing number of data center networks (DCNs) have been built to provide various cloud applications. Major challenges in the design of next generation DC networks include reduction of the energy consumption, high flexibility and scalability, high data rates, minimum latency and high cyber security. Use of optical wireless communication (OWC) to augment the DC network could help to confront some of these challenges. In this paper we present an OWC multi channels communication method that could lead to significant energy reduction of the communication equipment. The method is to convert a high speed serial data stream to many slower and parallel streams and vies versa at the receiver. We implement this concept of multi channels using optical orthogonal frequency division multiplexing (O-OFDM) method. In our scheme, we use asymmetrically clipped optical OFDM (ACO-OFDM). Our results show that the realization of multi channels OFDM (ACO-OFDM) methods reduces the total energy consumption exponentially, as the number of channels transmitted through them rises.

Traffic shaping and scheduling for OBS-based IP/WDM backbones

NASA Astrophysics Data System (ADS)

Elhaddad, Mahmoud S.; Melhem, Rami G.; Znati, Taieb; Basak, Debashis

2003-10-01

We introduce Proactive Reservation-based Switching (PRS) -- a switching architecture for IP/WDM networks based on Labeled Optical Burst Switching. PRS achieves packet delay and loss performance comparable to that of packet-switched networks, without requiring large buffering capacity, or burst scheduling across a large number of wavelengths at the core routers. PRS combines proactive channel reservation with periodic shaping of ingress-egress traffic aggregates to hide the offset latency and approximate the utilization/buffering characteristics of discrete-time queues with periodic arrival streams. A channel scheduling algorithm imposes constraints on burst departure times to ensure efficient utilization of wavelength channels and to maintain the distance between consecutive bursts through the network. Results obtained from simulation using TCP traffic over carefully designed topologies indicate that PRS consistently achieves channel utilization above 90% with modest buffering requirements.

Advanced teleprocessing systems

NASA Astrophysics Data System (ADS)

Kleinrock, L.; Gerla, M.

1982-09-01

This Annual Technical Report covers research covering the period from October 1, 1981 to September 30, 1982. This contract has three primary designated research areas: packet radio systems, resource sharing and allocation, and distributed processing and control. This report contains abstracts of publications which summarize research results in these areas followed by the main body of the report which is devoted to a study of channel access protocols that are executed by the nodes of a network to schedule their transmissions on multi-access broadcast channel. In particular the main body consists of a Ph.D. dissertation, Channel Access Protocols for Multi-Hop Broadcast Packet Radio Networks. This work discusses some new channel access protocols useful for mobile radio networks. Included is an analysis of slotted ALOHA and some tight bounds on the performance of all possible protocols in a mobile environment.

Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks.

PubMed

Milz, Patricia; Pascual-Marqui, Roberto D; Lehmann, Dietrich; Faber, Pascal L

2016-05-01

Functional states of the brain are constituted by the temporally attuned activity of spatially distributed neural networks. Such networks can be identified by independent component analysis (ICA) applied to frequency-dependent source-localized EEG data. This methodology allows the identification of networks at high temporal resolution in frequency bands of established location-specific physiological functions. EEG measurements are sensitive to neural activity changes in cortical areas of modality-specific processing. We tested effects of modality-specific processing on functional brain networks. Phasic modality-specific processing was induced via tasks (state effects) and tonic processing was assessed via modality-specific person parameters (trait effects). Modality-specific person parameters and 64-channel EEG were obtained from 70 male, right-handed students. Person parameters were obtained using cognitive style questionnaires, cognitive tests, and thinking modality self-reports. EEG was recorded during four conditions: spatial visualization, object visualization, verbalization, and resting. Twelve cross-frequency networks were extracted from source-localized EEG across six frequency bands using ICA. RMANOVAs, Pearson correlations, and path modelling examined effects of tasks and person parameters on networks. Results identified distinct state- and trait-dependent functional networks. State-dependent networks were characterized by decreased, trait-dependent networks by increased alpha activity in sub-regions of modality-specific pathways. Pathways of competing modalities showed opposing alpha changes. State- and trait-dependent alpha were associated with inhibitory and automated processing, respectively. Antagonistic alpha modulations in areas of competing modalities likely prevent intruding effects of modality-irrelevant processing. Considerable research suggested alpha modulations related to modality-specific states and traits. This study identified the distinct electrophysiological cortical frequency-dependent networks within which they operate.

Multi-channel multi-radio using 802.11 based media access for sink nodes in wireless sensor networks.

PubMed

Campbell, Carlene E-A; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Multi-Channel Multi-Radio Using 802.11 Based Media Access for Sink Nodes in Wireless Sensor Networks

PubMed Central

Campbell, Carlene E.-A.; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives. PMID:22163883

Social Network Analysis of the Farabi Exchange Program: Student Mobility

ERIC Educational Resources Information Center

Ugurlu, Zeynep

2016-01-01

Problem Statement: Exchange programs offer communication channels created through student and instructor exchanges; a flow of information takes place through these channels. The Farabi Exchange Program (FEP) is a student and instructor exchange program between institutions of higher education. Through the use of social network analysis and…

A novel speech-processing strategy incorporating tonal information for cochlear implants.

PubMed

Lan, N; Nie, K B; Gao, S K; Zeng, F G

2004-05-01

Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-processing strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F0) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundatmental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F0 information. We then compared the novel strategy with the envelope-extraction CIS strategy in human subjects with normal hearing. The novel strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages.

River network bedload model: a tool to investigate the impact of flow regulation on grain size distribution in a large Alpine catchment

NASA Astrophysics Data System (ADS)

Costa, Anna; Molnar, Peter

2017-04-01

Sediment transport rates along rivers and the grain size distribution (GSD) of coarse channel bed sediment are the result of the long term balance between transport capacity and sediment supply. Transport capacity, mainly a function of channel geometry and flow competence, can be altered by changes in climatic forcing as well as by human activities. In Alpine rivers it is hydropower production systems that are the main causes of modification to the transport capacity of water courses through flow regulation, leading over longer time scales to the adjustment of river bed GSDs. We developed a river network bedload transport model to evaluate the impacts of hydropower on the transfer of sediments and the GSDs of the Upper Rhône basin, a 5,200 km2 catchment located in the Swiss Alps. Many large reservoirs for hydropower production have been built along the main tributaries of the Rhône River since the 1960s, resulting in a complex system of intakes, tunnels, and pumping stations. Sediment storage behind dams and intakes, is accompanied by altered discharge due to hydropower operations, mainly higher flow in winter and lower in summer. It is expected that this change in flow regime may have resulted in different bedload transport. However, due the non-linear, threshold-based nature of the relation between discharge and sediment mobilization, the effects of changed hydraulic conditions are not easily deducible, and because observations of bedload in pre- and post-dam conditions are usually not available, a modelling approach is often necessary. In our modelling approach, the river network is conceptualized as a series of connected links (river reaches). Average geometric characteristics of each link (width, length, and slope of cross section) are extracted from digital elevation data, while surface roughness coefficients are assigned based on the GSD. Under the assumptions of rectangular prismatic cross sections and normal flow conditions, bed shear stress is estimated from available time series of daily discharge distributed along the river network. Potential bedload transport is estimated by the Wilcock and Crowe surface-based model for the entire GSD. Mass balance between transport capacity and sediment supply, applied to each individual grain size, determines the actual transport and the resulting GSD of the channel bed. Channel bed erosion is allowed through a long-term erosion rate. Sediment input from hillslopes is included as lateral sediment flux. Initial and boundary conditions are set based on available data of GSDs, while an approximation of the depth of the mobile bed is selected through sensitivity analysis. With the river network bedload model we aim to estimate the effect of flow regulation, i.e. altered transport capacity, on sediment transport and GSD of the entire Rhône river system. The model can also be applied as a tool to explore possible changes in bedload transport and channel GSDs under different discharge scenarios based, for example, on climate change projections or modified hydropower operation policies.

Laws of valley growth

NASA Astrophysics Data System (ADS)

Seybold, Hansjoerg; Yi, Robert; Willenbring, Jane; Kirchner, James; Rothman, Daniel

2015-04-01

The question of how the channel heads advance has long been debated [1,2]. By studying a simplified setting - channels incised by re-emerging groundwater flow - we seek insight into the headward growth of channel networks, by combining theoretical modeling with field observations. A concept for how such seepage channel systems form was first proposed by T. Dunne in the early 1980s [2]. A small bulge in the sidewall of a stream focuses ground water flow. This results in a larger flux and therefore a higher erosion rate in this direction. Over time such small perturbations grow into newly formed streams, but how they do so and how erosion depends on the water flux is unclear. The theory of diffusive growth provides a theoretical framework to describe channelization in response to groundwater flow. For this system the underlying physical equations are well-defined, and numerical and analytical predictions can be obtained and tested in the field. If a stream advances at a rate v˜ q^η, where q is the discharge of ground water into the tip, theory predicts that η has to be smaller than a critical value η^star to obtain ramified networks [3]. We test this hypothesis by measuring erosion rates in a field site in the Florida Panhandle, which provides a natural laboratory to study channel incision by re-emerging groundwater flow [4]. Our theoretical network reconstruction yields tip growth rates which we can directly compare to observational rates obtained from cosmogenic 10Be measurements. This comparison of theory and observation allows us to verify the existence of a constitutive discharge-erosion relation, and to better characterize growth and competition of streams at the channel head. [1] Montgommery, D. R. and Dietrich, W. E. Where do channels begin?, Nature, 336, no. 6196 (1988): 232-234 [2] Dunne, T. Formation and controls of channel networks, Prog. Phys. Geogr., 4 (1980): 211-239 [3] Carleson, L. and Makarov, N. Laplacian path models, J. Anal. Math., 87, no. 1 (2002): 103-150 [4] Devauchelle, O., Petroff, A. P., Seybold, H., & Rothman, D. H. Ramification of stream networks, PNAS, 109 (51), 20832-20836.

Key Exchange Trust Evaluation in Peer-to-Peer Sensor Networks With Unconditionally Secure Key Exchange

NASA Astrophysics Data System (ADS)

Gonzalez, Elias; Kish, Laszlo B.

2016-03-01

As the utilization of sensor networks continue to increase, the importance of security becomes more profound. Many industries depend on sensor networks for critical tasks, and a malicious entity can potentially cause catastrophic damage. We propose a new key exchange trust evaluation for peer-to-peer sensor networks, where part of the network has unconditionally secure key exchange. For a given sensor, the higher the portion of channels with unconditionally secure key exchange the higher the trust value. We give a brief introduction to unconditionally secured key exchange concepts and mention current trust measures in sensor networks. We demonstrate the new key exchange trust measure on a hypothetical sensor network using both wired and wireless communication channels.

GEOMORPHIC THRESHOLDS AND CHANNEL MORPHOLOGY IN LARGE RIVERS

EPA Science Inventory

Systematic changes in channel morphology occur as channel gradient, streamflow, and sediment character change and interact. Geomorphic thresholds of various kinds are useful metrics to define these changes along the river network, as they are based on in-channel processes that d...

Measurement of the Single Top Quark Cross Section in the Lepton Plus Jets Final State in Proton-Antiproton Collisions at a Center of Mass Energy of 1.96 TeV Using the CDF II Detector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Zhenbin

2012-01-01

We present a measurement of the single top quark cross section in the lepton plus jets final state using an integrated luminosity corresponding to 7.5 fb -1 of p\\bar p collision data collected by the Collider Detector at Fermilab. The single top candidate events are identified by the signature of a charged lepton, large missing transverse energy, and two or three jets with at least one of them identified as originating from a bottom quark. A new Monte Carlo generator POWHEG is used to model the single top quark production processes, which include s-channel, t-channel, and Wt-channel. A neural network multivariate method is exploited to discriminate the single top quark signal from the comparatively large backgrounds. We measure a single top production cross section ofmore » $$3.04^{+0.57}_{-0.53} (\\mathrm{stat.~+~syst.})$$ pb assuming $$m_{\\rm top}=172.5$$~GeV/$c^2$. In addition, we extract the CKM matrix element value $$|V_{tb}|=0.96\\pm 0.09~(\\mathrm{stat.~+~syst.})\\ ± 0.05~(\\mathrm{theory})$$ and set a lower limit of $$|V_{tb}|>0.78$$ at the 95% credibility level.« less

Hypertensive retinopathy identification through retinal fundus image using backpropagation neural network

NASA Astrophysics Data System (ADS)

Syahputra, M. F.; Amalia, C.; Rahmat, R. F.; Abdullah, D.; Napitupulu, D.; Setiawan, M. I.; Albra, W.; Nurdin; Andayani, U.

2018-03-01

Hypertension or high blood pressure can cause damage of blood vessels in the retina of eye called hypertensive retinopathy (HR). In the event Hypertension, it will cause swelling blood vessels and a decrese in retina performance. To detect HR in patients body, it is usually performed through physical examination of opthalmoscope which is still conducted manually by an ophthalmologist. Certainly, in such a manual manner, takes a ong time for a doctor to detetct HR on aa patient based on retina fundus iamge. To overcome ths problem, a method is needed to identify the image of retinal fundus automatically. In this research, backpropagation neural network was used as a method for retinal fundus identification. The steps performed prior to identification were pre-processing (green channel, contrast limited adapative histogram qualization (CLAHE), morphological close, background exclusion, thresholding and connected component analysis), feature extraction using zoning. The results show that the proposed method is able to identify retinal fundus with an accuracy of 95% with maximum epoch of 1500.

Hydrogen-Bonded Network and Water Dynamics in the D-channel of Cytochrome c Oxidase.

PubMed

Ghane, Tahereh; Gorriz, Rene F; Wrzalek, Sandro; Volkenandt, Senta; Dalatieh, Ferand; Reidelbach, Marco; Imhof, Petra

2018-02-12

Proton transfer in cytochrome c oxidase (CcO) from the cellular inside to the binuclear redox centre as well as proton pumping through the membrane takes place through proton entrance via two distinct pathways, the D- and K-channel. Both channels show a dependence of their hydration level on the protonation states of their key residues, K362 for the K-channel, and E286 or D132 for the D-channel. In the oxidative half of CcO's catalytic cycle the D-channel is the proton-conducting path. For this channel, an interplay of protonation state of the D-channel residues with the water and hydrogen-bond dynamics has been observed in molecular dynamics simulations of the CcO protein, embedded in a lipid bi-layer, modelled in different protonation states. Protonation of residue E286 at the end of the D-channel results in a hydrogen-bonded network pointing from E286 to N139, that is against proton transport, and favouring N139 conformations which correspond to a closed asparagine gate (formed by residues N121 and N139). Consequently, the hydration level is lower than with unprotonated E286. In those models, the Asn gate is predominantly open, allowing water molecules to pass and thus increase the hydration level. The hydrogen-bonded network in these states exhibits longer life times of the Asn residues with water than other models and shows the D-channel to be traversable from the entrance, D132, to exit, E286. The D-channel can thus be regarded as auto-regulated with respect to proton transport, allowing proton passage only when required, that is the proton is located at the lower part of the D-channel (D132 to Asn gate) and not at the exit (E286).

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

PubMed

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-09-12

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs.

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks

PubMed Central

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-01-01

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end, simulations are made using MATLAB, and the results show that the Extended version of NEAMCBTC algorithm (Ext-NEAMCBTC) outperforms the compared techniques in terms of channel quality and stability assessment. It also minimizes channel switching overheads (in terms of switching delays and energy consumption) for accommodating stream-based communication in multichannel WSNs. PMID:27626429

Highly Efficient Multi Channel Packet Forwarding with Round Robin Intermittent Periodic Transmit for Multihop Wireless Backhaul Networks

PubMed Central

Furukawa, Hiroshi

2017-01-01

Round Robin based Intermittent Periodic Transmit (RR-IPT) has been proposed which achieves highly efficient multi-hop relays in multi-hop wireless backhaul networks (MWBN) where relay nodes are 2-dimensionally deployed. This paper newly investigates multi-channel packet scheduling and forwarding scheme for RR-IPT. Downlink traffic is forwarded by RR-IPT via one of the channels, while uplink traffic and part of downlink are accommodated in the other channel. By comparing IPT and carrier sense multiple access with collision avoidance (CSMA/CA) for uplink/downlink packet forwarding channel, IPT is more effective in reducing packet loss rate whereas CSMA/CA is better in terms of system throughput and packet delay improvement. PMID:29137164

Why Does Mptcp Have To Make Things So Complicated : Cross Path Nids Evasion And Countermeasures

DTIC Science & Technology

2016-09-01

previously only establish communication channels over single network paths to communicate over multiple network paths. MPTCP is an enhancement toTCP that...the attacker would fail to create a Command and Control (C2) channel unless the attacker had created a new mapping to the target on the splicing...machine. This would allow the attacker to conduct C2 over a spliced channel . This may even make the attacker’s C2 more evasive. In fact, the effect

On the ecogeomorphological feedbacks that control tidal channel network evolution in a sandy mangrove setting

PubMed Central

van Maanen, B.; Coco, G.; Bryan, K. R.

2015-01-01

An ecomorphodynamic model was developed to study how Avicennia marina mangroves influence channel network evolution in sandy tidal embayments. The model accounts for the effects of mangrove trees on tidal flow patterns and sediment dynamics. Mangrove growth is in turn controlled by hydrodynamic conditions. The presence of mangroves was found to enhance the initiation and branching of tidal channels, partly because the extra flow resistance in mangrove forests favours flow concentration, and thus sediment erosion in between vegetated areas. The enhanced branching of channels is also the result of a vegetation-induced increase in erosion threshold. On the other hand, this reduction in bed erodibility, together with the soil expansion driven by organic matter production, reduces the landward expansion of channels. The ongoing accretion in mangrove forests ultimately drives a reduction in tidal prism and an overall retreat of the channel network. During sea-level rise, mangroves can potentially enhance the ability of the soil surface to maintain an elevation within the upper portion of the intertidal zone, while hindering both the branching and headward erosion of the landward expanding channels. The modelling results presented here indicate the critical control exerted by ecogeomorphological interactions in driving landscape evolution. PMID:26339195

High performance network and channel-based storage

NASA Technical Reports Server (NTRS)

Katz, Randy H.

1991-01-01

In the traditional mainframe-centered view of a computer system, storage devices are coupled to the system through complex hardware subsystems called input/output (I/O) channels. With the dramatic shift towards workstation-based computing, and its associated client/server model of computation, storage facilities are now found attached to file servers and distributed throughout the network. We discuss the underlying technology trends that are leading to high performance network-based storage, namely advances in networks, storage devices, and I/O controller and server architectures. We review several commercial systems and research prototypes that are leading to a new approach to high performance computing based on network-attached storage.

An extended smart utilization medium access control (ESU-MAC) protocol for ad hoc wireless systems

NASA Astrophysics Data System (ADS)

Vashishtha, Jyoti; Sinha, Aakash

2006-05-01

The demand for spontaneous setup of a wireless communication system has increased in recent years for areas like battlefield, disaster relief operations etc., where a pre-deployment of network infrastructure is difficult or unavailable. A mobile ad-hoc network (MANET) is a promising solution, but poses a lot of challenges for all the design layers, specifically medium access control (MAC) layer. Recent existing works have used the concepts of multi-channel and power control in designing MAC layer protocols. SU-MAC developed by the same authors, efficiently uses the 'available' data and control bandwidth to send control information and results in increased throughput via decreasing contention on the control channel. However, SU-MAC protocol was limited for static ad-hoc network and also faced the busy-receiver node problem. We present the Extended SU-MAC (ESU-MAC) protocol which works mobile nodes. Also, we significantly improve the scheme of control information exchange in ESU-MAC to overcome the busy-receiver node problem and thus, further avoid the blockage of control channel for longer periods of time. A power control scheme is used as before to reduce interference and to effectively re-use the available bandwidth. Simulation results show that ESU-MAC protocol is promising for mobile, ad-hoc network in terms of reduced contention at the control channel and improved throughput because of channel re-use. Results show a considerable increase in throughput compared to SU-MAC which could be attributed to increased accessibility of control channel and improved utilization of data channels due to superior control information exchange scheme.

Simulation and Spectrum Extraction in the Spectroscopic Channel of the SNAP Experiment

NASA Astrophysics Data System (ADS)

Tilquin, Andre; Bonissent, A.; Gerdes, D.; Ealet, A.; Prieto, E.; Macaire, C.; Aumenier, M. H.

2007-05-01

A pixel-level simulation software is described. It is composed of two modules. The first module applies Fourier optics at each active element of the system to construct the PSF at a large variety of wavelengths and spatial locations of the point source. The input is provided by the engineer's design program (Zemax). It describes the optical path and the distortions. The PSF properties are compressed and interpolated using shapelets decomposition and neural network techniques. A second module is used for production jobs. It uses the output of the first module to reconstruct the relevant PSF and integrate it on the detector pixels. Extended and polychromatic sources are approximated by a combination of monochromatic point sources. For the spectrum extraction, we use a fast simulator based on a multidimensional linear interpolation of the pixel response tabulated on a grid of values of wavelength, position on sky and slice number. The prediction of the fast simulator is compared to the observed pixel content, and a chi-square minimization where the parameters are the bin contents is used to build the extracted spectrum. The visible and infrared arms are combined in the same chi-square, providing a single spectrum.

76 FR 33656 - Television Broadcasting Services; Nashville, TN

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-09

.... SUMMARY: The Commission grants a petition for rulemaking filed by NewsChannel 5 Network, LLC (``News... Nashville. According to NewsChannel 5, after WTVF(TV) transitioned from its pre-transition digital channel...

Venusian channels and valleys - Distribution and volcanological implications

NASA Technical Reports Server (NTRS)

Komatsu, Goro; Baker, Victor R.; Gulick, Virginia C.; Parker, Timothy J.

1993-01-01

An updated map is presented which shows the distribution of more than 200 channels and valleys on Venus. A large number of channels are concentrated in equatorial regions characterized by highlands, rift and fracture zones, an associated volcanic features. Many channels associated with flow deposits are similar to typical terrestrial lava drainage channels. They are associated with a wide range of volcanic edifices. More than half of the sinuous rilles are associated with coronae, coronalike features, or arachnoids. Corona volcanism driven by mantle plume events may explain this association. Many valley network are observed in highlands and in association with coronae, coronalike features, or arachnoids. This indicates that highlands and coronae provided fractures and flow-viscosity lavas, both of which seem to be required for network formation by lava sapping processes. Canali-type channels have a unique distribution limited to some plains regions.

A (very) Simple Model for the Aspect Ratio of High-Order River Basins

NASA Astrophysics Data System (ADS)

Shelef, E.

2017-12-01

The structure of river networks dictates the distribution of elevation, water, and sediments across Earth's surface. Despite its intricate shape, the structure of high-order river networks displays some surprising regularities such as the consistent aspect ratio (i.e., basin's width over length) of river basins along linear mountain fronts. This ratio controls the spacing between high-order channels as well as the spacing between the depositional bodies they form. It is generally independent of tectonic and climatic conditions and is often attributed to the initial topography over which the network was formed. This study shows that a simple, cross-like channel model explains this ratio via a requirement for equal elevation gain between the outlets and drainage-divides of adjacent channels at topographic steady state. This model also explains the dependence of aspect ratio on channel concavity and the location of the widest point on a drainage divide.

Two algorithms for neural-network design and training with application to channel equalization.

PubMed

Sweatman, C Z; Mulgrew, B; Gibson, G J

1998-01-01

We describe two algorithms for designing and training neural-network classifiers. The first, the linear programming slab algorithm (LPSA), is motivated by the problem of reconstructing digital signals corrupted by passage through a dispersive channel and by additive noise. It constructs a multilayer perceptron (MLP) to separate two disjoint sets by using linear programming methods to identify network parameters. The second, the perceptron learning slab algorithm (PLSA), avoids the computational costs of linear programming by using an error-correction approach to identify parameters. Both algorithms operate in highly constrained parameter spaces and are able to exploit symmetry in the classification problem. Using these algorithms, we develop a number of procedures for the adaptive equalization of a complex linear 4-quadrature amplitude modulation (QAM) channel, and compare their performance in a simulation study. Results are given for both stationary and time-varying channels, the latter based on the COST 207 GSM propagation model.

Parallel multipoint recording of aligned and cultured neurons on corresponding Micro Channel Array toward on-chip cell analysis.

PubMed

Tonomura, W; Moriguchi, H; Jimbo, Y; Konishi, S

2008-01-01

This paper describes an advanced Micro Channel Array (MCA) so as to record neuronal network at multiple points simultaneously. Developed MCA is designed for neuronal network analysis which has been studied by co-authors using MEA (Micro Electrode Arrays) system. The MCA employs the principle of the extracellular recording. Presented MCA has the following advantages. First of all, the electrodes integrated around individual micro channels are electrically isolated for parallel multipoint recording. Sucking and clamping of cells through micro channels is expected to improve the cellular selectivity and S/N ratio. In this study, hippocampal neurons were cultured on the developed MCA. As a result, the spontaneous and evoked spike potential could be recorded by sucking and clamping the cells at multiple points. Herein, we describe the successful experimental results together with the design and fabrication of the advanced MCA toward on-chip analysis of neuronal network.

Interplay between spatially explicit sediment sourcing, hierarchical river-network structure, and in-channel bed material sediment transport and storage dynamics

NASA Astrophysics Data System (ADS)

Czuba, Jonathan A.; Foufoula-Georgiou, Efi; Gran, Karen B.; Belmont, Patrick; Wilcock, Peter R.

2017-05-01

Understanding how sediment moves along source to sink pathways through watersheds—from hillslopes to channels and in and out of floodplains—is a fundamental problem in geomorphology. We contribute to advancing this understanding by modeling the transport and in-channel storage dynamics of bed material sediment on a river network over a 600 year time period. Specifically, we present spatiotemporal changes in bed sediment thickness along an entire river network to elucidate how river networks organize and process sediment supply. We apply our model to sand transport in the agricultural Greater Blue Earth River Basin in Minnesota. By casting the arrival of sediment to links of the network as a Poisson process, we derive analytically (under supply-limited conditions) the time-averaged probability distribution function of bed sediment thickness for each link of the river network for any spatial distribution of inputs. Under transport-limited conditions, the analytical assumptions of the Poisson arrival process are violated (due to in-channel storage dynamics) where we find large fluctuations and periodicity in the time series of bed sediment thickness. The time series of bed sediment thickness is the result of dynamics on a network in propagating, altering, and amalgamating sediment inputs in sometimes unexpected ways. One key insight gleaned from the model is that there can be a small fraction of reaches with relatively low-transport capacity within a nonequilibrium river network acting as "bottlenecks" that control sediment to downstream reaches, whereby fluctuations in bed elevation can dissociate from signals in sediment supply.

Multi-channels coupling-induced pattern transition in a tri-layer neuronal network

NASA Astrophysics Data System (ADS)

Wu, Fuqiang; Wang, Ya; Ma, Jun; Jin, Wuyin; Hobiny, Aatef

2018-03-01

Neurons in nerve system show complex electrical behaviors due to complex connection types and diversity in excitability. A tri-layer network is constructed to investigate the signal propagation and pattern formation by selecting different coupling channels between layers. Each layer is set as different states, and the local kinetics is described by Hindmarsh-Rose neuron model. By changing the number of coupling channels between layers and the state of the first layer, the collective behaviors of each layer and synchronization pattern of network are investigated. A statistical factor of synchronization on each layer is calculated. It is found that quiescent state in the second layer can be excited and disordered state in the third layer is suppressed when the first layer is controlled by a pacemaker, and the developed state is dependent on the number of coupling channels. Furthermore, the collapse in the first layer can cause breakdown of other layers in the network, and the mechanism is that disordered state in the third layer is enhanced when sampled signals from the collapsed layer can impose continuous disturbance on the next layer.

PULSE HEIGHT ANALYZER

DOEpatents

Johnstone, C.W.

1958-01-21

An anticoincidence device is described for a pair of adjacent channels of a multi-channel pulse height analyzer for preventing the lower channel from generating a count pulse in response to an input pulse when the input pulse has sufficient magnitude to reach the upper level channel. The anticoincidence circuit comprises a window amplifier, upper and lower level discriminators, and a biased-off amplifier. The output of the window amplifier is coupled to the inputs of the discriminators, the output of the upper level discriminator is connected to the resistance end of a series R-C network, the output of the lower level discriminator is coupled to the capacitance end of the R-C network, and the grid of the biased-off amplifier is coupled to the junction of the R-C network. In operation each discriminator produces a negative pulse output when the input pulse traverses its voltage setting. As a result of the connections to the R-C network, a trigger pulse will be sent to the biased-off amplifier when the incoming pulse level is sufficient to trigger only the lower level discriminator.

Performance evaluation of multi-channel wireless mesh networks with embedded systems.

PubMed

Lam, Jun Huy; Lee, Sang-Gon; Tan, Whye Kit

2012-01-01

Many commercial wireless mesh network (WMN) products are available in the marketplace with their own proprietary standards, but interoperability among the different vendors is not possible. Open source communities have their own WMN implementation in accordance with the IEEE 802.11s draft standard, Linux open80211s project and FreeBSD WMN implementation. While some studies have focused on the test bed of WMNs based on the open80211s project, none are based on the FreeBSD. In this paper, we built an embedded system using the FreeBSD WMN implementation that utilizes two channels and evaluated its performance. This implementation allows the legacy system to connect to the WMN independent of the type of platform and distributes the load between the two non-overlapping channels. One channel is used for the backhaul connection and the other one is used to connect to the stations to wireless mesh network. By using the power efficient 802.11 technology, this device can also be used as a gateway for the wireless sensor network (WSN).

Parallel multipoint recording of aligned and cultured neurons on micro channel array toward cellular network analysis.

PubMed

Tonomura, Wataru; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

2010-08-01

This paper describes an advanced Micro Channel Array (MCA) for recording electrophysiological signals of neuronal networks at multiple points simultaneously. The developed MCA is designed for neuronal network analysis which has been studied by the co-authors using the Micro Electrode Arrays (MEA) system, and employs the principles of extracellular recordings. A prerequisite for extracellular recordings with good signal-to-noise ratio is a tight contact between cells and electrodes. The MCA described herein has the following advantages. The electrodes integrated around individual micro channels are electrically isolated to enable parallel multipoint recording. Reliable clamping of a targeted cell through micro channels is expected to improve the cellular selectivity and the attachment between the cell and the electrode toward steady electrophysiological recordings. We cultured hippocampal neurons on the developed MCA. As a result, the spontaneous and evoked spike potentials could be recorded by sucking and clamping the cells at multiple points. In this paper, we describe the design and fabrication of the MCA and the successful electrophysiological recordings leading to the development of an effective cellular network analysis device.

A coupled geomorphic and ecological model of tidal marsh evolution.

PubMed

Kirwan, Matthew L; Murray, A Brad

2007-04-10

The evolution of tidal marsh platforms and interwoven channel networks cannot be addressed without treating the two-way interactions that link biological and physical processes. We have developed a 3D model of tidal marsh accretion and channel network development that couples physical sediment transport processes with vegetation biomass productivity. Tidal flow tends to cause erosion, whereas vegetation biomass, a function of bed surface depth below high tide, influences the rate of sediment deposition and slope-driven transport processes such as creek bank slumping. With a steady, moderate rise in sea level, the model builds a marsh platform and channel network with accretion rates everywhere equal to the rate of sea-level rise, meaning water depths and biological productivity remain temporally constant. An increase in the rate of sea-level rise, or a reduction in sediment supply, causes marsh-surface depths, biomass productivity, and deposition rates to increase while simultaneously causing the channel network to expand. Vegetation on the marsh platform can promote a metastable equilibrium where the platform maintains elevation relative to a rapidly rising sea level, although disturbance to vegetation could cause irreversible loss of marsh habitat.

Channel Access in Erlang

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicklaus, Dennis J.

2013-10-13

We have developed an Erlang language implementation of the Channel Access protocol. Included are low-level functions for encoding and decoding Channel Access protocol network packets as well as higher level functions for monitoring or setting EPICS process variables. This provides access to EPICS process variables for the Fermilab Acnet control system via our Erlang-based front-end architecture without having to interface to C/C++ programs and libraries. Erlang is a functional programming language originally developed for real-time telecommunications applications. Its network programming features and list management functions make it particularly well-suited for the task of managing multiple Channel Access circuits and PVmore » monitors.« less

Denitrification in the Mississippi River network controlled by flow through river bedforms

USGS Publications Warehouse

Gomez-Velez, Jesus D.; Harvey, Judson W.; Cardenas, M. Bayani; Kiel, Brian

2015-01-01

Increasing nitrogen concentrations in the world’s major rivers have led to over-fertilization of sensitive downstream waters1, 2, 3, 4. Flow through channel bed and bank sediments acts to remove riverine nitrogen through microbe-mediated denitrification reactions5, 6, 7, 8, 9, 10. However, little is understood about where in the channel network this biophysical process is most efficient, why certain channels are more effective nitrogen reactors, and how management practices can enhance the removal of nitrogen in regions where water circulates through sediment and mixes with groundwater - hyporheic zones8, 11, 12. Here we present numerical simulations of hyporheic flow and denitrification throughout the Mississippi River network using a hydrogeomorphic model. We find that vertical exchange with sediments beneath the riverbed in hyporheic zones, driven by submerged bedforms, has denitrification potential that far exceeds lateral hyporheic exchange with sediments alongside river channels, driven by river bars and meandering banks. We propose that geomorphic differences along river corridors can explain why denitrification efficiency varies between basins in the Mississippi River network. Our findings suggest that promoting the development of permeable bedforms at the streambed - and thus vertical hyporheic exchange - would be more effective at enhancing river denitrification in large river basins than promoting lateral exchange through induced channel meandering. 

Evaluation of Dynamic Channel and Power Assignment for Cognitive Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syed A. Ahmad; Umesh Shukla; Ryan E. Irwin

2011-03-01

In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. We apply our evaluation method to five algorithms representative of DCPA used in literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate themore » effectiveness of the algorithms in achieving feasible link allocations in the network, as well as their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment (LICIPA) algorithm does not require cross-link gain information, has the overall lowest run time, and highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.« less

Exploring 3D optimal channel networks by multiple organizing principles

NASA Astrophysics Data System (ADS)

Mason, Emanuele; Bizzi, Simone; Cominola, Andrea; Castelletti, Andrea; Paik, Kyungrock

2017-04-01

Catchment topography and flow networks are shaped by the interactions of water and sediment across various spatial and temporal scales. The complexity of these processes hinders the development of models able to assess the validity of general principles governing such phenomena. The theory of Optimal Channel Networks (OCNs) proved that it is possible to generate drainage networks statistically comparable to those observed in nature by minimizing the energy spent by the water flowing through them. So far, the OCN theory has been developed for planar 2D domains, assuming equal energy expenditure per unit area of channel and, correspondingly, a constant slope-discharge relationship. In this work, we apply the OCN theory to 3D problems by introducing a multi-principle minimization starting from an artificial digital elevation model of pyramidal shape. The OCN theory assumption of constant slope-area relationship is relaxed and embedded into a second-order principle. The modelled 3D channel networks achieve lower total energy expenditure corresponding to 2D sub-optimal OCNs bound to specific slope-area relationships. This is the first time we are able to explore accessible 3D OCNs starting from a general DEM. By contrasting the modelled 3D OCNs and natural river networks, we found statistical similarities of two indexes, namely the area exponent index and the profile concavity index. Among the wide range of alternative and sub-optimal river networks, a minimum degree of 3D network organization is found to guarantee the indexes values within the natural range. These networks simultaneously possess topological and topographic properties of real river networks. We found a pivotal functional link between slope-area relationship and accessible sub-optimal 2D river network paths, which suggests that geological and climate conditions producing slope-area relationships in natural basins co-determine the degree of optimality of accessible network paths.

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals.

PubMed

Tsiouris, Κostas Μ; Pezoulas, Vasileios C; Zervakis, Michalis; Konitsiotis, Spiros; Koutsouris, Dimitrios D; Fotiadis, Dimitrios I

2018-05-17

The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in electrical brain activity that could declare an imminent seizure. In this work, Long Short-Term Memory (LSTM) networks are introduced in epileptic seizure prediction using EEG signals, expanding the use of deep learning algorithms with convolutional neural networks (CNN). A pre-analysis is initially performed to find the optimal architecture of the LSTM network by testing several modules and layers of memory units. Based on these results, a two-layer LSTM network is selected to evaluate seizure prediction performance using four different lengths of preictal windows, ranging from 15 min to 2 h. The LSTM model exploits a wide range of features extracted prior to classification, including time and frequency domain features, between EEG channels cross-correlation and graph theoretic features. The evaluation is performed using long-term EEG recordings from the open CHB-MIT Scalp EEG database, suggest that the proposed methodology is able to predict all 185 seizures, providing high rates of seizure prediction sensitivity and low false prediction rates (FPR) of 0.11-0.02 false alarms per hour, depending on the duration of the preictal window. The proposed LSTM-based methodology delivers a significant increase in seizure prediction performance compared to both traditional machine learning techniques and convolutional neural networks that have been previously evaluated in the literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

A demand assignment control in international business satellite communications network

NASA Astrophysics Data System (ADS)

Nohara, Mitsuo; Takeuchi, Yoshio; Takahata, Fumio; Hirata, Yasuo

An experimental system is being developed for use in an international business satellite (IBS) communications network based on demand-assignment (DA) and TDMA techniques. This paper discusses its system design, in particular from the viewpoints of a network configuration, a DA control, and a satellite channel-assignment algorithm. A satellite channel configuration is also presented along with a tradeoff study on transmission rate, HPA output power, satellite resource efficiency, service quality, and so on.

System Design for Nano-Network Communications

NASA Astrophysics Data System (ADS)

ShahMohammadian, Hoda

The potential applications of nanotechnology in a wide range of areas necessities nano-networking research. Nano-networking is a new type of networking which has emerged by applying nanotechnology to communication theory. Therefore, this dissertation presents a framework for physical layer communications in a nano-network and addresses some of the pressing unsolved challenges in designing a molecular communication system. The contribution of this dissertation is proposing well-justified models for signal propagation, noise sources, optimum receiver design and synchronization in molecular communication channels. The design of any communication system is primarily based on the signal propagation channel and noise models. Using the Brownian motion and advection molecular statistics, separate signal propagation and noise models are presented for diffusion-based and flow-based molecular communication channels. It is shown that the corrupting noise of molecular channels is uncorrelated and non-stationary with a signal dependent magnitude. The next key component of any communication system is the reception and detection process. This dissertation provides a detailed analysis of the effect of the ligand-receptor binding mechanism on the received signal, and develops the first optimal receiver design for molecular communications. The bit error rate performance of the proposed receiver is evaluated and the impact of medium motion on the receiver performance is investigated. Another important feature of any communication system is synchronization. In this dissertation, the first blind synchronization algorithm is presented for the molecular communication channels. The proposed algorithm uses a non-decision directed maximum likelihood criterion for estimating the channel delay. The Cramer-Rao lower bound is also derived and the performance of the proposed synchronization algorithm is evaluated by investigating its mean square error.

On Channel-Discontinuity-Constraint Routing in Wireless Networks☆

PubMed Central

Sankararaman, Swaminathan; Efrat, Alon; Ramasubramanian, Srinivasan; Agarwal, Pankaj K.

2011-01-01

Multi-channel wireless networks are increasingly deployed as infrastructure networks, e.g. in metro areas. Network nodes frequently employ directional antennas to improve spatial throughput. In such networks, between two nodes, it is of interest to compute a path with a channel assignment for the links such that the path and link bandwidths are the same. This is achieved when any two consecutive links are assigned different channels, termed as “Channel-Discontinuity-Constraint” (CDC). CDC-paths are also useful in TDMA systems, where, preferably, consecutive links are assigned different time-slots. In the first part of this paper, we develop a t-spanner for CDC-paths using spatial properties; a sub-network containing O(n/θ) links, for any θ > 0, such that CDC-paths increase in cost by at most a factor t = (1−2 sin (θ/2))−2. We propose a novel distributed algorithm to compute the spanner using an expected number of O(n log n) fixed-size messages. In the second part, we present a distributed algorithm to find minimum-cost CDC-paths between two nodes using O(n2) fixed-size messages, by developing an extension of Edmonds’ algorithm for minimum-cost perfect matching. In a centralized implementation, our algorithm runs in O(n2) time improving the previous best algorithm which requires O(n3) running time. Moreover, this running time improves to O(n/θ) when used in conjunction with the spanner developed. PMID:24443646

Research on two-port network of wavelet transform processor using surface acoustic wavelet devices and its application.

PubMed

Liu, Shoubing; Lu, Wenke; Zhu, Changchun

2017-11-01

The goal of this research is to study two-port network of wavelet transform processor (WTP) using surface acoustic wave (SAW) devices and its application. The motive was prompted by the inconvenience of the long research and design cycle and the huge research funding involved with traditional method in this field, which were caused by the lack of the simulation and emulation method of WTP using SAW devices. For this reason, we introduce the two-port network analysis tool, which has been widely used in the design and analysis of SAW devices with uniform interdigital transducers (IDTs). Because the admittance parameters calculation formula of the two-port network can only be used for the SAW devices with uniform IDTs, this analysis tool cannot be directly applied into the design and analysis of the processor using SAW devices, whose input interdigital transducer (IDT) is apodized weighting. Therefore, in this paper, we propose the channel segmentation method, which can convert the WTP using SAW devices into parallel channels, and also provide with the calculation formula of the number of channels, the number of finger pairs and the static capacitance of an interdigital period in each parallel channel firstly. From the parameters given above, we can calculate the admittance parameters of the two port network for each channel, so that we can obtain the admittance parameter of the two-port network of the WTP using SAW devices on the basis of the simplification rule of parallel two-port network. Through this analysis tool, not only can we get the impulse response function of the WTP using SAW devices but we can also get the matching circuit of it. Large numbers of studies show that the parameters of the two-port network obtained by this paper are consistent with those measured by network analyzer E5061A, and the impulse response function obtained by the two-port network analysis tool is also consistent with that measured by network analyzer E5061A, which can meet the accuracy requirements of the analysis of the WTP using SAW devices. Therefore the two-port network analysis tool discussed in this paper has comparatively higher theoretical and practical value. Copyright © 2017 Elsevier B.V. All rights reserved.

Channel access schemes and fiber optic configurations for integrated-services local area networks

NASA Astrophysics Data System (ADS)

Nassehi, M. Mehdi

1987-03-01

Local Area Networks are in common use for data communications and have enjoyed great success. Recently, there is a growing interest in using a single network to support many applications in addition to traditional data traffic. These additional applications introduce new requirements in terms of volume of traffic and real-time delivery of data which are not met by existing networks. To satisfy these requirements, a high-bandwidth tranmission medium, such as fiber optics, and a distributed channel access scheme for the efficient sharing of the bandwidth among the various applications are needed. As far as the throughput-delay requirements of the various application are concerned, a network structure along with a distributed channel access are proposed which incorporate appropriate scheduling policies for the transmission of outstanding messages on the network. A dynamic scheduling policy was devised which outperforms all existing policies in terms of minimizing the expected cost per message. A broadcast mechanism was devised for the efficient dissemination of all relevant information. Fiber optic technology is considered for the high-bandwidth transmisison medium.

Channel access schemes and fiber optic configurations for integrated-services local area networks. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Nassehi, M. Mehdi

1987-01-01

Local Area Networks are in common use for data communications and have enjoyed great success. Recently, there is a growing interest in using a single network to support many applications in addition to traditional data traffic. These additional applications introduce new requirements in terms of volume of traffic and real-time delivery of data which are not met by existing networks. To satisfy these requirements, a high-bandwidth tranmission medium, such as fiber optics, and a distributed channel access scheme for the efficient sharing of the bandwidth among the various applications are needed. As far as the throughput-delay requirements of the various application are concerned, a network structure along with a distributed channel access are proposed which incorporate appropriate scheduling policies for the transmission of outstanding messages on the network. A dynamic scheduling policy was devised which outperforms all existing policies in terms of minimizing the expected cost per message. A broadcast mechanism was devised for the efficient dissemination of all relevant information. Fiber optic technology is considered for the high-bandwidth transmisison medium.

Analysis of wireless sensor network topology and estimation of optimal network deployment by deterministic radio channel characterization.

PubMed

Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leire; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco

2015-02-05

One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.

Determination of well flat band condition in thin film FDSOI transistors using C-V measurement for accurate parameter extraction

NASA Astrophysics Data System (ADS)

Mohamad, B.; Leroux, C.; Reimbold, G.; Ghibaudo, G.

2018-01-01

For advanced gate stacks, effective work function (WFeff) and equivalent oxide thickness (EOT) are fundamental parameters for technology optimization. On FDSOI transistors, and contrary to the bulk technologies, while EOT can still be extracted at strong inversion from the typical gate-to-channel capacitance (Cgc), it is no longer the case for WFeff due to the disappearance of an observable flat band condition on capacitance characteristics. In this work, a new experimental method, the Cbg(VBG) characteristic, is proposed in order to extract the well flat band condition (VFB, W). This characteristic enables an accurate and direct evaluation of WFeff. Moreover, using the previous extraction of the gate oxide (tfox), and buried oxide (tbox) from typical capacitance characteristics (Cgc and Cbc), it allows the extraction of the channel thickness (tch). Furthermore, the measurement of the well flat band condition on Cbg(VBG) characteristics for two different Si and SiGe channel also proves the existence of a dipole at the SiGe/SiO2 interface.

Dispersion compensation of fiber optic communication system with direct detection using artificial neural networks (ANNs)

NASA Astrophysics Data System (ADS)

Maghrabi, Mahmoud M. T.; Kumar, Shiva; Bakr, Mohamed H.

2018-02-01

This work introduces a powerful digital nonlinear feed-forward equalizer (NFFE), exploiting multilayer artificial neural network (ANN). It mitigates impairments of optical communication systems arising due to the nonlinearity introduced by direct photo-detection. In a direct detection system, the detection process is nonlinear due to the fact that the photo-current is proportional to the absolute square of the electric field intensity. The proposed equalizer provides the most efficient computational cost with high equalization performance. Its performance is comparable to the benchmark compensation performance achieved by maximum-likelihood sequence estimator. The equalizer trains an ANN to act as a nonlinear filter whose impulse response removes the intersymbol interference (ISI) distortions of the optical channel. Owing to the proposed extensive training of the equalizer, it achieves the ultimate performance limit of any feed-forward equalizer (FFE). The performance and efficiency of the equalizer is investigated by applying it to various practical short-reach fiber optic communication system scenarios. These scenarios are extracted from practical metro/media access networks and data center applications. The obtained results show that the ANN-NFFE compensates for the received BER degradation and significantly increases the tolerance to the chromatic dispersion distortion.

Fluvial Channel Networks as Analogs for the Ridge-Forming Unit, Sinus Meridiani, Mars

NASA Technical Reports Server (NTRS)

Wilkinson, M. J.; du Bois, J. B.

2010-01-01

Fluvial models have been generally discounted as analogs for the younger layered rock units of Sinus Meridiani. A fluvial model based on the large fluvial fan provides a possibly close analog for various features of the sinuous ridges of the etched, ridge-forming unit (RFU) in particular. The close spacing of the RFU ridges, their apparently chaotic orientations, and their organization in dense networks all appear unlike classical stream channel patterns. However, drainage patterns on large fluvial fans low-angle, fluvial aggradational features, 100s of km long, documented worldwide by us provide parallels. Some large fan characteristics resemble those of classical floodplains, but many differences have been demonstrated. One major distinction relevant to the RFU is that channel landscapes of large fans can dominate large areas (1.2 million km2 in one S. American study area). We compare channel morphologies on large fans in the southern Sahara Desert with ridge patterns in Sinus Meridiani (fig 1). Stream channels are the dominant landform on large terrestrial fans: they may equate to the ubiquitous, sinuous, elongated ridges of the RFU that cover areas region wide. Networks of convergent/divergent and crossing channels may equate to similar features in the ridge networks. Downslope divergence is absent in channels of terrestrial upland erosional landscapes (fig. 1, left), whereas it is common to both large fans (fig. 1, center) and RFU ridge patterns (fig 1, right downslope defined as the regional NW slope of Sinus Meridiani). RFU ridge orientation, judged from those areas apparently devoid of impact crater control, is broadly parallel with the regional slope (arrow, fig. 1, right), as is mean orientation of major channels on large fans (arrow, fig. 1, center). High densities per unit area characterize fan channels and martian ridges reaching an order of magnitude higher than those in uplands just upstream of the terrestrial study areas fig. 1. In concert with several other regional features, these morphological similarities argue for the RFU as a possibly fluvial unit.

Improving subthreshold swing to thermionic emission limit in carbon nanotube network film-based field-effect

NASA Astrophysics Data System (ADS)

Zhao, Chenyi; Zhong, Donglai; Qiu, Chenguang; Han, Jie; Zhang, Zhiyong; Peng, Lian-Mao

2018-01-01

In this letter, we explore the vertical scaling-down behavior of carbon nanotube (CNT) network film field-effect transistors (FETs) and show that by using a high-efficiency gate insulator, we can substantially improve the subthreshold swing (SS) and its uniformity. By using an HfO2 layer with a thickness of 7.3 nm as the gate insulator, we fabricated CNT network film FETs with a long channel (>2 μm) that exhibit an SS of approximately 60 mV/dec. The preferred thickness of HfO2 as the gate insulator in a CNT network FET is between 7 nm and 10 nm, simultaneously yielding an excellent SS (<80 mV/decade) and low gate leakage. However, because of the statistical fluctuations of the network CNT channel, the lateral scaling of CNT network film-based FETs is more difficult than that of conventional FETs. Experiments suggest that excellent SS is difficult to achieve statistically in CNT network film FETs with a small channel length (smaller than the mean length of the CNTs), which eventually limits the further scaling down of this kind of CNT FET to the sub-micrometer regime.

Efficiently sphere-decodable physical layer transmission schemes for wireless storage networks

NASA Astrophysics Data System (ADS)

Lu, Hsiao-Feng Francis; Barreal, Amaro; Karpuk, David; Hollanti, Camilla

2016-12-01

Three transmission schemes over a new type of multiple-access channel (MAC) model with inter-source communication links are proposed and investigated in this paper. This new channel model is well motivated by, e.g., wireless distributed storage networks, where communication to repair a lost node takes place from helper nodes to a repairing node over a wireless channel. Since in many wireless networks nodes can come and go in an arbitrary manner, there must be an inherent capability of inter-node communication between every pair of nodes. Assuming that communication is possible between every pair of helper nodes, the newly proposed schemes are based on various smart time-sharing and relaying strategies. In other words, certain helper nodes will be regarded as relays, thereby converting the conventional uncooperative multiple-access channel to a multiple-access relay channel (MARC). The diversity-multiplexing gain tradeoff (DMT) of the system together with efficient sphere-decodability and low structural complexity in terms of the number of antennas required at each end is used as the main design objectives. While the optimal DMT for the new channel model is fully open, it is shown that the proposed schemes outperform the DMT of the simple time-sharing protocol and, in some cases, even the optimal uncooperative MAC DMT. While using a wireless distributed storage network as a motivating example throughout the paper, the MAC transmission techniques proposed here are completely general and as such applicable to any MAC communication with inter-source communication links.

Age-dependent axonal expression of potassium channel proteins during development in mouse hippocampus.

PubMed

Prüss, Harald; Grosse, Gisela; Brunk, Irene; Veh, Rüdiger W; Ahnert-Hilger, Gudrun

2010-03-01

The development of the hippocampal network requires neuronal activity, which is shaped by the differential expression and sorting of a variety of potassium channels. Parallel to their maturation, hippocampal neurons undergo a distinct development of their ion channel profile. The age-dependent dimension of ion channel occurrence is of utmost importance as it is interdependently linked to network formation. However, data regarding the exact temporal expression of potassium channels during postnatal hippocampal development are scarce. We therefore studied the expression of several voltage-gated potassium channel proteins during hippocampal development in vivo and in primary cultures, focusing on channels that were sorted to the axonal compartment. The Kv1.1, Kv1.2, Kv1.4, and Kv3.4 proteins showed a considerable temporal variation of axonal localization among neuronal subpopulations. It is possible, therefore, that hippocampal neurons possess cell type-specific mechanisms for channel compartmentalization. Thus, age-dependent axonal sorting of the potassium channel proteins offers a new approach to functionally distinguish classes of hippocampal neurons and may extend our understanding of hippocampal circuitry and memory processing.

Automatic Channel Fault Detection on a Small Animal APD-Based Digital PET Scanner

NASA Astrophysics Data System (ADS)

Charest, Jonathan; Beaudoin, Jean-François; Cadorette, Jules; Lecomte, Roger; Brunet, Charles-Antoine; Fontaine, Réjean

2014-10-01

Avalanche photodiode (APD) based positron emission tomography (PET) scanners show enhanced imaging capabilities in terms of spatial resolution and contrast due to the one to one coupling and size of individual crystal-APD detectors. However, to ensure the maximal performance, these PET scanners require proper calibration by qualified scanner operators, which can become a cumbersome task because of the huge number of channels they are made of. An intelligent system (IS) intends to alleviate this workload by enabling a diagnosis of the observational errors of the scanner. The IS can be broken down into four hierarchical blocks: parameter extraction, channel fault detection, prioritization and diagnosis. One of the main activities of the IS consists in analyzing available channel data such as: normalization coincidence counts and single count rates, crystal identification classification data, energy histograms, APD bias and noise thresholds to establish the channel health status that will be used to detect channel faults. This paper focuses on the first two blocks of the IS: parameter extraction and channel fault detection. The purpose of the parameter extraction block is to process available data on individual channels into parameters that are subsequently used by the fault detection block to generate the channel health status. To ensure extensibility, the channel fault detection block is divided into indicators representing different aspects of PET scanner performance: sensitivity, timing, crystal identification and energy. Some experiments on a 8 cm axial length LabPET scanner located at the Sherbrooke Molecular Imaging Center demonstrated an erroneous channel fault detection rate of 10% (with a 95% confidence interval (CI) of [9, 11]) which is considered tolerable. Globally, the IS achieves a channel fault detection efficiency of 96% (CI: [95, 97]), which proves that many faults can be detected automatically. Increased fault detection efficiency would be advantageous but, the achieved results would already benefit scanner operators in their maintenance task.

New method for the extraction of bulk channel mobility and flat-band voltage in junctionless transistors

NASA Astrophysics Data System (ADS)

Jeon, Dae-Young; Park, So Jeong; Mouis, Mireille; Barraud, Sylvain; Kim, Gyu-Tae; Ghibaudo, Gérard

2013-11-01

A new and simple method for the extraction of electrical parameters in junctionless transistors (JLTs) is presented. The bulk channel mobility (μbulk) and flat-band voltage (Vfb) were successfully extracted from the new method, based on a linear dependence between the inverse of transconductance squared (1/gm2) vs gate voltage in the partially depleted operation regime (Vth < Vg < Vfb). The validity of the new method is also proved by 2D numerical simulation and newly defined Maserjian's-like function for gm of JLT devices.

Design and characterization of hydrogel-based microfluidic devices with biomimetic solute transport networks

PubMed Central

Koo, Hyung-Jun

2017-01-01

Hydrogel could serve as a matrix material of new classes of solar cells and photoreactors with embedded microfluidic networks. These devices mimic the structure and function of plant leaves, which are a natural soft matter based microfluidic system. These unusual microfluidic-hydrogel devices with fluid-penetrable medium operate on the basis of convective-diffusive mechanism, where the liquid is transported between the non-connected channels via molecular permeation through the hydrogel. We define three key designs of such hydrogel devices, having linear, T-shaped, and branched channels and report results of numerical simulation of the process of their infusion with solute carried by the incoming fluid. The computational procedure takes into account both pressure-driven convection and concentration gradient-driven diffusion in the permeable gel matrix. We define the criteria for evaluation of the fluid infusion rate, uniformity, solute loss by outflow and overall performance. The T-shaped channel network was identified as the most efficient one and was improved further by investigating the effect of the channel-end secondary branches. Our parallel experimental data on the pattern of solute infusions are in excellent agreement with the simulation. These network designs can be applied to a broad range of novel microfluidic materials and soft matter devices with distributed microchannel networks. PMID:28396708

Ramification of Channel Networks Incised by Groundwater Flow

NASA Astrophysics Data System (ADS)

Yi, R. S.; Seybold, H. F.; Petroff, A. P.; Devauchelle, O.; Rothman, D.

2011-12-01

The geometry of channel networks has been a source of fascination since at least Leonardo da Vinci's time. Yet a comprehensive understanding of ramification---the mechanism of branching by which a stream network acquires its geometric complexity---remains elusive. To investigate the mechanisms of ramification and network growth, we consider channel growth driven by groundwater flow as a model system, analogous to a medical scientist's laboratory rat. We test our theoretical predictions through analysis of a particularly compelling example found on the Florida Panhandle north of Bristol. As our ultimate goal is to understand ramification and growth dynamics of the entire network, we build a computational model based on the following growth hypothesis: Channels grow in the direction that captures the maximum water flux. When there are two such directions, tips bifurcate. The direction of growth can be determined from the expansion of the ground water field around each tip, where each coefficient in this expansion has a physical interpretation. The first coefficient in the expansion determines the ground water discharge, leading to a straight growth of the channel. The second term describes the asymmetry in the water field leading to a bending of the stream in the direction of maximal water flux. The ratio between the first and the third coefficient determines a critical distance rc over which the tip feels inhomogeneities in the ground water table. This initiates then the splitting of the tip. In order to test our growth hypothesis and to determine rc, we grow the Florida network backward. At each time step we calculate the solution of the ground water field and determine the appropriate expansion coefficients around each tip. Comparing this simulation result to the predicted values provides us with a stringent measure for rc and the significance of our growth hypothesis.

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

Impact of the intermixed phase and the channel network on the carrier mobility of nanostructured solar cells

NASA Astrophysics Data System (ADS)

Woellner, Cristiano F.; Freire, José A.

2016-02-01

We analyzed the impact of the complex channel network of donor and acceptor domains in nanostructured solar cells on the mobility of the charge carriers moving by thermally activated hopping. Particular attention was given to the so called intermixed phase, or interface roughness, that has recently been shown to promote an increase in the cell efficiency. The domains were obtained from a Monte Carlo simulation of a two-species lattice gas. We generated domain morphologies with controllable channel size and interface roughness. The field and density dependence of the carrier hopping mobility in different morphologies was obtained by solving a master equation. Our results show that the mobility decreases with roughness and increases with typical channel sizes. The deleterious effect of the roughness on the mobility is quite dramatic at low carrier densities and high fields. The complex channel network is shown to be directly responsible for two potentially harmful effects to the cell performance: a remarkable decrease of the mobility with increasing field and the accumulation of charge at the domains interface, which leads to recombination losses.

Changes to channel sediments resulting from complex human impacts in a gravel-bed river, Polish Carpathians

NASA Astrophysics Data System (ADS)

Zawiejska, Joanna; Wyżga, Bartłomiej; Hajdukiewicz, Hanna; Radecki-Pawlik, Artur; Mikuś, Paweł

2016-04-01

During the second half of the twentieth century, many sections of the Czarny Dunajec River, Polish Carpathians, were considerably modified by channelization as well as gravel-mining and the resultant channel incision (up to 3.5 m). This paper examines changes to the longitudinal pattern of grain size and sorting of bed material in an 18-km-long river reach. Surface bed-material grain size was established on 47 gravel bars and compared with a reference downstream fining trend of bar sediments derived from the sites with average river width and a vertically stable channel. Contrary to expectations, the extraction of cobbles from the channel bed in the upper part of the study reach, conducted in the past decades, has resulted in the marked coarsening of bed material in this river section. The extraction facilitated entrainment of exposed finer grains and has led to rapid bed degradation, whereas the concentration of flood flows in the increasingly deep and narrow channel has increased their competence and enabled a delivery of the coarse particles previously typical of the upstream reach. The middle section of the study reach, channelized to prevent sediment delivery to a downstream reservoir, now transfers the bed material flushed out from the incising upstream section. With considerably increased transport capacity of the river and with sediment delivery from bank erosion eliminated by bank reinforcements, bar sediments in the channelized section are typified by increased size of the finer fraction and better-than-average sorting. In the wide, multi-thread channel in the lower part of the reach, low unit stream power and high channel-form roughness facilitate sediment deposition and are reflected in relatively fine grades of bar gravels. The study showed that selective extraction of larger particles from the channel bed leads to channel incision at and upstream of the mining site. However, unlike bulk gravel mining, selective extraction does not result in sediment deficit downstream as large volumes of finer bed material are flushed out from the incising channel section. Grain-size analyses of bulk gravels and measurements of 100 coarsest particles within the channel sediment ranging in age from 5200 years BP to the present, performed in this deeply incised section, indicated that grain size of channel sediments changed relatively little since mid-Holocene to the 1960s, but has increased rapidly over the last half-century as a result of human interventions and rapidly progressing channel incision. This study was performed within the scope of the Research Project DEC-2013/09/B/ST10/00056 financed by the National Science Centre of Poland.

Flow regulation in the Swiss Alps: a river network modelling approach to investigate the impacts on bed load and grain size distribution

NASA Astrophysics Data System (ADS)

Costa, A.; Molnar, P.; Schmitt, R. J. P.

2017-12-01

The grain size distribution (GSD) of river bed sediment results from the long term balance between transport capacity and sediment supply. Changes in climate and human activities may alter the spatial distribution of transport capacity and sediment supply along channels and hence impact local bedload transport and GSD. The effects of changed flow are not easily inferable due the non-linear, threshold-based nature of the relation between discharge and sediment mobilization, and the network-scale control on local sediment supply. We present a network-scale model for fractional sediment transport to quantify the impact of hydropower (HP) operations on river network GSD. We represent the river network as a series of connected links for which we extract the geometric characteristics from satellite images and a digital elevation model. We assign surface roughness based on the channel bed GSD. Bed shear stress is estimated at link-scale under the assumptions of rectangular prismatic cross sections and normal flow. The mass balance between sediment supply and transport capacity, computed with the Wilcock and Crowe model, determines transport rates of multiple grain size classes and the resulting GSD. We apply the model to the upper Rhone basin, a large Alpine basin in Switzerland. Since 1960s, changed flow conditions due to HP operations and sediment storage behind dams have potentially altered the sediment transport of the basin. However, little is known on the magnitude and spatial distribution of these changes. We force the model with time series of daily discharge derived with a spatially distributed hydrological model for pre and post HP scenarios. We initialize GSD under the assumption that coarse grains (d90) are mobilized only during mean annual maximum flows, and on the basis of ratios between d90 and characteristic diameters estimated from field measurements. Results show that effects of flow regulation vary significantly in space and in time and are grain size dependent. HP operations led to an overall reduction of sediment transport at network scale, especially in summer and for coarser grains, leading to a general coarsening of the river bed sediments at the upstream reaches. The model allows investigating the impact of modified HP operations and climate change projections on sediment dynamics at the network scale.

An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks.

PubMed

Hao, Kun; Jin, Zhigang; Shen, Haifeng; Wang, Ying

2015-05-28

Efficient routing protocols for data packet delivery are crucial to underwater sensor networks (UWSNs). However, communication in UWSNs is a challenging task because of the characteristics of the acoustic channel. Network coding is a promising technique for efficient data packet delivery thanks to the broadcast nature of acoustic channels and the relatively high computation capabilities of the sensor nodes. In this work, we present GPNC, a novel geographic routing protocol for UWSNs that incorporates partial network coding to encode data packets and uses sensor nodes' location information to greedily forward data packets to sink nodes. GPNC can effectively reduce network delays and retransmissions of redundant packets causing additional network energy consumption. Simulation results show that GPNC can significantly improve network throughput and packet delivery ratio, while reducing energy consumption and network latency when compared with other routing protocols.

A Mobile Satellite Experiment (MSAT-X) network definition

NASA Technical Reports Server (NTRS)

Wang, Charles C.; Yan, Tsun-Yee

1990-01-01

The network architecture development of the Mobile Satellite Experiment (MSAT-X) project for the past few years is described. The results and findings of the network research activities carried out under the MSAT-X project are summarized. A framework is presented upon which the Mobile Satellite Systems (MSSs) operator can design a commercial network. A sample network configuration and its capability are also included under the projected scenario. The Communication Interconnection aspect of the MSAT-X network is discussed. In the MSAT-X network structure two basic protocols are presented: the channel access protocol, and the link connection protocol. The error-control techniques used in the MSAT-X project and the packet structure are also discussed. A description of two testbeds developed for experimentally simulating the channel access protocol and link control protocol, respectively, is presented. A sample network configuration and some future network activities of the MSAT-X project are also presented.

The Deep Space Network: A Radio Communications Instrument for Deep Space Exploration

NASA Technical Reports Server (NTRS)

Renzetti, N. A.; Stelzried, C. T.; Noreen, G. K.; Slobin, S. D.; Petty, S. M.; Trowbridge, D. L.; Donnelly, H.; Kinman, P. W.; Armstrong, J. W.; Burow, N. A.

1983-01-01

The primary purpose of the Deep Space Network (DSN) is to serve as a communications instrument for deep space exploration, providing communications between the spacecraft and the ground facilities. The uplink communications channel provides instructions or commands to the spacecraft. The downlink communications channel provides command verification and spacecraft engineering and science instrument payload data.

Valley segments, stream reaches, and channel units [Chapter 2

Treesearch

Peter A. Bisson; David R. Montgomery; John M. Buffington

2006-01-01

Valley segments, stream reaches, and channel units are three hierarchically nested subdivisions of the drainage network (Frissell et al. 1986), falling in size between landscapes and watersheds (see Chapter 1) and individual point measurements made along the stream network (Table 2.1; also see Chapters 3 and 4). These three subdivisions compose the habitat for large,...

A 16-Channel Distributed-Feedback Laser Array with a Monolithic Integrated Arrayed Waveguide Grating Multiplexer for a Wavelength Division Multiplex-Passive Optical Network System Network

NASA Astrophysics Data System (ADS)

Zhao, Jian-Yi; Chen, Xin; Zhou, Ning; Huang, Xiao-Dong; Cao, Ming-De; Liu, Wen

2014-07-01

A 16-channel distributed-feedback (DFB) laser array with a monolithic integrated arrayed waveguide grating multiplexer for a wavelength division multiplex-passive optical network system is fabricated by using the butt-joint metal organic chemical vapor deposition technology and nanoimpirnt technology. The results show that the threshold current is about 20-30 mA at 25°C. The DFB laser side output power is about 16 mW with a 150 mA injection current. The lasing wavelength is from 1550 nm to 1575 nm covering a more than 25 nm range with 200 GHz channel space. A more than 55 dB sidemode suppression ratio is obtained.

NEFI: Network Extraction From Images

PubMed Central

Dirnberger, M.; Kehl, T.; Neumann, A.

2015-01-01

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de. PMID:26521675

Target recognition based on convolutional neural network

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

2017-11-01

One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

Bidirectional ultradense WDM for metro networks adopting the beat-frequency-locking method

NASA Astrophysics Data System (ADS)

Kim, Sang-Yuep; Lee, Jae-Hoon; Lee, Jae-Seung

2003-10-01

We present a technique to increase the spectral efficiencies of metro networks by using channel-interleaved bidirectional ultradense wavelength-division multiplexing (WDM) within each customer's optical band. As a demonstration, we transmit 12.5-GHz-spaced 8×10 Gbit/s channels achieving spectral efficiency as high as 0.8 bit/s/Hz with a 25-GHz WDM demultiplexer. The beat-frequency-locking method is used to stabilize the channel frequencies within +/-200 MHz, which is far more accurate than with conventional wavelength lockers.

Role of groundwater in formation of Martian channels

NASA Technical Reports Server (NTRS)

Howard, Alan D.

1991-01-01

A global 3-D model of groundwater flow has been used to study possible behavior of groundwater on Mars and its role in creating fluvial features. Conclusions drawn from an earlier 2-D groundwater model are supplemented and expanded. Topical headings are discussed as follows: timescales of groundwater flow; wet areas on Mars and location of outflow channels; implications for valley networks; the enigma of Hellas; absence of fluvial or periglacial features on Syrtis Major; development of chaotic terrain and associated outflow channels; and structurally controlled valley networks.

Report on Physics of Channelization: Theory, Experiment, and Observation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kudrolli, Arshad

2014-05-19

The project involved a study of physical processes that create eroded channel and drainage networks. A particular focus was on how the shape of the channels and the network depended on the nature of the fluid flow. Our approach was to combine theoretical, experimental, and observational studies in close collaboration with Professor Daniel Rothman of the Massachusetts Institute of Technology. Laboratory -scaled experiments were developed and quantitative data on the shape of the pattern and erosion dynamics are obtained with a laser-aided topography technique and fluorescent optical imaging techniques.

Microfabrication of channel arrays promotes vessel-like network formation in cardiac cell construct and vascularization in vivo.

PubMed

Zieber, Liran; Or, Shira; Ruvinov, Emil; Cohen, Smadar

2014-06-01

Pre-vascularization is important for the reconstruction of dense and metabolically active myocardial tissue and its integration with the host myocardium after implantation. Herein, we demonstrate that the fabrication of micro-channels in alginate scaffold combined with the presentation of adhesion peptides and an angiogenic growth factor promote vessel-like networks in the construct, both in vitro and in vivo. Using a CO2 laser engraving system, 200 µm diameter channels were formed from top to bottom of the 2 mm thick alginate scaffold, with a channel-to-channel distance of 400 µm. Cells were seeded in a sequential manner onto the scaffolds: first, human umbilical vascular endothelial cells (HUVECs) were seeded and cultured for three days, then neonatal rat cardiomyocytes (CMs) and cardiofibroblasts were added at a final cell ratio of 50:35:15, respectively, and the constructs were cultivated for an additional seven days. A vessel-like network was formed within the cell constructs, wherein HUVECs were organized around the channels in a multilayer manner, while the CMs were located in-between the channels and exhibited the characteristic morphological features of a mature cardiac fiber. Acellular scaffolds with the affinity-bound basic fibroblast growth factor were implanted subcutaneously in mice. Increased cell penetration into the channeled scaffold and greater vessel density were found in comparison with the nonchanneled scaffolds. Our results thus point to the importance of micro-channels as a major structural promoter of vascularization in scaffolds, in conjunction with the sequential preculture of ECs and angiogenic factor presentation.

Automatic River Network Extraction from LIDAR Data

NASA Astrophysics Data System (ADS)

Maderal, E. N.; Valcarcel, N.; Delgado, J.; Sevilla, C.; Ojeda, J. C.

2016-06-01

National Geographic Institute of Spain (IGN-ES) has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI) within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network) and hydrological criteria (flow accumulation river network), and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files), and process; using local virtualization and the Amazon Web Service (AWS), which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri) and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.

Communication and cooperation in underwater acoustic networks

NASA Astrophysics Data System (ADS)

Yerramalli, Srinivas

In this thesis, we present a study of several problems related to underwater point to point communications and network formation. We explore techniques to improve the achievable data rate on a point to point link using better physical layer techniques and then study sensor cooperation which improves the throughput and reliability in an underwater network. Robust point-to-point communications in underwater networks has become increasingly critical in several military and civilian applications related to underwater communications. We present several physical layer signaling and detection techniques tailored to the underwater channel model to improve the reliability of data detection. First, a simplified underwater channel model in which the time scale distortion on each path is assumed to be the same (single scale channel model in contrast to a more general multi scale model). A novel technique, which exploits the nature of OFDM signaling and the time scale distortion, called Partial FFT Demodulation is derived. It is observed that this new technique has some unique interference suppression properties and performs better than traditional equalizers in several scenarios of interest. Next, we consider the multi scale model for the underwater channel and assume that single scale processing is performed at the receiver. We then derive optimized front end pre-processing techniques to reduce the interference caused during single scale processing of signals transmitted on a multi-scale channel. We then propose an improvised channel estimation technique using dictionary optimization methods for compressive sensing and show that significant performance gains can be obtained using this technique. In the next part of this thesis, we consider the problem of sensor node cooperation among rational nodes whose objective is to improve their individual data rates. We first consider the problem of transmitter cooperation in a multiple access channel and investigate the stability of the grand coalition of transmitters using tools from cooperative game theory and show that the grand coalition in both the asymptotic regimes of high and low SNR. Towards studying the problem of receiver cooperation for a broadcast channel, we propose a game theoretic model for the broadcast channel and then derive a game theoretic duality between the multiple access and the broadcast channel and show that how the equilibria of the broadcast channel are related to the multiple access channel and vice versa.

The sinuous ridge and channel network within Rahway Vallis and the wider contextual study of the surrounding Rahway Basin, Mars.

NASA Astrophysics Data System (ADS)

Ramsdale, Jason; Balme, Matthew; Conway, Susan; Gallagher, Colman

2014-05-01

Rahway Vallis is a previously identified shallow v-shaped valley network in the Mars Orbiter Laser Altimeter data, located at 10°N 175°E, within the Cerberus Plains in the Elysium Planitia region of Mars. Rahway Vallis is situated in low-lying terrain bounded to west, north and east by older highlands, and to the south by the flood-carved channel system Marte Vallis. Here we present a study of the low-lying area in which Rahway Vallis sits, which we refer to as the "Rahway basin". The floor of the Rahway basin is extremely flat (sloping at 0.02° south-east) and hosts a branching network of ridge and channel systems. The aim of this project is to determine the genesis of these branching forms, in particular to test the hypothesis that they are glaciofluvial in origin. Using topographic cross-profiles of the channels that are identifiable in CTX 6 m/pixel images, we have found that they are set within broader v-shaped valley that has almost no morphological expression. These valleys have a convex-up, shallow (around 15 metres vertically compared to several kilometres in the horizontal) V-shaped profiles that are consistent in form across the whole Rahway Basin. Long profiles show the channels to deepen with respect to the bank height downslope. Both channels and valley show a consistent downhill gradient from west to east. The channels typically widen down-slope and increase in width at confluences. If these are water-cut channels, they reach Strahler stream orders of 4, consistent with a contributory network with multiple sources. Associated with the channels are sinuous ridges, typically several kilometres long, 20 m across, with heights on the order of 10 m. They sometimes form branching networks leading into the channels but also form individually and parallel to the channels. Possible explanations for the sinuous ridges include inverted fluvial channels and eskers. However despite looking through ca. 250 CTX images across the Rahway basin, no other glacial landform was identified. This makes the esker hypothesis unlikely. We have found that the transition between the older heavily cratered highland terrain and the floor of the Rahway basin is often bounded by near-horizontal topographic terraces. These terraces appear continuous around the basin margin and are present in almost all locations where 6m/pixel resolution CTX images are available. These steps are at altitudes between -3108 m and -2620 m with a mean of -3000 m above the Mars datum and have a standard deviation of 68.7 metres. These properties suggest that the terraces could represent the palaeo-shorelines of a drained/evaporated standing body of water. A since drained standing body of water is consistent with the hypothesis that the channels and ridges are fluvial and inverted fluvial channels respectively.

Role of partial linear momentum transfer on incomplete fusion reaction

NASA Astrophysics Data System (ADS)

Ali, Sabir; Ahmad, Tauseef; Kumar, Kamal; Gull, Muntazir; Rizvi, I. A.; Agarwal, Avinash; Ghugre, S. S.; Sinha, A. K.; Chaubey, A. K.

2018-04-01

Measurements of forward recoil range distributions (FRRDs) of the evaporation residues, populated in the 20Ne+51V reaction at E_{lab}≈ 145 MeV, have been carried out using the offline characteristic γ-ray detection method. The observation does corroborate the presence of complete fusion (CF) process in the population of p xn channel residues and both complete as well as incomplete fusion (ICF) processes in the population of α emitting channel residues. The FRRDs of p xn channel residues comprise single peak only, whereas α emitting channel residues have multiple peaks in their FRRDs. CF cross section data were used to extract the fusion functions. Extracted fusion functions were found to be suppressed with respect to the universal fusion function which is used as a uniform standard reference. The observed contribution arising from the ICF process in the population of α emitting channel residues is explained in terms of breakup fusion model.

Queuing theory models for computer networks

NASA Technical Reports Server (NTRS)

Galant, David C.

1989-01-01

A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.

The Influence of Cold Temperature on Cellular Excitability of Hippocampal Networks

PubMed Central

Vara, Hugo; Caires, Rebeca; Ballesta, Juan J.; Belmonte, Carlos; Viana, Felix

2012-01-01

The hippocampus plays an important role in short term memory, learning and spatial navigation. A characteristic feature of the hippocampal region is its expression of different electrical population rhythms and activities during different brain states. Physiological fluctuations in brain temperature affect the activity patterns in hippocampus, but the underlying cellular mechanisms are poorly understood. In this work, we investigated the thermal modulation of hippocampal activity at the cellular network level. Primary cell cultures of mouse E17 hippocampus displayed robust network activation upon light cooling of the extracellular solution from baseline physiological temperatures. The activity generated was dependent on action potential firing and excitatory glutamatergic synaptic transmission. Involvement of thermosensitive channels from the transient receptor potential (TRP) family in network activation by temperature changes was ruled out, whereas pharmacological and immunochemical experiments strongly pointed towards the involvement of temperature-sensitive two-pore-domain potassium channels (K2P), TREK/TRAAK family. In hippocampal slices we could show an increase in evoked and spontaneous synaptic activity produced by mild cooling in the physiological range that was prevented by chloroform, a K2P channel opener. We propose that cold-induced closure of background TREK/TRAAK family channels increases the excitability of some hippocampal neurons, acting as a temperature-sensitive gate of network activation. Our findings in the hippocampus open the possibility that small temperature variations in the brain in vivo, associated with metabolism or blood flow oscillations, act as a switch mechanism of neuronal activity and determination of firing patterns through regulation of thermosensitive background potassium channel activity. PMID:23300680

Establishing a Multi-scale Stream Gaging Network in the Whitewater River Basin, Kansas, USA

USGS Publications Warehouse

Clayton, J.A.; Kean, J.W.

2010-01-01

Investigating the routing of streamflow through a large drainage basin requires the determination of discharge at numerous locations in the channel network. Establishing a dense network of stream gages using conventional methods is both cost-prohibitive and functionally impractical for many research projects. We employ herein a previously tested, fluid-mechanically based model for generating rating curves to establish a stream gaging network in the Whitewater River basin in south-central Kansas. The model was developed for the type of channels typically found in this watershed, meaning that it is designed to handle deep, narrow geomorphically stable channels with irregular planforms, and can model overbank flow over a vegetated floodplain. We applied the model to ten previously ungaged stream reaches in the basin, ranging from third- to sixth-order channels. At each site, detailed field measurements of the channel and floodplain morphology, bed and bank roughness, and vegetation characteristics were used to quantify the roughness for a range of flow stages, from low flow to overbank flooding. Rating curves that relate stage to discharge were developed for all ten sites. Both fieldwork and modeling were completed in less than 2 years during an anomalously dry period in the region, which underscores an advantage of using theoretically based (as opposed to empirically based) discharge estimation techniques. ?? 2010 Springer Science+Business Media B.V.

Concurrent Transmission Based on Channel Quality in Ad Hoc Networks: A Game Theoretic Approach

NASA Astrophysics Data System (ADS)

Chen, Chen; Gao, Xinbo; Li, Xiaoji; Pei, Qingqi

In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

PubMed Central

2014-01-01

In order to overcome the shortcomings of existing medium access control (MAC) protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA) technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC) scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS) requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD) and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput. PMID:25126592

Finite-SNR analysis for partial relaying cooperation with channel coding and opportunistic relay selection

NASA Astrophysics Data System (ADS)

Vu, Thang X.; Duhamel, Pierre; Chatzinotas, Symeon; Ottersten, Bjorn

2017-12-01

This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple relays, and one destination. To achieve high spectral efficiency, we assume that a single time slot is dedicated to relaying. Conventional network-coded-based cooperation (NCC) selects the best relay which uses network coding to serve the two sources simultaneously. The bit error rate (BER) performance of NCC with channel coding, however, is still unknown. In this paper, we firstly study the BER of NCC via a closed-form expression and analytically show that NCC only achieves diversity of order two regardless of the number of available relays and the channel code. Secondly, we propose a novel partial relaying-based cooperation (PARC) scheme to improve the system diversity in the finite signal-to-noise ratio (SNR) regime. In particular, closed-form expressions for the system BER and diversity order of PARC are derived as a function of the operating SNR value and the minimum distance of the channel code. We analytically show that the proposed PARC achieves full (instantaneous) diversity order in the finite SNR regime, given that an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR gain of PARC over NCC in the SNR region of interest.

Independent and cooperative motions of the Kv1.2 channel: voltage sensing and gating.

PubMed

Yeheskel, Adva; Haliloglu, Turkan; Ben-Tal, Nir

2010-05-19

Voltage-gated potassium (Kv) channels, such as Kv1.2, are involved in the generation and propagation of action potentials. The Kv channel is a homotetramer, and each monomer is composed of a voltage-sensing domain (VSD) and a pore domain (PD). We analyzed the fluctuations of a model structure of Kv1.2 using elastic network models. The analysis suggested a network of coupled fluctuations of eight rigid structural units and seven hinges that may control the transition between the active and inactive states of the channel. For the most part, the network is composed of amino acids that are known to affect channel activity. The results suggested allosteric interactions and cooperativity between the subunits in the coupling between the motion of the VSD and the selectivity filter of the PD, in accordance with recent empirical data. There are no direct contacts between the VSDs of the four subunits, and the contacts between these and the PDs are loose, suggesting that the VSDs are capable of functioning independently. Indeed, they manifest many inherent fluctuations that are decoupled from the rest of the structure. In general, the analysis suggests that the two domains contribute to the channel function both individually and cooperatively. Copyright 2010 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Neural network explanation using inversion.

PubMed

Saad, Emad W; Wunsch, Donald C

2007-01-01

An important drawback of many artificial neural networks (ANN) is their lack of explanation capability [Andrews, R., Diederich, J., & Tickle, A. B. (1996). A survey and critique of techniques for extracting rules from trained artificial neural networks. Knowledge-Based Systems, 8, 373-389]. This paper starts with a survey of algorithms which attempt to explain the ANN output. We then present HYPINV, a new explanation algorithm which relies on network inversion; i.e. calculating the ANN input which produces a desired output. HYPINV is a pedagogical algorithm, that extracts rules, in the form of hyperplanes. It is able to generate rules with arbitrarily desired fidelity, maintaining a fidelity-complexity tradeoff. To our knowledge, HYPINV is the only pedagogical rule extraction method, which extracts hyperplane rules from continuous or binary attribute neural networks. Different network inversion techniques, involving gradient descent as well as an evolutionary algorithm, are presented. An information theoretic treatment of rule extraction is presented. HYPINV is applied to example synthetic problems, to a real aerospace problem, and compared with similar algorithms using benchmark problems.

Emotion recognition from EEG using higher order crossings.

PubMed

Petrantonakis, Panagiotis C; Hadjileontiadis, Leontios J

2010-03-01

Electroencephalogram (EEG)-based emotion recognition is a relatively new field in the affective computing area with challenging issues regarding the induction of the emotional states and the extraction of the features in order to achieve optimum classification performance. In this paper, a novel emotion evocation and EEG-based feature extraction technique is presented. In particular, the mirror neuron system concept was adapted to efficiently foster emotion induction by the process of imitation. In addition, higher order crossings (HOC) analysis was employed for the feature extraction scheme and a robust classification method, namely HOC-emotion classifier (HOC-EC), was implemented testing four different classifiers [quadratic discriminant analysis (QDA), k-nearest neighbor, Mahalanobis distance, and support vector machines (SVMs)], in order to accomplish efficient emotion recognition. Through a series of facial expression image projection, EEG data have been collected by 16 healthy subjects using only 3 EEG channels, namely Fp1, Fp2, and a bipolar channel of F3 and F4 positions according to 10-20 system. Two scenarios were examined using EEG data from a single-channel and from combined-channels, respectively. Compared with other feature extraction methods, HOC-EC appears to outperform them, achieving a 62.3% (using QDA) and 83.33% (using SVM) classification accuracy for the single-channel and combined-channel cases, respectively, differentiating among the six basic emotions, i.e., happiness, surprise, anger, fear, disgust, and sadness. As the emotion class-set reduces its dimension, the HOC-EC converges toward maximum classification rate (100% for five or less emotions), justifying the efficiency of the proposed approach. This could facilitate the integration of HOC-EC in human machine interfaces, such as pervasive healthcare systems, enhancing their affective character and providing information about the user's emotional status (e.g., identifying user's emotion experiences, recurring affective states, time-dependent emotional trends).

Entropy and optimality in river deltas

NASA Astrophysics Data System (ADS)

Tejedor, Alejandro; Longjas, Anthony; Edmonds, Douglas A.; Zaliapin, Ilya; Georgiou, Tryphon T.; Rinaldo, Andrea; Foufoula-Georgiou, Efi

2017-10-01

The form and function of river deltas is intricately linked to the evolving structure of their channel networks, which controls how effectively deltas are nourished with sediments and nutrients. Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. To date, however, a unified theory explaining how deltas self-organize to distribute water and sediment up to the shoreline remains elusive. Here, we provide evidence for an optimality principle underlying the self-organized partition of fluxes in delta channel networks. By introducing a suitable nonlocal entropy rate (nER) and by analyzing field and simulated deltas, we suggest that delta networks achieve configurations that maximize the diversity of water and sediment flux delivery to the shoreline. We thus suggest that prograding deltas attain dynamically accessible optima of flux distributions on their channel network topologies, thus effectively decoupling evolutionary time scales of geomorphology and hydrology. When interpreted in terms of delta resilience, high nER configurations reflect an increased ability to withstand perturbations. However, the distributive mechanism responsible for both diversifying flux delivery to the shoreline and dampening possible perturbations might lead to catastrophic events when those perturbations exceed certain intensity thresholds.

Vitex negundo induces an anticonvulsant effect by inhibiting voltage gated sodium channels in murine Neuro 2A cell line.

PubMed

Khan, Faisal; Saify, Zafar Saeed; Jamali, Khawar Saeed; Naz, Saima; Hassan, Sohail; Siddiqui, Sonia

2018-01-01

Vitex negundo (Vn) extract is famous for the treatment of neurological diseases such as migraine and epilepsy. These neurological diseases have been associated with abnormally increased influx of sodium ions into the neurons. Drugs that inhibit voltage gated sodium channels can be used as potent anti-epileptics. Till now, the effects of Vn on sodium channels have not been investigated. Therefore, we have investigated the effects of methalonic fraction of Vn extract in Murine Neuro 2A cell line. Cells were cultured in a defined medium with or without the Vn extract (100 μg/ml). Sodium currents were recorded using whole-cell patch clamp method. The data show that methanolic extract of Vn inhibited sodium currents in a dose dependent manner (IC50 =161μg/ml). Vn (100 μg/ml) shifted the steady-state inactivation curve to the left or towards the hyper polarization state. However, Vn did not show any effects on outward rectifying potassium currents. Moreover, Vn (100 μg/ml) significantly reduced the sustained repetitive (48±4.8%, P<0.01) firing from neonatal hippocampal neurons at 12 DIV. Hence, our data suggested that inhibition of sodium channels by Vn may exert pharmacological effects in reducing pain and convulsions.

A modeling study of tidal energy extraction and the associated impact on tidal circulation in a multi-inlet bay system of Puget Sound

DOE PAGES

Wang, Taiping; Yang, Zhaoqing

2017-03-25

Previously, a major focus of tidal energy studies in Puget Sound were the deep channels such as Admiralty Inlet that have a larger power potential. Our paper focuses on the possibility of extracting tidal energy from minor tidal channels of Puget Sound by using a hydrodynamic model to quantify the power potential and the associated impact on tidal circulation. The study site is a multi-inlet bay system connected by two narrow inlets, Agate Pass and Rich Passage, to the Main Basin of Puget Sound. A three-dimensional hydrodynamic model was applied to the study site and validated for tidal elevations andmore » currents. Here, we examined three energy extraction scenarios in which turbines were deployed in each of the two passages and concurrently in both. Extracted power rates and associated changes in tidal elevation, current, tidal flux, and residence time were examined. Maximum instantaneous power rates reached 250 kW, 1550 kW, and 1800 kW, respectively, for the three energy extraction scenarios. Model results suggest that with the level of energy extraction in the three energy extraction scenarios, the impact on tidal circulation is very small. It is worth investigating the feasibility of harnessing tidal energy from minor tidal channels of Puget Sound.« less

A modeling study of tidal energy extraction and the associated impact on tidal circulation in a multi-inlet bay system of Puget Sound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Taiping; Yang, Zhaoqing

Previously, a major focus of tidal energy studies in Puget Sound were the deep channels such as Admiralty Inlet that have a larger power potential. Our paper focuses on the possibility of extracting tidal energy from minor tidal channels of Puget Sound by using a hydrodynamic model to quantify the power potential and the associated impact on tidal circulation. The study site is a multi-inlet bay system connected by two narrow inlets, Agate Pass and Rich Passage, to the Main Basin of Puget Sound. A three-dimensional hydrodynamic model was applied to the study site and validated for tidal elevations andmore » currents. Here, we examined three energy extraction scenarios in which turbines were deployed in each of the two passages and concurrently in both. Extracted power rates and associated changes in tidal elevation, current, tidal flux, and residence time were examined. Maximum instantaneous power rates reached 250 kW, 1550 kW, and 1800 kW, respectively, for the three energy extraction scenarios. Model results suggest that with the level of energy extraction in the three energy extraction scenarios, the impact on tidal circulation is very small. It is worth investigating the feasibility of harnessing tidal energy from minor tidal channels of Puget Sound.« less

Open source system OpenVPN in a function of Virtual Private Network

NASA Astrophysics Data System (ADS)

Skendzic, A.; Kovacic, B.

2017-05-01

Using of Virtual Private Networks (VPN) can establish high security level in network communication. VPN technology enables high security networking using distributed or public network infrastructure. VPN uses different security and managing rules inside networks. It can be set up using different communication channels like Internet or separate ISP communication infrastructure. VPN private network makes security communication channel over public network between two endpoints (computers). OpenVPN is an open source software product under GNU General Public License (GPL) that can be used to establish VPN communication between two computers inside business local network over public communication infrastructure. It uses special security protocols and 256-bit Encryption and it is capable of traversing network address translators (NATs) and firewalls. It allows computers to authenticate each other using a pre-shared secret key, certificates or username and password. This work gives review of VPN technology with a special accent on OpenVPN. This paper will also give comparison and financial benefits of using open source VPN software in business environment.

Convolutional neural network for road extraction

NASA Astrophysics Data System (ADS)

Li, Junping; Ding, Yazhou; Feng, Fajie; Xiong, Baoyu; Cui, Weihong

2017-11-01

In this paper, the convolution neural network with large block input and small block output was used to extract road. To reflect the complex road characteristics in the study area, a deep convolution neural network VGG19 was conducted for road extraction. Based on the analysis of the characteristics of different sizes of input block, output block and the extraction effect, the votes of deep convolutional neural networks was used as the final road prediction. The study image was from GF-2 panchromatic and multi-spectral fusion in Yinchuan. The precision of road extraction was 91%. The experiments showed that model averaging can improve the accuracy to some extent. At the same time, this paper gave some advice about the choice of input block size and output block size.

Do distributaries in a delta plain resemble an ideal estuary? Results from theKapuas Delta,Indonesia

NASA Astrophysics Data System (ADS)

Hoitink, T.; Kastner, K.; Vermeulen, B.; Geertsema, T.; Nining, S. N.

2017-12-01

Coastal lowland plains under mixed fluvial-tidal influence can form complex channel networks, where distributaries blend the characteristics of mouth bar channels, avulsion channels and tidal creeks. These networks are shaped by the interplay of river flow and tides. Our goal is to increase the general understanding of physical processes in the fluvial-tidal transition. Here we present first results of an extensive field survey of the Kapuas river and give insight into the along channel trends of cross section geometry and bed material grain size. main distributary and slightly increases in downstream direction (Fig. 2c).The Kapuas river is a large tropical river in West Kalimantan, Indonesia. Discharge ranges between 10^3 m^3/s in the wet and 10^4 m^3/s in the dry season. The Kapuas consists of one main distributary from which three smaller distributaries branch off along the alluvial plain (Fig. 1a). Tides are mainly diurnal, with an average spring range of 1.5m at the mouth.Figure 1: Map of the Kapuas river delta plain Between 2013 and 2015 we surveyed the Kapuas from the sea to upstream km 300. Bankfull river width was extracted from Landsat images. Bathymetry was surveyed with a single beam each sounder. Bed material was sampled with a van Veen grabber. The geometry of the Kapuas river deviates from that of an idealized estuary, as it does not converge to an equilibirum width and depth. Such a break in scaling was previously found in the Mahakam Delta by Sassi et al. 2012, which suggests this may be a general characteristic in the fluvial to tidal transition. There is no simple relation between bed material grain size and channel geometry. The particular geometry of the Kapuas also leads to particular hydrodynamics in the fluvial-tidal transition. Thus the draw-down curve during high flow and backwater curve at flow are much less pronounced in the Kapuas, and tides propagate far up the river. At the moment we investigate the consequences for river discharge-tide interaction. In particular we focus on propagation of the tide depending on the river discharge as well as consequences for delta morphology.

Optical data communication: fundamentals and future directions

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.

1998-12-01

An overview of optical data communications is provided, beginning with a brief history and discussion of the unique requirements that distinguish this subfield from related areas such as telecommunications. Each of the major datacom standards is then discussed, including the physical layer specification, distances and data rates, fiber and connector types, data frame structures, and network considerations. These standards can be categorized by their prevailing applications, either storage [Enterprise System Connection, Fiber Channel Connection, and Fiber Channel], coupling (Fiber Channel), or networking [Fiber Distributed Data Interface, Gigabit Ethernet, and asynchronous transfer mode/synchronous optical network]. We also present some emerging technologies and their applications, including parallel optical interconnects, plastic optical fiber, wavelength multiplexing, and free- space optical links. We conclude with some cost/performance trade-offs and predictions of future bandwidth trends.

Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

PubMed

Elayavilli, Ravikumar Komandur; Liu, Hongfang

2016-01-01

Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological framework. The ICEPO ontology is available for download at http://openbionlp.org/mutd/supplementarydata/ICEPO/ICEPO.owl.

Research of G3-PLC net self-organization processes in the NS-3 modeling framework

NASA Astrophysics Data System (ADS)

Pospelova, Irina; Chebotayev, Pavel; Klimenko, Aleksey; Myakochin, Yuri; Polyakov, Igor; Shelupanov, Alexander; Zykov, Dmitriy

2017-11-01

When modern infocommunication networks are designed, the combination of several data transfer channels is widely used. It is necessary for the purposes of improvement in quality and robustness of communication. Communication systems based on more than one data transfer channel are named heterogeneous communication systems. For the design of a heterogeneous network, the most optimal solution is the use of mesh technology. Mesh technology ensures message delivery to the destination under conditions of unpredictable interference environment situation in each of two channels. Therewith, one of the high-priority problems is the choice of a routing protocol when the mesh networks are designed. An important design stage for any computer network is modeling. Modeling allows us to design a few different variants of design solutions and also to compute all necessary functional specifications for each of these solutions. As a result, it allows us to reduce costs for the physical realization of a network. In this article the research of dynamic routing in the NS3 simulation modeling framework is presented. The article contains an evaluation of simulation modeling applicability in solving the problem of heterogeneous networks design. Results of modeling may be afterwards used for physical realization of this kind of networks.

Cell membrane organization is important for inner hair cell MET-channel gating

NASA Astrophysics Data System (ADS)

Effertz, Thomas; Scharr, Alexandra L.; Ricci, Anthony J.

2018-05-01

Specialized sensory cells, hair cells, translate mechanical stimuli into electro/chemical responses. This process, termed mechano-electrical transduction (MET), is localized to the hair cell's sensory organelle, the hair bundle. The mature hair bundle comprises three rows of actin filled stereocilia, arranged in a staircase pattern. Deflections towards the tallest row of stereocilia activate MET channels, residing at the top of stereocilia. While other MET channels can be activated or modulated by changes to their lipid environment, this remains unknown for the mammalian auditory MET channel. We show here that the effect of lipid and cholesterol depletion from the cell membrane affect the MET current as well. We used γ-cyclodextrin to extract lipids form the membrane, reversibly reducing the peak MET current, current adaptation, and decreasing the channels resting open probability. The recovery after γ-cyclodextrin treatment was slower than the initial peak current reduction, suggesting that a specific lipid organization is required for normal MET channel function, which requires time reestablish. Extraction of cholesterol, using Mβ-cyclodextrin, irreversibly reduces the peak MET current and reversibly increases the channel resting open probability, suggesting that cholesterol restricts MET channel opening. This restriction could be useful to increase the channel's signal to noise ratio. Together this data suggests that the cell membrane is part of the force relay machinery to the MET channel and could possibly restrict gating associated conformational changes of the MET channel.

Quasi-Optical Network Analyzers and High-Reliability RF MEMS Switched Capacitors

NASA Astrophysics Data System (ADS)

Grichener, Alexander

The thesis first presents a 2-port quasi-optical scalar network analyzer consisting of a transmitter and receiver both built in planar technology. The network analyzer is based on a Schottky-diode mixer integrated inside a planar antenna and fed differentially by a CPW transmission line. The antenna is placed on an extended hemispherical high-resistivity silicon substrate lens. The LO signal is swept from 3-5 GHz and high-order harmonic mixing in both up- and down- conversion mode is used to realize the 15-50 GHz RF bandwidth. The network analyzer resulted in a dynamic range of greater than 40 dB and was successfully used to measure a frequency selective surface with a second-order bandpass response. Furthermore, the system was built with circuits and components for easy scaling to millimeter-wave frequencies which is the primary motivation for this work. The application areas for a millimeter and submillimeter-wave network analyzer include material characterization and art diagnostics. The second project presents several RF MEMS switched capacitors designed for high-reliability operation and suitable for tunable filters and reconfigurable networks. The first switched-capacitor resulted in a digital capacitance ratio of 5 and an analog capacitance ratio of 5-9. The analog tuning of the down-state capacitance is enhanced by a positive vertical stress gradient in the the beam, making it ideal for applications that require precision tuning. A thick electroplated beam resulted in Q greater than 100 at C to X-band frequencies, and power handling of 0.6-1.1 W. The design also minimized charging in the dielectric, resulting in excellent reliability performance even under hot-switched and high power (1 W) conditions. The second switched-capacitor was designed without any dielectric to minimize charging. The device was hot-switched at 1 W of RF power for greater than 11 billion cycles with virtually no change in the C-V curve. The final project presents a 7-channel channelizer based on the mammalian cochlea. The cochlea is an amazing channelizing filter, covering three decades of bandwidth with over 3,000 channels in a very small physical space. Using a simplified mechanical cochlear model and its electrical analogue, a design method is demonstrated for RF and microwave channelizers that retains the desirable features of the cochlea including the ability to cascade a large number of channels (for multiple-octave frequency coverage), and a high-order stop-band rejection. A 6-pole response is synthesized in each channel using the top-C coupled topology. A constant absolute 3 dB bandwidth of around 4.3 MHz and an insertion loss of around 3.9 dB is measured in each channel. A high isolation (greater than 35 dB) is achieved between adjacent channels. A reflection loss of greater than 15 dB is measured at the input port over the entire channelizer bandwidth. Application areas for the demonstrated channelizer include wideband, contiguous-channel receivers for signal intelligence or spectral analysis.

HealthTrust: a social network approach for retrieving online health videos.

PubMed

Fernandez-Luque, Luis; Karlsen, Randi; Melton, Genevieve B

2012-01-31

Social media are becoming mainstream in the health domain. Despite the large volume of accurate and trustworthy health information available on social media platforms, finding good-quality health information can be difficult. Misleading health information can often be popular (eg, antivaccination videos) and therefore highly rated by general search engines. We believe that community wisdom about the quality of health information can be harnessed to help create tools for retrieving good-quality social media content. To explore approaches for extracting metrics about authoritativeness in online health communities and how these metrics positively correlate with the quality of the content. We designed a metric, called HealthTrust, that estimates the trustworthiness of social media content (eg, blog posts or videos) in a health community. The HealthTrust metric calculates reputation in an online health community based on link analysis. We used the metric to retrieve YouTube videos and channels about diabetes. In two different experiments, health consumers provided 427 ratings of 17 videos and professionals gave 162 ratings of 23 videos. In addition, two professionals reviewed 30 diabetes channels. HealthTrust may be used for retrieving online videos on diabetes, since it performed better than YouTube Search in most cases. Overall, of 20 potential channels, HealthTrust's filtering allowed only 3 bad channels (15%) versus 8 (40%) on the YouTube list. Misleading and graphic videos (eg, featuring amputations) were more commonly found by YouTube Search than by searches based on HealthTrust. However, some videos from trusted sources had low HealthTrust scores, mostly from general health content providers, and therefore not highly connected in the diabetes community. When comparing video ratings from our reviewers, we found that HealthTrust achieved a positive and statistically significant correlation with professionals (Pearson r₁₀ = .65, P = .02) and a trend toward significance with health consumers (r₇ = .65, P = .06) with videos on hemoglobinA(1c), but it did not perform as well with diabetic foot videos. The trust-based metric HealthTrust showed promising results when used to retrieve diabetes content from YouTube. Our research indicates that social network analysis may be used to identify trustworthy social media in health communities.

Contact resistance extraction methods for short- and long-channel carbon nanotube field-effect transistors

NASA Astrophysics Data System (ADS)

Pacheco-Sanchez, Anibal; Claus, Martin; Mothes, Sven; Schröter, Michael

2016-11-01

Three different methods for the extraction of the contact resistance based on both the well-known transfer length method (TLM) and two variants of the Y-function method have been applied to simulation and experimental data of short- and long-channel CNTFETs. While for TLM special CNT test structures are mandatory, standard electrical device characteristics are sufficient for the Y-function methods. The methods have been applied to CNTFETs with low and high channel resistance. It turned out that the standard Y-function method fails to deliver the correct contact resistance in case of a relatively high channel resistance compared to the contact resistances. A physics-based validation is also given for the application of these methods based on applying traditional Si MOSFET theory to quasi-ballistic CNTFETs.

Chaotic mixing in three-dimensional microvascular networks fabricated by direct-write assembly.

PubMed

Therriault, Daniel; White, Scott R; Lewis, Jennifer A

2003-04-01

The creation of geometrically complex fluidic devices is a subject of broad fundamental and technological interest. Here, we demonstrate the fabrication of three-dimensional (3D) microvascular networks through direct-write assembly of a fugitive organic ink. This approach yields a pervasive network of smooth cylindrical channels (approximately 10-300 microm) with defined connectivity. Square-spiral towers, isolated within this vascular network, promote fluid mixing through chaotic advection. These vertical towers give rise to dramatic improvements in mixing relative to simple straight (1D) and square-wave (2D) channels while significantly reducing the device planar footprint. We envisage that 3D microvascular networks will provide an enabling platform for a wide array of fluidic-based applications.

Diffusion in random networks: Asymptotic properties, and numerical and engineering approximations

NASA Astrophysics Data System (ADS)

Padrino, Juan C.; Zhang, Duan Z.

2016-11-01

The ensemble phase averaging technique is applied to model mass transport by diffusion in random networks. The system consists of an ensemble of random networks, where each network is made of a set of pockets connected by tortuous channels. Inside a channel, we assume that fluid transport is governed by the one-dimensional diffusion equation. Mass balance leads to an integro-differential equation for the pores mass density. The so-called dual porosity model is found to be equivalent to the leading order approximation of the integration kernel when the diffusion time scale inside the channels is small compared to the macroscopic time scale. As a test problem, we consider the one-dimensional mass diffusion in a semi-infinite domain, whose solution is sought numerically. Because of the required time to establish the linear concentration profile inside a channel, for early times the similarity variable is xt- 1 / 4 rather than xt- 1 / 2 as in the traditional theory. This early time sub-diffusive similarity can be explained by random walk theory through the network. In addition, by applying concepts of fractional calculus, we show that, for small time, the governing equation reduces to a fractional diffusion equation with known solution. We recast this solution in terms of special functions easier to compute. Comparison of the numerical and exact solutions shows excellent agreement.

Low and High-Frequency Field Potentials of Cortical Networks ...

EPA Pesticide Factsheets

Neural networks grown on microelectrode arrays (MEAs) have become an important, high content in vitro assay for assessing neuronal function. MEA experiments typically examine high- frequency (HF) (>200 Hz) spikes, and bursts which can be used to discriminate between different pharmacological agents/chemicals. However, normal brain activity is additionally composed of integrated low-frequency (0.5-100 Hz) field potentials (LFPs) which are filtered out of MEA recordings. The objective of this study was to characterize the relationship between HF and LFP neural network signals, and to assess the relative sensitivity of LFPs to selected neurotoxicants. Rat primary cortical cultures were grown on glass, single-well MEA chips. Spontaneous activity was sampled at 25 kHz and recorded (5 min) (Multi-Channel Systems) from mature networks (14 days in vitro). HF (spike, mean firing rate, MFR) and LF (power spectrum, amplitude) components were extracted from each network and served as its baseline (BL). Next, each chip was treated with either 1) a positive control, bicuculline (BIC, 25μM) or domoic acid (DA, 0.3μM), 2) or a negative control, acetaminophen (ACE, 100μM) or glyphosate (GLY, 100μM), 3) a solvent control (H2O or DMSO:EtOH), or 4) a neurotoxicant, (carbaryl, CAR 5, 30μM ; lindane, LIN 1, 10μM; permethrin, PERM 25, 50μM; triadimefon, TRI 5, 65μM). Post treatment, 5 mins of spontaneous activity was recorded and analyzed. As expected posit

A Hybrid Neural Network and Feature Extraction Technique for Target Recognition.

DTIC Science & Technology

target features are extracted, the extracted data being evaluated in an artificial neural network to identify a target at a location within the image scene from which the different viewing angles extend.

Contact effects analyzed by a parameter extraction method based on a single bottom-gate/top-contact organic thin-film transistor

NASA Astrophysics Data System (ADS)

Takagaki, Shunsuke; Yamada, Hirofumi; Noda, Kei

2018-03-01

Contact effects in organic thin-film transistors (OTFTs) were examined by using our previously proposed parameter extraction method from the electrical characteristics of a single staggered-type device. Gate-voltage-dependent contact resistance and channel mobility in the linear regime were evaluated for bottom-gate/top-contact (BGTC) pentacene TFTs with active layers of different thicknesses, and for pentacene TFTs with contact-doped layers prepared by coevaporation of pentacene and tetrafluorotetracyanoquinodimethane (F4TCNQ). The extracted parameters suggested that the influence of the contact resistance becomes more prominent with the larger active-layer thickness, and that contact-doping experiments give rise to a drastic decrease in the contact resistance and a concurrent considerable improvement in the channel mobility. Additionally, the estimated energy distributions of trap density in the transistor channel probably reflect the trap filling with charge carriers injected into the channel regions. The analysis results in this study confirm the effectiveness of our proposed method, with which we can investigate contact effects and circumvent the influences of characteristic variations in OTFT fabrication.

A hybrid model based on neural networks for biomedical relation extraction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Zhang, Shaowu; Sun, Yuanyuan; Yang, Liang

2018-05-01

Biomedical relation extraction can automatically extract high-quality biomedical relations from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in the literature. Recurrent neural networks (RNNs) and convolutional neural networks (CNNs) are two major neural network models for biomedical relation extraction. Neural network-based methods for biomedical relation extraction typically focus on the sentence sequence and employ RNNs or CNNs to learn the latent features from sentence sequences separately. However, RNNs and CNNs have their own advantages for biomedical relation extraction. Combining RNNs and CNNs may improve biomedical relation extraction. In this paper, we present a hybrid model for the extraction of biomedical relations that combines RNNs and CNNs. First, the shortest dependency path (SDP) is generated based on the dependency graph of the candidate sentence. To make full use of the SDP, we divide the SDP into a dependency word sequence and a relation sequence. Then, RNNs and CNNs are employed to automatically learn the features from the sentence sequence and the dependency sequences, respectively. Finally, the output features of the RNNs and CNNs are combined to detect and extract biomedical relations. We evaluate our hybrid model using five public (protein-protein interaction) PPI corpora and a (drug-drug interaction) DDI corpus. The experimental results suggest that the advantages of RNNs and CNNs in biomedical relation extraction are complementary. Combining RNNs and CNNs can effectively boost biomedical relation extraction performance. Copyright © 2018 Elsevier Inc. All rights reserved.

A Spectrum Access Based on Quality of Service (QoS) in Cognitive Radio Networks.

PubMed

Zhai, Linbo; Wang, Hua; Gao, Chuangen

2016-01-01

The quality of service (QoS) is important issue for cognitive radio networks. In the cognitive radio system, the licensed users, also called primary users (PUs), are authorized to utilize the wireless spectrum, while unlicensed users, also called secondary users (SUs), are not authorized to use the wireless spectrum. SUs access the wireless spectrum opportunistically when the spectrum is idle. While SUs use an idle channel, the instance that PUs come back makes SUs terminate their communications and leave the current channel. Therefore, quality of service (QoS) is difficult to be ensured for SUs. In this paper, we first propose an analysis model to obtain QoS for cognitive radio networks such as blocking probability, completed traffic and termination probability of SUs. When the primary users use the channels frequently, QoS of SUs is difficult to be ensured, especially the termination probability. Then, we propose a channel reservation scheme to improve QoS of SUs. The scheme makes the terminated SUs move to the reserved channels and keep on communications. Simulation results show that our scheme can improve QoS of SUs especially the termination probability with a little cost of blocking probability in dynamic environment.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information.

PubMed

Wang, Chundong; Zhu, Likun; Gong, Liangyi; Zhao, Zhentang; Yang, Lei; Liu, Zheli; Cheng, Xiaochun

2018-03-15

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.

Accurate Sybil Attack Detection Based on Fine-Grained Physical Channel Information

PubMed Central

Wang, Chundong; Zhao, Zhentang; Yang, Lei; Liu, Zheli; Cheng, Xiaochun

2018-01-01

With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks. PMID:29543773

Adaptive limited feedback for interference alignment in MIMO interference channels.

PubMed

Zhang, Yang; Zhao, Chenglin; Meng, Juan; Li, Shibao; Li, Li

2016-01-01

It is very important that the radar sensor network has autonomous capabilities such as self-managing, etc. Quite often, MIMO interference channels are applied to radar sensor networks, and for self-managing purpose, interference management in MIMO interference channels is critical. Interference alignment (IA) has the potential to dramatically improve system throughput by effectively mitigating interference in multi-user networks at high signal-to-noise (SNR). However, the implementation of IA predominantly relays on perfect and global channel state information (CSI) at all transceivers. A large amount of CSI has to be fed back to all transmitters, resulting in a proliferation of feedback bits. Thus, IA with limited feedback has been introduced to reduce the sum feedback overhead. In this paper, by exploiting the advantage of heterogeneous path loss, we first investigate the throughput of IA with limited feedback in interference channels while each user transmits multi-streams simultaneously, then we get the upper bound of sum rate in terms of the transmit power and feedback bits. Moreover, we propose a dynamic feedback scheme via bit allocation to reduce the throughput loss due to limited feedback. Simulation results demonstrate that the dynamic feedback scheme achieves better performance in terms of sum rate.

Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

PubMed

Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

2012-01-01

In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

Microstates in resting-state EEG: current status and future directions.

PubMed

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M; Farzan, Faranak

2015-02-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable "microstates" that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

Microstates in Resting-State EEG: Current Status and Future Directions

PubMed Central

Khanna, Arjun; Pascual-Leone, Alvaro; Michel, Christoph M.; Farzan, Faranak

2015-01-01

Electroencephalography (EEG) is a powerful method of studying the electrophysiology of the brain with high temporal resolution. Several analytical approaches to extract information from the EEG signal have been proposed. One method, termed microstate analysis, considers the multichannel EEG recording as a series of quasi-stable “microstates” that are each characterized by a unique topography of electric potentials over the entire channel array. Because this technique simultaneously considers signals recorded from all areas of the cortex, it is capable of assessing the function of large-scale brain networks whose disruption is associated with several neuropsychiatric disorders. In this review, we first introduce the method of EEG microstate analysis. We then review studies that have discovered significant changes in the resting-state microstate series in a variety of neuropsychiatric disorders and behavioral states. We discuss the potential utility of this method in detecting neurophysiological impairments in disease and monitoring neurophysiological changes in response to an intervention. Finally, we discuss how the resting-state microstate series may reflect rapid switching among neural networks while the brain is at rest, which could represent activity of resting-state networks described by other neuroimaging modalities. We conclude by commenting on the current and future status of microstate analysis, and suggest that EEG microstates represent a promising neurophysiological tool for understanding and assessing brain network dynamics on a millisecond timescale in health and disease. PMID:25526823

Channel and Interface Management in a Heterogeneous Multi-Channel Multi-Radio Wireless Network

DTIC Science & Technology

2009-03-01

its channel is changed, the change is advertised to neighbors. An R-interface is also used for transmitting packets that are to be sent on its...Agrawal, S. Banerjee, and S. Ganguly, “Distributed channel management in uncoordinated wireless environments.” in MOBI - COM, 2006, pp. 170–181. [18] W. Wang

Deterministic Teleportation of Multi-qudit States in a Network via Various Probabilistic Channels

NASA Astrophysics Data System (ADS)

Zhang, Ti-Hang; Jiang, Min; Huang, Xu; Wan, Min

2014-04-01

In this paper, we present a generalized approach to faithfully teleport an unknown state of a multi-qudit system involving multi spatially remote agents via various probabilistic channels. In a quantum teleportation network, there are generally multi spatially remote relay agents between a sender and a distant receiver. With the assistance of the relay agents, it is possible to directly construct a deterministic channel between the sender and the distant receiver. In our scheme, different from previous probabilistic teleportation protocols, the integrity of the unknown multi-qudit state could be maintained even when the construction of faithful channel fails. Our results also show that the required auxiliary particle resources, local operations and classical communications are considerably reduced for the present purpose.

IQ imbalance tolerable parallel-channel DMT transmission for coherent optical OFDMA access network

NASA Astrophysics Data System (ADS)

Jung, Sang-Min; Mun, Kyoung-Hak; Jung, Sun-Young; Han, Sang-Kook

2016-12-01

Phase diversity of coherent optical communication provides spectrally efficient higher-order modulation for optical communications. However, in-phase/quadrature (IQ) imbalance in coherent optical communication degrades transmission performance by introducing unwanted signal distortions. In a coherent optical orthogonal frequency division multiple access (OFDMA) passive optical network (PON), IQ imbalance-induced signal distortions degrade transmission performance by interferences of mirror subcarriers, inter-symbol interference (ISI), and inter-channel interference (ICI). We propose parallel-channel discrete multitone (DMT) transmission to mitigate transceiver IQ imbalance-induced signal distortions in coherent orthogonal frequency division multiplexing (OFDM) transmissions. We experimentally demonstrate the effectiveness of parallel-channel DMT transmission compared with that of OFDM transmission in the presence of IQ imbalance.

Le cône sous-marin du Nil et son réseau de chenaux profonds : nouveaux résultats (campagne Fanil)The Nile Cone and its channel system: new results after the Fanil cruise

NASA Astrophysics Data System (ADS)

Bellaiche, Gilbert; Loncke, Lies; Gaullier, Virginie; Mascle, Jean; Courp, Thierry; Moreau, Alain; Radan, Silviu; Sardou, Olivier

2001-10-01

The meandrous leveed channels of the Nile Cone show clear evidence of avulsions. Their sedimentary architecture is founded on numerous stacked lens-shaped acoustic units. In the areas of the distal fan, lobe deposits are apparent from multichannel imagery. Huge debris flow deposits, sometimes associated with pockmarks, are recognized. Mud volcanoes and gas seeping are closely associated with faulting. In the East, a very long north-trending channel, originating from the Egyptian coast, merges with a network of channels, very probably originating from the Levantine coasts. Both networks outlet in the sedimentary basin located south of Cyprus.

In-stream wetlands and their significance for channel filling and the catchment sediment budget, Jugiong Creek, New South Wales

NASA Astrophysics Data System (ADS)

Zierholz, C.; Prosser, I. P.; Fogarty, P. J.; Rustomji, P.

2001-06-01

Evidence is presented here of recent and extensive infilling of the incised channel network of the Jugiong Creek catchment, SE Australia. The present channel network resulted from widespread stream and gully incision in the period between 1880 and 1920. Our survey shows that gully floors have been colonised extensively by emergent macrophyte vegetation since before 1944, forming continuous, dense, in-stream wetlands, which now cover 25% of the channel network in the 2175 km 2 catchment and have so far trapped almost 2,000,000 t of nutrient-enriched, fine sediments. This mass of sediments represents the equivalent of 4.7 years of annual sediment production across the catchment and in some tributaries, more than 20 years of annual yield is stored within in-stream wetlands. Previous work on the late Quaternary stratigraphy of the region has shown that there were repeated phases of channel incision in the past following which the channels quickly stabilised by natural means and then filled with fine-grained sediment to the point of channel extinction, creating unchannelled swampy valley floors. The current formation and spread of in-stream wetlands is interpreted to be the onset of the next infill phase but it is not known whether present conditions will allow complete channel filling and reformation of the pre-existing swampy valley floors. Nevertheless, further spread of in-stream wetlands is likely to increase the sediment trapping capacity and further reduce the discharge of sediments and nutrients into the Murrumbidgee River. The in-stream wetlands may provide a significant capacity to buffer erosion from gullied catchments of considerable size (up to 300 km 2) as an adjunct to current riparian management options. They may also assist the recovery of sediment-impacted channels downstream.

Expected Applications of the SRTM Data Within the Amazon Basin

NASA Astrophysics Data System (ADS)

Alsdorf, D.; Hess, L.; Melack, J.; Melack, J.; Dunne, T.; Dunne, T.; Mertes, L.; Ballantine, A.; Biggs, T.; Holmes, K.

2001-12-01

Using the SRTM data combined with additional SAR, optical, and ground based observations throughout the entire Amazon basin, we plan to (1) determine long-term landscape evolution using a stream channel incision and local uplift model, (2) apply a mass-flux model to estimate the Andean sediment supply, (3) characterize channel migration, (4) model topographically driven runoff and groundwater recharge to assess the rate of delivery of flood runoff to channels, and (5) quantify areas of basic vegetation types and their methane production. Presently, we have been using a high-resolution mosaic of JERS-1 SAR data until the Basin wide SRTM DEM is available. Stream networks automatically extracted from the mosaic have already been combined with interferometric SAR measurements of water level changes to yield a floodplain storage estimate. Furthermore, the mosaic has now been used to characterize regions of expected topographic ruggedness. The advent of the DEM will allow relationships to be developed between topographic slopes and measured concentrations and fluxes of dissolved inorganic material. Most significantly for SRTM DEM studies and as based on our SIR-C research, the C-band radar is backscattered from within the uppermost canopy. Thus to convert the DEM from canopy-top to expected ground heights we plan to use our classification methods to produce a map showing vegetation types and average heights which can be subtracted from the SRTM DEM.

Topics on data transmission problem in software definition network

NASA Astrophysics Data System (ADS)

Gao, Wei; Liang, Li; Xu, Tianwei; Gan, Jianhou

2017-08-01

In normal computer networks, the data transmission between two sites go through the shortest path between two corresponding vertices. However, in the setting of software definition network (SDN), it should monitor the network traffic flow in each site and channel timely, and the data transmission path between two sites in SDN should consider the congestion in current networks. Hence, the difference of available data transmission theory between normal computer network and software definition network is that we should consider the prohibit graph structures in SDN, and these forbidden subgraphs represent the sites and channels in which data can't be passed by the serious congestion. Inspired by theoretical analysis of an available data transmission in SDN, we consider some computational problems from the perspective of the graph theory. Several results determined in the paper imply the sufficient conditions of data transmission in SDN in the various graph settings.

Gene expression links functional networks across cortex and striatum.

PubMed

Anderson, Kevin M; Krienen, Fenna M; Choi, Eun Young; Reinen, Jenna M; Yeo, B T Thomas; Holmes, Avram J

2018-04-12

The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease.

Thinking outside the channel: Modeling nitrogen cycling in networked river ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Helton, Ashley; Poole, Geoffrey C.; Meyer, Judy

2011-01-01

Agricultural and urban development alters nitrogen and other biogeochemical cycles in rivers worldwide. Because such biogeochemical processes cannot be measured empirically across whole river networks, simulation models are critical tools for understanding river-network biogeochemistry. However, limitations inherent in current models restrict our ability to simulate biogeochemical dynamics among diverse river networks. We illustrate these limitations using a river-network model to scale up in situ measures of nitrogen cycling in eight catchments spanning various geophysical and land-use conditions. Our model results provide evidence that catchment characteristics typically excluded from models may control river-network biogeochemistry. Based on our findings, we identify importantmore » components of a revised strategy for simulating biogeochemical dynamics in river networks, including approaches to modeling terrestrial-aquatic linkages, hydrologic exchanges between the channel, floodplain/riparian complex, and subsurface waters, and interactions between coupled biogeochemical cycles.« less

Compact and cost-effective multi-channel optical spectrometer for fine FBG sensing in IoT technology

NASA Astrophysics Data System (ADS)

Konishi, Tsuyoshi; Yamasaki, Yu

2018-02-01

Optical fiber sensor networks have attracted much attention in IoT technology and a fiber Bragg grating is one of key sensor devices there because of their advantages in a high affinity for optical fiber networks, compactness, immunity to electromagnetic interference and so on. Nevertheless, its sensitivity is not always satisfactory so as to be usable together with widespread cost-effective multi-channel spectrometers. In this paper, we introduce a new cost-effective approach for a portable multi-channel spectrometer with high spectral resolution and demonstrates some preliminary experimental results for fine FBG sensing.

Channel erosion in a rapidly urbanizing region of Tijuana, Mexico: Enlargement downstream of channel hardpoints

NASA Astrophysics Data System (ADS)

Taniguchi, Kristine; Biggs, Trent; Langendoen, Eddy; Castillo, Carlos; Gudiño, Napoleon; Yuan, Yongping; Liden, Douglas

2016-04-01

Urban-induced erosion in Tijuana, Mexico, has led to excessive sediment deposition in the Tijuana Estuary in the United States. Urban areas in developing countries, in contrast to developed countries, are characterized by much lower proportions of vegetation and impervious surfaces due to limited access to urban services such as road paving and landscaping, and larger proportions of exposed soils. In developing countries, traditional watershed scale variables such as impervious surfaces may not be good predictors of channel enlargement. In this research, we surveyed the stream channel network of an erodible tributary of the Tijuana River Watershed, Los Laureles Canyon, at 125 locations, including repeat surveys from 2008. Structure from Motion (SfM) and 3D photo-reconstruction techniques were used to create digital terrain models of stream reaches upstream and downstream of channel hardpoints. Channels are unstable downstream of hardpoints, with incision up to 2 meters and widening up to 12 meters. Coordinated channelization is essential to avoid piece-meal approaches that lead to channel degradation. Watershed impervious area is not a good predictor of channel erosion due to the overriding importance of hardpoints and likely to the high sediment supply from the unpaved roads which prevents channel erosion throughout the stream network.

A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition.

PubMed

Khushaba, Rami N; Al-Timemy, Ali H; Al-Ani, Ahmed; Al-Jumaily, Adel

2017-10-01

The extraction of the accurate and efficient descriptors of muscular activity plays an important role in tackling the challenging problem of myoelectric control of powered prostheses. In this paper, we present a new feature extraction framework that aims to give an enhanced representation of muscular activities through increasing the amount of information that can be extracted from individual and combined electromyogram (EMG) channels. We propose to use time-domain descriptors (TDDs) in estimating the EMG signal power spectrum characteristics; a step that preserves the computational power required for the construction of spectral features. Subsequently, TDD is used in a process that involves: 1) representing the temporal evolution of the EMG signals by progressively tracking the correlation between the TDD extracted from each analysis time window and a nonlinearly mapped version of it across the same EMG channel and 2) representing the spatial coherence between the different EMG channels, which is achieved by calculating the correlation between the TDD extracted from the differences of all possible combinations of pairs of channels and their nonlinearly mapped versions. The proposed temporal-spatial descriptors (TSDs) are validated on multiple sparse and high-density (HD) EMG data sets collected from a number of intact-limbed and amputees performing a large number of hand and finger movements. Classification results showed significant reductions in the achieved error rates in comparison to other methods, with the improvement of at least 8% on average across all subjects. Additionally, the proposed TSDs achieved significantly well in problems with HD-EMG with average classification errors of <5% across all subjects using windows lengths of 50 ms only.

Revisiting Melton: Analyzing the correlation structure of geomorphological and climatological parameters

NASA Astrophysics Data System (ADS)

Carothers, R. A.; Sangireddy, H.; Passalacqua, P.

2013-12-01

In his expansive 1957 study of over 80 basins in Arizona, Colorado, New Mexico, and Utah, Mark Melton measured key morphometric, soil, land cover, and climatic parameters [Melton, 1957]. He identified correlations between morphological parameters and climatic regimes in an attempt to characterize the geomorphology of the basin as a function of climate and vegetation. Using modern techniques such as high resolution digital terrain models in combination with high spatial resolution weather station records, vector soil maps, seamless raster geological data, and land cover vector maps, we revisit Melton's 1957 dataset with the following hypotheses: (1) Patterns of channelization carry strong, codependent signatures in the form of statistical correlations of rainfall variability, soil type, and vegetation patterns. (2) Channelization patterns reflect the erosion processes on sub-catchment scale and the subsequent processes of vegetation recovery and gullying. In order to characterize various topographic and climatic parameters, we obtain elevation and land cover data from the USGS National Elevation dataset, climate data from the Western Regional Climate Center and PRISM climate group database, and soil type from the USDA STATSGO soil database. We generate a correlative high resolution database on vegetation, soil cover, lithology, and climatology for the basins identified by Melton in his 1957 study. Using the GeoNet framework developed by Passalacqua et al. [2010], we extract various morphological parameters such as slope, drainage density, and stream frequency. We also calculate metrics for patterns of channelization such as number of channelized pixels in a basin and channel head density. In order to understand the correlation structure between climate and morphological variables, we compute the Pearson's correlation coefficient similar to Melton's analysis and also explore other statistical procedures to characterize the feedbacks between these variables. By identifying the differences in Melton's and our results, we address the influence of climate over the degree of channel dissection in the landscape. References: Melton, M. A. (1957). An analysis of the relations among elements of climate, surface properties, and geomorphology (No. CU-TR-11). COLUMBIA UNIV NEW YORK Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., & Dietrich, W. E. (2010). A geometric framework for channel network extraction from lidar: Nonlinear diffusion and geodesic paths. Journal of Geophysical Research: Earth Surface (2003-2012), 115(F1). PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu, created 4 Feb 2004 Soil Survey Staff, Natural Resources Conservation Service, United States Department of Agriculture. U.S. General Soil Map (STATSGO2). Available online at http://soildatamart.nrcs.usda.gov USGS National Map Viewer, United States Geological Survey. Web. 10 June 2013. http://viewer.nationalmap.gov/viewer/ Western U.S. Historical Climate Summaries, Western Regional Climate Group, 2013. Web. 10 June 2013. http://www.wrcc.dri.edu/Climsum.html

Network-scale dynamics of sediment mixtures: how do tectonics affect surface bed texture and channel slope?

NASA Astrophysics Data System (ADS)

Gasparini, N. M.; Bras, R. L.; Tucker, G. E.

2003-04-01

An alluvial channel's slope and bed texture are intimately linked. Along with fluvial discharge, these variables are the key players in setting alluvial transport rates. We know that both channel slope and mean grain size usually decrease downstream, but how sensitive are these variables to tectonic changes? Are basin concavity and downstream fining drastically disrupted during transitions from one tectonic regime to another? We explore these questions using the CHILD numerical landscape evolution model to generate alluvial networks composed of a sand and gravel mixture. The steady-state and transient patterns of both channel slope and sediment texture are investigated. The steady-state patterns in slope and sediment texture are verified independently by solving the erosion equations under equilibrium conditions, i.e. the case when the erosion rate is equal to the uplift rate across the entire landscape. The inclusion of surface texture as a free parameter (as opposed to just channel slope) leads to some surprising results. In all cases, an increase in uplift rate results in channel beds which are finer at equilibrium (for a given drainage area). Higher uplift rates imply larger equilibrium transport rates; this leads to finer channels that have a smaller critical shear stress to entrain material, and therefore more material can be transported for a given discharge (and channel slope). Changes in equilibrium slopes are less intuitive. An increase in uplift rates can cause channel slopes to increase, remain the same, or decrease, depending on model parameter values. In the surprising case in which equilibrium channel slopes decrease with increasing uplift rates, we suggest that surface texture changes more than compensate for the required increase in transport rates, causing channel slopes to decrease. These results highlight the important role of sediment grain size in determining transport rates and caution us against ignoring this important variable in fluvial networks.

All-printed thin-film transistors from networks of liquid-exfoliated nanosheets

NASA Astrophysics Data System (ADS)

Kelly, Adam G.; Hallam, Toby; Backes, Claudia; Harvey, Andrew; Esmaeily, Amir Sajad; Godwin, Ian; Coelho, João; Nicolosi, Valeria; Lauth, Jannika; Kulkarni, Aditya; Kinge, Sachin; Siebbeles, Laurens D. A.; Duesberg, Georg S.; Coleman, Jonathan N.

2017-04-01

All-printed transistors consisting of interconnected networks of various types of two-dimensional nanosheets are an important goal in nanoscience. Using electrolytic gating, we demonstrate all-printed, vertically stacked transistors with graphene source, drain, and gate electrodes, a transition metal dichalcogenide channel, and a boron nitride (BN) separator, all formed from nanosheet networks. The BN network contains an ionic liquid within its porous interior that allows electrolytic gating in a solid-like structure. Nanosheet network channels display on:off ratios of up to 600, transconductances exceeding 5 millisiemens, and mobilities of >0.1 square centimeters per volt per second. Unusually, the on-currents scaled with network thickness and volumetric capacitance. In contrast to other devices with comparable mobility, large capacitances, while hindering switching speeds, allow these devices to carry higher currents at relatively low drive voltages.

Flow model for open-channel reach or network

USGS Publications Warehouse

Schaffranek, R.W.

1987-01-01

Formulation of a one-dimensional model for simulating unsteady flow in a single open-channel reach or in a network of interconnected channels is presented. The model is both general and flexible in that it can be used to simulate a wide range of flow conditions for various channel configurations. It is based on a four-point (box), implicit, finite-difference approximation of the governing nonlinear flow equations with user-definable weighting coefficients to permit varying the solution scheme from box-centered to fully forward. Unique transformation equations are formulated that permit correlation of the unknowns at the extremities of the channels, thereby reducing coefficient matrix and execution time requirements. Discharges and water-surface elevations computed at intermediate locations within a channel are determined following solution of the transformation equations. The matrix of transformation and boundary-condition equations is solved by Gauss elimination using maximum pivot strategy. Two diverse applications of the model are presented to illustrate its broad utility. (USGS)

Modeling and Reconstruction of Micro-structured 3D Chitosan/Gelatin Porous Scaffolds Using Micro-CT

NASA Astrophysics Data System (ADS)

Gong, Haibo; Li, Dichen; He, Jiankang; Liu, Yaxiong; Lian, Qin; Zhao, Jinna

2008-09-01

Three dimensional (3D) channel networks are the key to promise the uniform distribution of nutrients inside 3D hepatic tissue engineering scaffolds and prompt elimination of metabolic products out of the scaffolds. 3D chitosan/gelatin porous scaffolds with predefined internal channels were fabricated and a combination of light microscope, laser confocal microscopy and micro-CT were employed to characterize the structure of porous scaffolds. In order to evaluate the flow field distribution inside the micro-structured 3D scaffolds, a computer reconstructing method based on Micro-CT was proposed. According to this evaluating method, a contrast between 3D porous scaffolds with and without predefined internal channels was also performed to assess scaffolds' fluid characters. Results showed that the internal channel of the 3D scaffolds formed the 3D fluid channel network; the uniformity of flow field distribution of the scaffolds fabricated in this paper was better than the simple porous scaffold without micro-fluid channels.

A review of channel selection algorithms for EEG signal processing

NASA Astrophysics Data System (ADS)

Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

2015-12-01

Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

A semi-automatic method for extracting thin line structures in images as rooted tree network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brazzini, Jacopo; Dillard, Scott; Soille, Pierre

2010-01-01

This paper addresses the problem of semi-automatic extraction of line networks in digital images - e.g., road or hydrographic networks in satellite images, blood vessels in medical images, robust. For that purpose, we improve a generic method derived from morphological and hydrological concepts and consisting in minimum cost path estimation and flow simulation. While this approach fully exploits the local contrast and shape of the network, as well as its arborescent nature, we further incorporate local directional information about the structures in the image. Namely, an appropriate anisotropic metric is designed by using both the characteristic features of the targetmore » network and the eigen-decomposition of the gradient structure tensor of the image. Following, the geodesic propagation from a given seed with this metric is combined with hydrological operators for overland flow simulation to extract the line network. The algorithm is demonstrated for the extraction of blood vessels in a retina image and of a river network in a satellite image.« less

Transmission of 2.5 Gbit/s Spectrum-sliced WDM System for 50 km Single-mode Fiber

NASA Astrophysics Data System (ADS)

Ahmed, Nasim; Aljunid, Sayed Alwee; Ahmad, R. Badlisha; Fadil, Hilal Adnan; Rashid, Mohd Abdur

2011-06-01

The transmission of a spectrum-sliced WDM channel at 2.5 Gbit/s for 50 km of single mode fiber using an system channel spacing only 0.4 nm is reported. We have investigated the system performance using NRZ modulation format. The proposed system is compared with conventional system. The system performance is characterized as the bit-error-rate (BER) received against the system bit rates. Simulation results show that the NRZ modulation format performs well for 2.5 Gbit/s system bit rates. Using this narrow channel spectrum-sliced technique, the total number of multiplexed channels can be increased greatly in WDM system. Therefore, 0.4 nm channel spacing spectrum-sliced WDM system is highly recommended for the long distance optical access networks, like the Metro Area Network (MAN), Fiber-to-the-Building (FTTB) and Fiber-to-the-Home (FTTH).

Two-dimensional distributed-phase-reference protocol for quantum key distribution

NASA Astrophysics Data System (ADS)

Bacco, Davide; Christensen, Jesper Bjerge; Castaneda, Mario A. Usuga; Ding, Yunhong; Forchhammer, Søren; Rottwitt, Karsten; Oxenløwe, Leif Katsuo

2016-12-01

Quantum key distribution (QKD) and quantum communication enable the secure exchange of information between remote parties. Currently, the distributed-phase-reference (DPR) protocols, which are based on weak coherent pulses, are among the most practical solutions for long-range QKD. During the last 10 years, long-distance fiber-based DPR systems have been successfully demonstrated, although fundamental obstacles such as intrinsic channel losses limit their performance. Here, we introduce the first two-dimensional DPR-QKD protocol in which information is encoded in the time and phase of weak coherent pulses. The ability of extracting two bits of information per detection event, enables a higher secret key rate in specific realistic network scenarios. Moreover, despite the use of more dimensions, the proposed protocol remains simple, practical, and fully integrable.

Two-dimensional distributed-phase-reference protocol for quantum key distribution.

PubMed

Bacco, Davide; Christensen, Jesper Bjerge; Castaneda, Mario A Usuga; Ding, Yunhong; Forchhammer, Søren; Rottwitt, Karsten; Oxenløwe, Leif Katsuo

2016-12-22

Quantum key distribution (QKD) and quantum communication enable the secure exchange of information between remote parties. Currently, the distributed-phase-reference (DPR) protocols, which are based on weak coherent pulses, are among the most practical solutions for long-range QKD. During the last 10 years, long-distance fiber-based DPR systems have been successfully demonstrated, although fundamental obstacles such as intrinsic channel losses limit their performance. Here, we introduce the first two-dimensional DPR-QKD protocol in which information is encoded in the time and phase of weak coherent pulses. The ability of extracting two bits of information per detection event, enables a higher secret key rate in specific realistic network scenarios. Moreover, despite the use of more dimensions, the proposed protocol remains simple, practical, and fully integrable.

Measurement of the top-quark mass with dilepton events selected using neuroevolution at CDF.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Bednar, P; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Copic, K; Cordelli, M; Cortiana, G; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Handler, R; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hauser, J; Hays, C; Heck, M; Heijboer, A; Heinemann, B; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Koay, S A; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kusakabe, Y; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, S W; Leone, S; Lewis, J D; Lin, C S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lu, R-S; Lucchesi, D; Lueck, J; Luci, C; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Lytken, E; Mack, P; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlok, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Reisert, B; Rekovic, V; Renton, P; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Scheidle, T; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scott, A L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sfyrla, A; Shalhout, S Z; Shears, T; Shekhar, R; Shepard, P F; Sherman, D; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Tiwari, V; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Würthwein, F; Wagner, P; Wagner, R G; Wagner, R L; Wagner-Kuhr, J; Wagner, W; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Whiteson, S; Wicklund, A B; Wicklund, E; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Wynne, S M; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zaw, I; Zhang, X; Zheng, Y; Zucchelli, S

2009-04-17

We report a measurement of the top-quark mass M_{t} in the dilepton decay channel tt[over ] --> bl;{'+} nu_{l};{'}b[over ]l;{-}nu[over ]_{l}. Events are selected with a neural network which has been directly optimized for statistical precision in top-quark mass using neuroevolution, a technique modeled on biological evolution. The top-quark mass is extracted from per-event probability densities that are formed by the convolution of leading order matrix elements and detector resolution functions. The joint probability is the product of the probability densities from 344 candidate events in 2.0 fb;{-1} of pp[over ] collisions collected with the CDF II detector, yielding a measurement of M_{t} = 171.2 +/- 2.7(stat) +/- 2.9(syst) GeV / c;{2}.

Two-dimensional distributed-phase-reference protocol for quantum key distribution

PubMed Central

Bacco, Davide; Christensen, Jesper Bjerge; Castaneda, Mario A. Usuga; Ding, Yunhong; Forchhammer, Søren; Rottwitt, Karsten; Oxenløwe, Leif Katsuo

2016-01-01

Quantum key distribution (QKD) and quantum communication enable the secure exchange of information between remote parties. Currently, the distributed-phase-reference (DPR) protocols, which are based on weak coherent pulses, are among the most practical solutions for long-range QKD. During the last 10 years, long-distance fiber-based DPR systems have been successfully demonstrated, although fundamental obstacles such as intrinsic channel losses limit their performance. Here, we introduce the first two-dimensional DPR-QKD protocol in which information is encoded in the time and phase of weak coherent pulses. The ability of extracting two bits of information per detection event, enables a higher secret key rate in specific realistic network scenarios. Moreover, despite the use of more dimensions, the proposed protocol remains simple, practical, and fully integrable. PMID:28004821

Use of digital webcam images to track spring green-up in a deciduous broadleaf forest.

PubMed

Richardson, Andrew D; Jenkins, Julian P; Braswell, Bobby H; Hollinger, David Y; Ollinger, Scott V; Smith, Marie-Louise

2007-05-01

Understanding relationships between canopy structure and the seasonal dynamics of photosynthetic uptake of CO(2) by forest canopies requires improved knowledge of canopy phenology at eddy covariance flux tower sites. We investigated whether digital webcam images could be used to monitor the trajectory of spring green-up in a deciduous northern hardwood forest. A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Bartlett AmeriFlux site. Images were collected each day around midday. Red, green, and blue color channel brightness data for a 640 x 100-pixel region-of-interest were extracted from each image. We evaluated the green-up signal extracted from webcam images against changes in the fraction of incident photosynthetically active radiation that is absorbed by the canopy (f (APAR)), a broadband normalized difference vegetation index (NDVI), and the light-saturated rate of canopy photosynthesis (A(max)), inferred from eddy flux measurements. The relative brightness of the green channel (green %) was relatively stable through the winter months. A steady rising trend in green % began around day 120 and continued through day 160, at which point a stable plateau was reached. The relative brightness of the blue channel (blue %) also responded to spring green-up, although there was more day-to-day variation in the signal because blue % was more sensitive to changes in the quality (spectral distribution) of incident radiation. Seasonal changes in blue % were most similar to those in f (APAR) and broadband NDVI, whereas changes in green % proceeded more slowly, and were drawn out over a longer period of time. Changes in A(max) lagged green-up by at least a week. We conclude that webcams offer an inexpensive means by which phenological changes in the canopy state can be quantified. A network of cameras could offer a novel opportunity to implement a regional or national phenology monitoring program.

Automatic seizure detection based on the combination of newborn multi-channel EEG and HRV information

NASA Astrophysics Data System (ADS)

Mesbah, Mostefa; Balakrishnan, Malarvili; Colditz, Paul B.; Boashash, Boualem

2012-12-01

This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Two different approaches were used to combine this extracted information. The first approach, known as feature fusion, involves combining features extracted from EEG and heart rate variability (HRV) into a single feature vector prior to feeding it to a classifier. The second approach, called classifier or decision fusion, is achieved by combining the independent decisions of the EEG and the HRV-based classifiers. Tested on recordings obtained from eight newborns with identified EEG seizures, the proposed neonatal seizure detection algorithms achieved 95.20% sensitivity and 88.60% specificity for the feature fusion case and 95.20% sensitivity and 94.30% specificity for the classifier fusion case. These results are considerably better than those involving classifiers using EEG only (80.90%, 86.50%) or HRV only (85.70%, 84.60%).

Development of a microfluidic device for cell concentration and blood cell-plasma separation.

PubMed

Maria, M Sneha; Kumar, B S; Chandra, T S; Sen, A K

2015-12-01

This work presents design, fabrication and test of a microfluidic device which employs Fahraeus-Lindqvist and Zweifach-Fung effects for cell concentration and blood cell-plasma separation. The device design comprises a straight main channel with a series of branched channels placed symmetrically on both sides of the main channel. The design implements constrictions before each junction (branching point) in order to direct cells that would have migrated closer to the wall (naturally or after liquid extraction at a junction) towards the centre of the main channel. Theoretical and numerical analysis are performed for design of the microchannel network to ensure that a minimum flow rate ratio (of 2.5:1, main channel-to-side channels) is maintained at each junction and predict flow rate at the plasma outlet. The dimensions and location of the constrictions were determined using numerical simulations. The effect of presence of constrictions before the junctions was demonstrated by comparing the performances of the device with and without constrictions. To demonstrate the performance of the device, initial experiments were performed with polystyrene microbeads (10 and 15 μm size) and droplets. Finally, the device was used for concentration of HL60 cells and separation of plasma and cells in diluted blood samples. The cell concentration and blood-plasma purification efficiency was quantified using Haemocytometer and Fluorescence-Activated Cell Sorter (FACS). A seven-fold cell concentration was obtained with HL60 cells and a purification efficiency of 70 % and plasma recovery of 80 % was observed for diluted (1:20) blood sample. FACS was used to identify cell lysis and the cell viability was checked using Trypan Blue test which showed that more than 99 % cells are alive indicating the suitability of the device for practical use. The proposed device has potential to be used as a sample preparation module in lab on chip based diagnostic platforms.

Artificial neural network modeling and optimization of ultrahigh pressure extraction of green tea polyphenols.

PubMed

Xi, Jun; Xue, Yujing; Xu, Yinxiang; Shen, Yuhong

2013-11-01

In this study, the ultrahigh pressure extraction of green tea polyphenols was modeled and optimized by a three-layer artificial neural network. A feed-forward neural network trained with an error back-propagation algorithm was used to evaluate the effects of pressure, liquid/solid ratio and ethanol concentration on the total phenolic content of green tea extracts. The neural network coupled with genetic algorithms was also used to optimize the conditions needed to obtain the highest yield of tea polyphenols. The obtained optimal architecture of artificial neural network model involved a feed-forward neural network with three input neurons, one hidden layer with eight neurons and one output layer including single neuron. The trained network gave the minimum value in the MSE of 0.03 and the maximum value in the R(2) of 0.9571, which implied a good agreement between the predicted value and the actual value, and confirmed a good generalization of the network. Based on the combination of neural network and genetic algorithms, the optimum extraction conditions for the highest yield of green tea polyphenols were determined as follows: 498.8 MPa for pressure, 20.8 mL/g for liquid/solid ratio and 53.6% for ethanol concentration. The total phenolic content of the actual measurement under the optimum predicated extraction conditions was 582.4 ± 0.63 mg/g DW, which was well matched with the predicted value (597.2mg/g DW). This suggests that the artificial neural network model described in this work is an efficient quantitative tool to predict the extraction efficiency of green tea polyphenols. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Decoding communities in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

A Novel Nano/Micro-Fluidic Reactor for Evaluation of Pore-Scale Reactive Transport

NASA Astrophysics Data System (ADS)

Werth, C. J.; Alcalde, R.; Ghazvini, S.; Sanford, R. A.; Fouke, B. W.; Valocchi, A. J.

2017-12-01

The reactive transport of pollutants in groundwater can be affected by the presence of stressor chemicals, which inhibit microbial functions. The stressor can be a primary reactant (e.g., trichloroethene), a reaction product (e.g., nitrite from nitrate), or some other chemical present in groundwater (e.g., antibiotic). In this work, a novel nano/microfluidic cell was developed to examine the effect of the antibiotic ciprofloxacin on nitrate reduction coupled to lactate oxidation. The reactor contains parallel boundary channels that deliver flow and solutes on either side of a pore network. The boundary channels are separated from the pore network by one centimeter-long, one micrometer-thick walls perforated by hundreds of nanoslits. The nanoslits allow solute mass transfer from the boundary channels to the pore network, but not microbial passage. The pore network was inoculated with a pure culture of Shewanella oneidensis MR-1, and this was allowed to grow on lactate and nitrate in the presence of ciprofloxacin, all delivered through the boundary channels. Microbial growth patterns suggest inhibition from ciprofloxacin and the nitrate reduction product nitrite, and a dependence on nitrate and lactate mass transfer rates from the boundary channels. A numerical model was developed to interpret the controlling mechanisms, and results indicate cell chemotaxis also affects nitrate reduction and microbial growth. The results are broadly relevant to bioremediation efforts where one or more chemicals that inhibit microbial growth are present and inhibit pollutant degradation rates.

Decoding communities in networks.

PubMed

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Land-mobile satellite communication system

NASA Technical Reports Server (NTRS)

Yan, Tsun-Yee (Inventor); Rafferty, William (Inventor); Dessouky, Khaled I. (Inventor); Wang, Charles C. (Inventor); Cheng, Unjeng (Inventor)

1993-01-01

A satellite communications system includes an orbiting communications satellite for relaying communications to and from a plurality of ground stations, and a network management center for making connections via the satellite between the ground stations in response to connection requests received via the satellite from the ground stations, the network management center being configured to provide both open-end service and closed-end service. The network management center of one embodiment is configured to provides both types of service according to a predefined channel access protocol that enables the ground stations to request the type of service desired. The channel access protocol may be configured to adaptively allocate channels to open-end service and closed-end service according to changes in the traffic pattern and include a free-access tree algorithm that coordinates collision resolution among the ground stations.

Synthesizing Existing CSMA and TDMA Based MAC Protocols for VANETs

PubMed Central

Huang, Jiawei; Li, Qi; Zhong, Shaohua; Liu, Lianhai; Zhong, Ping; Wang, Jianxin; Ye, Jin

2017-01-01

Many Carrier Sense Multiple Access (CSMA) and Time Division Multiple Access (TDMA) based medium access control (MAC) protocols for vehicular ad hoc networks (VANETs) have been proposed recently. Contrary to the common perception that they are competitors, we argue that the underlying strategies used in these MAC protocols are complementary. Based on this insight, we design CTMAC, a MAC protocol that synthesizes existing strategies; namely, random accessing channel (used in CSMA-style protocols) and arbitral reserving channel (used in TDMA-based protocols). CTMAC swiftly changes its strategy according to the vehicle density, and its performance is better than the state-of-the-art protocols. We evaluate CTMAC using at-scale simulations. Our results show that CTMAC reduces the channel completion time and increases the network goodput by 45% for a wide range of application workloads and network settings. PMID:28208590

Synthesis of ZnO nanowires for thin film network transistors

NASA Astrophysics Data System (ADS)

Dalal, S. H.; Unalan, H. E.; Zhang, Y.; Hiralal, Pritesh; Gangloff, L.; Flewitt, Andrew J.; Amaratunga, Gehan A. J.; Milne, William I.

2008-08-01

Zinc oxide nanowire networks are attractive as alternatives to organic and amorphous semiconductors due to their wide bandgap, flexibility and transparency. We demonstrate the fabrication of thin film transistors (TFT)s which utilize ZnO nanowires as the semiconducting channel. These thin film transistors can be transparent and flexible and processed at low temperatures on to a variety of substrates. The nanowire networks are created using a simple contact transfer method that is easily scalable. Apparent nanowire network mobility values can be as high as 3.8 cm2/Vs (effective thin film mobility: 0.03 cm2/Vs) in devices with 20μm channel lengths and ON/OFF ratios of up to 104.

Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel information

NASA Astrophysics Data System (ADS)

Mabu, Shingo; Kido, Shoji; Hashimoto, Noriaki; Hirano, Yasushi; Kuremoto, Takashi

2018-02-01

This research proposes a multi-channel deep convolutional neural network (DCNN) for computer-aided diagnosis (CAD) that classifies normal and abnormal opacities of diffuse lung diseases in Computed Tomography (CT) images. Because CT images are gray scale, DCNN usually uses one channel for inputting image data. On the other hand, this research uses multi-channel DCNN where each channel corresponds to the original raw image or the images transformed by some preprocessing techniques. In fact, the information obtained only from raw images is limited and some conventional research suggested that preprocessing of images contributes to improving the classification accuracy. Thus, the combination of the original and preprocessed images is expected to show higher accuracy. The proposed method realizes region of interest (ROI)-based opacity annotation. We used lung CT images taken in Yamaguchi University Hospital, Japan, and they are divided into 32 × 32 ROI images. The ROIs contain six kinds of opacities: consolidation, ground-glass opacity (GGO), emphysema, honeycombing, nodular, and normal. The aim of the proposed method is to classify each ROI into one of the six opacities (classes). The DCNN structure is based on VGG network that secured the first and second places in ImageNet ILSVRC-2014. From the experimental results, the classification accuracy of the proposed method was better than the conventional method with single channel, and there was a significant difference between them.

Dynamics of EEG functional connectivity during statistical learning.

PubMed

Tóth, Brigitta; Janacsek, Karolina; Takács, Ádám; Kóbor, Andrea; Zavecz, Zsófia; Nemeth, Dezso

2017-10-01

Statistical learning is a fundamental mechanism of the brain, which extracts and represents regularities of our environment. Statistical learning is crucial in predictive processing, and in the acquisition of perceptual, motor, cognitive, and social skills. Although previous studies have revealed competitive neurocognitive processes underlying statistical learning, the neural communication of the related brain regions (functional connectivity, FC) has not yet been investigated. The present study aimed to fill this gap by investigating FC networks that promote statistical learning in humans. Young adults (N=28) performed a statistical learning task while 128-channels EEG was acquired. The task involved probabilistic sequences, which enabled to measure incidental/implicit learning of conditional probabilities. Phase synchronization in seven frequency bands was used to quantify FC between cortical regions during the first, second, and third periods of the learning task, respectively. Here we show that statistical learning is negatively correlated with FC of the anterior brain regions in slow (theta) and fast (beta) oscillations. These negative correlations increased as the learning progressed. Our findings provide evidence that dynamic antagonist brain networks serve a hallmark of statistical learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Cut-and-paste restoration of entanglement transmission

NASA Astrophysics Data System (ADS)

Cuevas, Álvaro; Mari, Andrea; De Pasquale, Antonella; Orieux, Adeline; Massaro, Marcello; Sciarrino, Fabio; Mataloni, Paolo; Giovannetti, Vittorio

2017-07-01

The distribution of entangled quantum systems among two or more nodes of a network is a key task at the basis of quantum communication, quantum computation, and quantum cryptography. Unfortunately, the transmission lines used in this procedure can introduce so many perturbations and so much noise in the transmitted signal that they prevent the possibility of restoring quantum correlations in the received messages either by means of encoding optimization or by exploiting local operations and classical communication. In this work we present a procedure which allows one to improve the performance of some of these channels. The mechanism underpinning this result is a protocol which we dub cut and paste, as it consists in extracting and reshuffling the subcomponents of these communication lines, which finally succeed in correcting each other. The proof of this counterintuitive phenomenon, while improving our theoretical understanding of quantum entanglement, also has a direct application in the realization of quantum information networks based on imperfect and highly noisy communication lines. A quantum optics experiment, based on the transmission of single-photon polarization states, is also presented which provides a proof-of-principle test of the proposed protocol.

Modelling the structural controls of primary kaolinite formation

NASA Astrophysics Data System (ADS)

Tierney, R. L.; Glass, H. J.

2016-09-01

An abundance of kaolinite was formed within the St. Austell outcrop of the Cornubian batholith in Cornwall, southwest England, by the hydrous dissolution of feldspar crystals. The permeability of Cornish granites is low and alteration acts pervasively from discontinuity features, with montmorillonite recognised as an intermediate assemblage in partially kaolinised material. Structural features allowed fluids to channel through the impermeable granite and pervade deep into the rock. Areas of high structural control are hypothesised to link well with areas of advanced alteration. As kaolinisation results in a loss of competence, we present a method of utilising discontinuity orientations from nearby unaltered granites alongside the local tectonic history to calculate strain rates and delineate a discrete fracture network. Simulation of the discrete fracture network is demonstrated through a case study at Higher Moor, where kaolinite is actively extracted from a pit. Reconciliation of fracture connectivity and permeability against measured subsurface data show that higher values of modelled properties match with advanced kaolinisation observed in the field. This suggests that the technique may be applicable across various industries and disciplines.

On the motion of substance in a channel of a network and human migration

NASA Astrophysics Data System (ADS)

Vitanov, Nikolay K.; Vitanov, Kaloyan N.

2018-01-01

We model the motion of a substance in a channel of a network that consists of chain of (i) nodes of the network and (ii) edges that connect the nodes and form the way for motion of the substance. The nodes of the channel can have different ;leakage;, i.e., some amount of the substance can leave the channel at a node and the rate of leaving can be different for the different nodes of the channel. The nodes close to the end of the channel for some (design or other) reason may be more ;attractive; for the substance in comparison to the nodes around the incoming node of the channel. We discuss channels containing infinite or finite number of nodes. The main outcome of the model is the distribution of the substance along the nodes. Two regimes of functioning of the channels are studied: stationary regime and non-stationary regime. The distribution of the substance along the nodes of the channel for the case of stationary regime is a distribution with a very long tail that contains as particular case the Waring distribution (for channel with infinite number of nodes) or the truncated Waring distribution (for channel with finite number of nodes). In the non-stationary regime of functioning of the channel one observes an exponential increase or exponential decrease of the amount of substance in the nodes. However the asymptotic distribution of the substance among the nodes of the channel in this regime remains stationary. The studied model is applied to the case of migration of humans through a migration channel consisting of chain of countries. In this case the model accounts for the number of migrants entering the channel through the first country of the channel; permeability of the borders between the countries; possible large attractiveness of some countries of the channel; possibility for migrants to obtain permission to reside in a country of the channel. The main outcome of the model is the distribution of migrants along the countries of the channel. We discuss the conditions for concentration of migrants in selected country of the channel. Finally two scenarios of changes of conditions of the functioning of the channel are discussed. It is shown that from the point of view of decreasing of the number of migrants in the countries of the channel it is more effective to concentrate efforts on preventing the entrance of migrants in the first country of the channel when compared to concentration of efforts on decrease of permeability of the borders between the countries of the channel.

Social network extraction based on Web: 1. Related superficial methods

NASA Astrophysics Data System (ADS)

Khairuddin Matyuso Nasution, Mahyuddin

2018-01-01

Often the nature of something affects methods to resolve the related issues about it. Likewise, methods to extract social networks from the Web, but involve the structured data types differently. This paper reveals several methods of social network extraction from the same sources that is Web: the basic superficial method, the underlying superficial method, the description superficial method, and the related superficial methods. In complexity we derive the inequalities between methods and so are their computations. In this case, we find that different results from the same tools make the difference from the more complex to the simpler: Extraction of social network by involving co-occurrence is more complex than using occurrences.

Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

NASA Astrophysics Data System (ADS)

Kim, Jonghwa; André, Elisabeth

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

The significance of small streams

NASA Astrophysics Data System (ADS)

Wohl, Ellen

2017-09-01

Headwaters, defined here as first- and secondorder streams, make up 70%‒80% of the total channel length of river networks. These small streams exert a critical influence on downstream portions of the river network by: retaining or transmitting sediment and nutrients; providing habitat and refuge for diverse aquatic and riparian organisms; creating migration corridors; and governing connectivity at the watershed-scale. The upstream-most extent of the channel network and the longitudinal continuity and lateral extent of headwaters can be difficult to delineate, however, and people are less likely to recognize the importance of headwaters relative to other portions of a river network. Consequently, headwaters commonly lack the legal protections accorded to other portions of a river network and are more likely to be significantly altered or completely obliterated by land use.

A performance analysis of DS-CDMA and SCPC VSAT networks

NASA Technical Reports Server (NTRS)

Hayes, David P.; Ha, Tri T.

1990-01-01

Spread-spectrum and single-channel-per-carrier (SCPC) transmission techniques work well in very small aperture terminal (VSAT) networks for multiple-access purposes while allowing the earth station antennas to remain small. Direct-sequence code-division multiple-access (DS-CDMA) is the simplest spread-spectrum technique to use in a VSAT network since a frequency synthesizer is not required for each terminal. An examination is made of the DS-CDMA and SCPC Ku-band VSAT satellite systems for low-density (64-kb/s or less) communications. A method for improving the standardf link analysis of DS-CDMA satellite-switched networks by including certain losses is developed. The performance of 50-channel full mesh and star network architectures is analyzed. The selection of operating conditions producing optimum performance is demonstrated.

Multi-temporal monitoring of a regional riparian buffer network (>12,000 km) with LiDAR and photogrammetric point clouds.

PubMed

Michez, Adrien; Piégay, Hervé; Lejeune, Philippe; Claessens, Hugues

2017-11-01

Riparian buffers are of major concern for land and water resource managers despite their relatively low spatial coverage. In Europe, this concern has been acknowledged by different environmental directives which recommend multi-scale monitoring (from local to regional scales). Remote sensing methods could be a cost-effective alternative to field-based monitoring, to build replicable "wall-to-wall" monitoring strategies of large river networks and associated riparian buffers. The main goal of our study is to extract and analyze various parameters of the riparian buffers of up to 12,000 km of river in southern Belgium (Wallonia) from three-dimensional (3D) point clouds based on LiDAR and photogrammetric surveys to i) map riparian buffers parameters on different scales, ii) interpret the regional patterns of the riparian buffers and iii) propose new riparian buffer management indicators. We propose different strategies to synthesize and visualize relevant information at different spatial scales ranging from local (<10 km) to regional scale (>12,000 km). Our results showed that the selected parameters had a clear regional pattern. The reaches of Ardenne ecoregion have channels with the highest flow widths and shallowest depths. In contrast, the reaches of the Loam ecoregion have the narrowest and deepest flow channels. Regional variability in channel width and depth is used to locate management units potentially affected by human impact. Riparian forest of the Loam ecoregion is characterized by the lowest longitudinal continuity and mean tree height, underlining significant human disturbance. As the availability of 3D point clouds at the regional scale is constantly growing, our study proposes reproducible methods which can be integrated into regional monitoring by land managers. With LiDAR still being relatively expensive to acquire, the use of photogrammetric point clouds combined with LiDAR data is a cost-effective means to update the characterization of the riparian forest conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

DEM-based analysis of landscape organization: 2) Application to catchment comparison

NASA Astrophysics Data System (ADS)

Seibert, J.; McGlynn, B.

2003-04-01

The delineation of homogeneous landscape elements (or "hydrologic response units") is often a prerequisite in field investigations and the application of semi-distributed hydrologic (or coupled hydrologic and biogeochemical) models. Delineation and quantification of dominant landscape elements requires methods to extract the features from digital elevation data or other readily available information. It is often assumed that hillslope and riparian areas constitute the two most important and identifiable landscape units contributing to catchment runoff in upland humid catchments. In addition, we have found that that the degree of hillslope water expression in stormflow is partially a function of riparian to hillslope reservoir ratios and landscape organization. Therefore, we developed a simple approach for quantifying landscape organization and distributed riparian to hillslope area ratios (riparian buffer ratios), as described in the accompanying contribution. Here we use this method as a framework for comparing and classifying diverse catchments located in Europe, the U.S., and New Zealand. Based on the three catchments Maimai (New Zealand), Panola (Georgia) and Sleepers (Vermont) we obtained the following preliminary results: (1) Local area entering the stream channels was most variable at Maimai and consistently diffuse at Sleepers and Panola. Also the median local area entering the channel network was largest at Maimai and smallest at Sleepers and Panola. This demonstrates the degree of landscape dissection (highest for Maimai) and the concentration of hillslope inputs along the stream network. (2) Riparian areas were smallest at Maimai, larger at Sleepers, and largest at Panola. The combination of riparian zone extent and focused (Maimai) versus diffuse (Sleepers and Panola) hillslope inputs to riparian zones controls local riparian to hillslope area ratios (riparian buffer capacities). (3) Area was accumulated to a large extend in the channel heads in all catchments. At Sleepers about 75 percent of all area originated from sub-catchments of less than 5 ha, whereas this proportion was 50 and 40 percent at Panola and Maimai respectively.

Bladder cancer treatment response assessment in CT urography using two-channel deep-learning network

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Samala, Ravi K.; Cohan, Richard H.; Caoili, Elaine M.; Weizer, Alon Z.; Alva, Ajjai

2018-02-01

We are developing a CAD system for bladder cancer treatment response assessment in CT. We trained a 2- Channel Deep-learning Convolution Neural Network (2Ch-DCNN) to identify responders (T0 disease) and nonresponders to chemotherapy. The 87 lesions from 82 cases generated 18,600 training paired ROIs that were extracted from segmented bladder lesions in the pre- and post-treatment CT scans and partitioned for 2-fold cross validation. The paired ROIs were input to two parallel channels of the 2Ch-DCNN. We compared the 2Ch-DCNN with our hybrid prepost- treatment ROI DCNN method and the assessments by 2 experienced abdominal radiologists. The radiologist estimated the likelihood of stage T0 after viewing each pre-post-treatment CT pair. Receiver operating characteristic analysis was performed and the area under the curve (AUC) and the partial AUC at sensitivity <90% (AUC0.9) were compared. The test AUCs were 0.76+/-0.07 and 0.75+/-0.07 for the 2 partitions, respectively, for the 2Ch-DCNN, and were 0.75+/-0.08 and 0.75+/-0.07 for the hybrid ROI method. The AUCs for Radiologist 1 were 0.67+/-0.09 and 0.75+/-0.07 for the 2 partitions, respectively, and were 0.79+/-0.07 and 0.70+/-0.09 for Radiologist 2. For the 2Ch-DCNN, the AUC0.9s were 0.43 and 0.39 for the 2 partitions, respectively, and were 0.19 and 0.28 for the hybrid ROI method. For Radiologist 1, the AUC0.9s were 0.14 and 0.34 for partition 1 and 2, respectively, and were 0.33 and 0.23 for Radiologist 2. Our study demonstrated the feasibility of using a 2Ch-DCNN for the estimation of bladder cancer treatment response in CT.

A new surface-process model for landscape evolution at a mountain belt scale

NASA Astrophysics Data System (ADS)

Willett, Sean D.; Braun, Jean; Herman, Frederic

2010-05-01

We present a new surface process model designed for modeling surface erosion and mass transport at an orogenic scale. Modeling surface processes at a large-scale is difficult because surface geomorphic processes are frequently described at the scale of a few meters, and such resolution cannot be represented in orogen-scale models operating over hundreds of square kilometers. We circumvent this problem by implementing a hybrid numerical -- analytical model. Like many previous models, the model is based on a numerical fluvial network represented by a series of nodes linked by model rivers in a descending network, with fluvial incision and sediment transport defined by laws operating on this network. However we only represent the largest rivers in the landscape by nodes in this model. Low-order rivers and water divides between large rivers are determined from analytical solutions assuming steady-state conditions with respect to the local river channel. The analytical solution includes the same fluvial incision law as the large rivers and a channel head with a specified size and mean slope. This permits a precise representation of the position of water divides between river basins. This is a key characteristic in landscape evolution as divide migration provides a positive feedback between river incision and a consequent increase in drainage area. The analytical solution also provides an explicit criterion for river capture, which occurs once a water divide migrates to its neighboring channel. This algorithm avoids the artificial network organization that often results from meshing and remeshing algorithms in numerical models. We demonstrate the use of this model with several simple examples including uniform uplift of a block, simultaneous uplift and shortening of a block, and a model involving strike slip faulting. We find a strong dependence on initial condition, but also a surprisingly strong dependence on channel head height parameters. Low channel heads, as expected, lead to more fluvial capture, but with low initial relief initial and a small channel-head height, runaway capture is common, with a few rivers capturing much of the available drainage area. With larger channel-head relief, lateral capture of rivers is less common, resulting in evenly spaced river basins. Basin spacing ratios matching those observed in nature are obtained for specific channel head parameters. These models thus demonstrate the mixed control on basin characteristics by antecedent river networks and channel-head parameters, which control the mobility of drainage basin water divides.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2011-09-30

channel interference mitigation for underwater acoustic MIMO - OFDM . 3) Turbo equalization for OFDM modulated physical layer network coding. 4) Blind CFO...Underwater Acoustic MIMO - OFDM . MIMO - OFDM has been actively studied for high data rate communications over the bandwidthlimited underwater acoustic...with the cochannel interference (CCI) due to parallel transmissions in MIMO - OFDM . Our proposed receiver has the following components: 1

MoNET: media over net gateway processor for next-generation network

NASA Astrophysics Data System (ADS)

Elabd, Hammam; Sundar, Rangarajan; Dedes, John

2001-12-01

MoNETTM (Media over Net) SX000 product family is designed using a scalable voice, video and packet-processing platform to address applications with channel densities from few voice channels to four OC3 per card. This platform is developed for bridging public circuit-switched network to the next generation packet telephony and data network. The platform consists of a DSP farm, RISC processors and interface modules. DSP farm is required to execute voice compression, image compression and line echo cancellation algorithms for large number of voice, video, fax, and modem or data channels. RISC CPUs are used for performing various packetizations based on RTP, UDP/IP and ATM encapsulations. In addition, RISC CPUs also participate in the DSP farm load management and communication with the host and other MoP devices. The MoNETTM S1000 communications device is designed for voice processing and for bridging TDM to ATM and IP packet networks. The S1000 consists of the DSP farm based on Carmel DSP core and 32-bit RISC CPU, along with Ethernet, Utopia, PCI, and TDM interfaces. In this paper, we will describe the VoIP infrastructure, building blocks of the S500, S1000 and S3000 devices, algorithms executed on these device and associated channel densities, detailed DSP architecture, memory architecture, data flow and scheduling.

Weighted least squares techniques for improved received signal strength based localization.

PubMed

Tarrío, Paula; Bernardos, Ana M; Casar, José R

2011-01-01

The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling.

Weighted Least Squares Techniques for Improved Received Signal Strength Based Localization

PubMed Central

Tarrío, Paula; Bernardos, Ana M.; Casar, José R.

2011-01-01

The practical deployment of wireless positioning systems requires minimizing the calibration procedures while improving the location estimation accuracy. Received Signal Strength localization techniques using propagation channel models are the simplest alternative, but they are usually designed under the assumption that the radio propagation model is to be perfectly characterized a priori. In practice, this assumption does not hold and the localization results are affected by the inaccuracies of the theoretical, roughly calibrated or just imperfect channel models used to compute location. In this paper, we propose the use of weighted multilateration techniques to gain robustness with respect to these inaccuracies, reducing the dependency of having an optimal channel model. In particular, we propose two weighted least squares techniques based on the standard hyperbolic and circular positioning algorithms that specifically consider the accuracies of the different measurements to obtain a better estimation of the position. These techniques are compared to the standard hyperbolic and circular positioning techniques through both numerical simulations and an exhaustive set of real experiments on different types of wireless networks (a wireless sensor network, a WiFi network and a Bluetooth network). The algorithms not only produce better localization results with a very limited overhead in terms of computational cost but also achieve a greater robustness to inaccuracies in channel modeling. PMID:22164092

Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?. -based on different credit correlations using hierarchical methods

NASA Astrophysics Data System (ADS)

He, Fang; Chen, Xi

2016-11-01

The accelerating accumulation and risk concentration of Chinese local financing platforms debts have attracted wide attention throughout the world. Due to the network of financial exposures among institutions, the failure of several platforms or regions of systemic importance will probably trigger systemic risk and destabilize the financial system. However, the complex network of credit relationships in Chinese local financing platforms at the state level remains unknown. To fill this gap, we presented the first complex networks and hierarchical cluster analysis of the credit market of Chinese local financing platforms using the ;bottom up; method from firm-level data. Based on balance-sheet channel, we analyzed the topology and taxonomy by applying the analysis paradigm of subdominant ultra-metric space to an empirical data in 2013. It is remarked that we chose to extract the network of co-financed financing platforms in order to evaluate the effect of risk contagion from platforms to bank system. We used the new credit similarity measure by combining the factor of connectivity and size, to extract minimal spanning trees (MSTs) and hierarchical trees (HTs). We found that: (1) the degree distributions of credit correlation backbone structure of Chinese local financing platforms are fat tailed, and the structure is unstable with respect to targeted failures; (2) the backbone is highly hierarchical, and largely explained by the geographic region; (3) the credit correlation backbone structure based on connectivity and size is significantly heterogeneous; (4) key platforms and regions of systemic importance, and contagion path of systemic risk are obtained, which are contributed to preventing systemic risk and regional risk of Chinese local financing platforms and preserving financial stability under the framework of macro prudential supervision. Our approach of credit similarity measure provides a means of recognizing ;systemically important; institutions and regions for a targeted policy with risk minimization which gives a flexible and comprehensive consideration to both aspects of ;too big to fail; and ;too central to fail;.

Computational, Experimental and Engineering Foundations of Ionic Channels as Miniaturized Sensors, Devices and Systems

DTIC Science & Technology

2003-10-01

made in an ensemble of channels of unknown orientation and number, preventing quantitative analysis . • Currents have been compared among continuum PNP...microfluidic) analysis of ion channels to obtain fundamental insights into the selectivity, conductivity, and sensitivity of ion channels [19], [6...1.1 Develop fast and efficient simulators for steady-state analysis of continuum model for extraction of I-V curves. 1.2 Create

Integrating publicly-available data to generate computationally ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) framework provides a way of organizing knowledge related to the key biological events that result in a particular health outcome. For the majority of environmental chemicals, the availability of curated pathways characterizing potential toxicity is limited. Methods are needed to assimilate large amounts of available molecular data and quickly generate putative AOPs for further testing and use in hazard assessment. A graph-based workflow was used to facilitate the integration of multiple data types to generate computationally-predicted (cp) AOPs. Edges between graph entities were identified through direct experimental or literature information or computationally inferred using frequent itemset mining. Data from the TG-GATEs and ToxCast programs were used to channel large-scale toxicogenomics information into a cpAOP network (cpAOPnet) of over 20,000 relationships describing connections between chemical treatments, phenotypes, and perturbed pathways measured by differential gene expression and high-throughput screening targets. Sub-networks of cpAOPs for a reference chemical (carbon tetrachloride, CCl4) and outcome (hepatic steatosis) were extracted using the network topology. Comparison of the cpAOP subnetworks to published mechanistic descriptions for both CCl4 toxicity and hepatic steatosis demonstrate that computational approaches can be used to replicate manually curated AOPs and identify pathway targets that lack genomic mar

Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

PubMed

Kim, Seongjung; Kim, Jongman; Ahn, Soonjae; Kim, Youngho

2018-04-18

Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.

Development & Characterization of Multifunctional Microfluidic Materials

NASA Astrophysics Data System (ADS)

Ucar, Ahmet Burak

The field of microfluidics has been mostly investigated for miniaturized lab on a chip devices for analytical and clinical applications. However, there is an emerging class of "smart" microfluidic materials, combining microfluidics with soft polymers to yield new functionalities. The best inspiration for such materials found in nature is skin, whose functions are maintained and controlled by a vascular "microfluidic" network. We report here the development and characterization of a few new classes of microfluidic materials. First, we introduced microfluidic materials that can change their stiffness on demand. These materials were based on an engineered microchannel network embedded into a matrix of polydimethylsiloxane (PDMS), whose channels were filled with a liquid photoresist (SU- 8). The elastomer filled with the photoresist was initially soft. The materials were shaped into a desired geometry and then exposed to UV-light. Once photocured, the material preserved the defined shape and it could be bent, twisted or stretched with a very high recoverable strain. As soon as the external force was removed the material returned back to its predefined shape. Thus, the polymerized SU-8 acted as the 'endoskeleton' of the microfluidic network, which drastically increased the composite's elastic and bending moduli. Second, we demonstrated a class of simple and versatile soft microfluidic materials that can be turned optically transparent or colored on demand. These materials were made in the form of flexible sheets containing a microchannel network embedded in PDMS, similar to the photocurable materials. However, this time the channels were filled with a glycerolwater mixture, whose refractive index was matched with that of the PDMS matrix. By pumping such dye solutions into the channel network and consecutively replacing the medium, we showed that we can control the material's color and light transmittance in the visible and near-infrared regions, which can be used for developing 'smart' windows and heat management. To better design new color changing elastomers, we investigated the role of the network geometry on liquid replacement efficiency with the aid of a multiphysics modeling and simulation software package, COMSOL. We simulated the liquid flow in various network geometries. Serpentine, parallel channel and lattice networks, as well as their tapered versions were compared. The comparison criteria were based on rapid and uniform liquid replacement with the least amount of dye/liquid required, for which we set multiple constraints such as constant inlet pressure or total channel area. We demonstrated that the tapered lattice type network provided the most rapid and uniform replacement with minimal liquid waste. Next, we designed a simple and inexpensive liquid dispensing microfluidic material which does not require complex micromachining techniques or automated actuators. It consisted of only a PDMS matrix with embedded chambers and channels. 'Pores/slits' were made on the surface and the liquid was released by contact on the dispensing surface of the material. We varied the network design, geometry, dimension, slit shape and length, and tested the material's liquid release performance. Promising preliminary results were obtained but for an end product with repeatable and reproducible performance, both material fabrication and characterization need to be improved further. Finally, we describe an alternative material/method for the fabrication of microfluidic materials. We aimed to replace the conventional fabrication material PDMS with Polyethylene (PE) sheets. The sheets were as transparent and flexible as PDMS, and also thinner. Channel patterns were drawn with a polymer solution of PolyVinylAlcohol (PVA), which is immiscible with PE, and captured in between the two PE sheets. After fusing the PE sheets on a hot press, PVA was washed off with water, so that the 'microfluidic channels' were successfully created. The produced channel widths were ˜0.7-0.8 mm. This novel method eliminates the need for soft lithography and master fabrication, thus decreases the cost and time of the material fabrication.

Experimental demonstration of wavelength domain rogue-free ONU based on wavelength-pairing for TDM/WDM optical access networks.

PubMed

Lee, Jie Hyun; Park, Heuk; Kang, Sae-Kyoung; Lee, Joon Ki; Chung, Hwan Seok

2015-11-30

In this study, we propose and experimentally demonstrate a wavelength domain rogue-free ONU based on wavelength-pairing of downstream and upstream signals for time/wavelength division-multiplexed optical access networks. The wavelength-pairing tunable filter is aligned to the upstream wavelength channel by aligning it to one of the downstream wavelength channels. Wavelength-pairing is implemented with a compact and cyclic Si-AWG integrated with a Ge-PD. The pairing filter covered four 100 GHz-spaced wavelength channels. The feasibility of the wavelength domain rogue-free operation is investigated by emulating malfunction of the misaligned laser. The wavelength-pairing tunable filter based on the Si-AWG blocks the upstream signal in the non-assigned wavelength channel before data collision with other ONUs.

Segmentized Clear Channel Assessment for IEEE 802.15.4 Networks.

PubMed

Son, Kyou Jung; Hong, Sung Hyeuck; Moon, Seong-Pil; Chang, Tae Gyu; Cho, Hanjin

2016-06-03

This paper proposed segmentized clear channel assessment (CCA) which increases the performance of IEEE 802.15.4 networks by improving carrier sense multiple access with collision avoidance (CSMA/CA). Improving CSMA/CA is important because the low-power consumption feature and throughput performance of IEEE 802.15.4 are greatly affected by CSMA/CA behavior. To improve the performance of CSMA/CA, this paper focused on increasing the chance to transmit a packet by assessing precise channel status. The previous method used in CCA, which is employed by CSMA/CA, assesses the channel by measuring the energy level of the channel. However, this method shows limited channel assessing behavior, which comes from simple threshold dependent channel busy evaluation. The proposed method solves this limited channel decision problem by dividing CCA into two groups. Two groups of CCA compare their energy levels to get precise channel status. To evaluate the performance of the segmentized CCA method, a Markov chain model has been developed. The validation of analytic results is confirmed by comparing them with simulation results. Additionally, simulation results show the proposed method is improving a maximum 8.76% of throughput and decreasing a maximum 3.9% of the average number of CCAs per packet transmission than the IEEE 802.15.4 CCA method.

Segmentized Clear Channel Assessment for IEEE 802.15.4 Networks

PubMed Central

Son, Kyou Jung; Hong, Sung Hyeuck; Moon, Seong-Pil; Chang, Tae Gyu; Cho, Hanjin

2016-01-01

This paper proposed segmentized clear channel assessment (CCA) which increases the performance of IEEE 802.15.4 networks by improving carrier sense multiple access with collision avoidance (CSMA/CA). Improving CSMA/CA is important because the low-power consumption feature and throughput performance of IEEE 802.15.4 are greatly affected by CSMA/CA behavior. To improve the performance of CSMA/CA, this paper focused on increasing the chance to transmit a packet by assessing precise channel status. The previous method used in CCA, which is employed by CSMA/CA, assesses the channel by measuring the energy level of the channel. However, this method shows limited channel assessing behavior, which comes from simple threshold dependent channel busy evaluation. The proposed method solves this limited channel decision problem by dividing CCA into two groups. Two groups of CCA compare their energy levels to get precise channel status. To evaluate the performance of the segmentized CCA method, a Markov chain model has been developed. The validation of analytic results is confirmed by comparing them with simulation results. Additionally, simulation results show the proposed method is improving a maximum 8.76% of throughput and decreasing a maximum 3.9% of the average number of CCAs per packet transmission than the IEEE 802.15.4 CCA method. PMID:27271626

Chromatic characterization of a three-channel colorimeter using back-propagation neural networks

NASA Astrophysics Data System (ADS)

Pardo, P. J.; Pérez, A. L.; Suero, M. I.

2004-09-01

This work describes a method for the chromatic characterization of a three-channel colorimeter of recent design and construction dedicated to color vision research. The colorimeter consists of two fixed monochromators and a third monochromator interchangeable with a cathode ray tube or any other external light source. Back-propagation neural networks were used for the chromatic characterization to establish the relationship between each monochromator's input parameters and the tristimulus values of each chromatic stimulus generated. The results showed the effectiveness of this type of neural-network-based system for the chromatic characterization of the stimuli produced by any monochromator.

A Quantitative Characterization and Classification of Martian Valley Networks: New Constraints on Mars' Early Climate and Its Variability in Space and Time

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.

2014-12-01

Valley networks and outflow channels are among the most arresting features of Mars' surface. Remarkable similarities between the structure and complexity of individual Martian channels with certain fluvial systems on Earth supports a popular picture of a warm wet early Mars. A key assumption in this picture is that "typical" Martian examples adequately capture the average character of the majority of all valley networks. However, a full catalog of the distribution of geomorphologic variability of valley networks over Mars' surface geometry has never been established. Accordingly, we present the first planet-wide map in which we use statistical methods and theoretical arguments to classify Martian channels in terms of the mechanics governing their formation. Using new metrics for the size, shape and complexity of channel networks, which we ground truth against a large suite of terrestrial examples, we distinguish drainage patterns related to glacial, subglacial, fluvial and lava flows. Preliminary results separate lava flows from other flow features and show that these features can be divided into three different groups of increasing complexity. The characteristics of these groups suggest that they represent fluvial, subglacial and glacial features. We show also that the relative proportions of the different groups varies systematically, with higher density of river-like features located in low longitudes and increasing glacial-like features as we move east or west. Our results suggest that the early Martian climate and hydrologic cycle was richer and more diverse than originally thought.

Vessel extraction in retinal images using automatic thresholding and Gabor Wavelet.

PubMed

Ali, Aziah; Hussain, Aini; Wan Zaki, Wan Mimi Diyana

2017-07-01

Retinal image analysis has been widely used for early detection and diagnosis of multiple systemic diseases. Accurate vessel extraction in retinal image is a crucial step towards a fully automated diagnosis system. This work affords an efficient unsupervised method for extracting blood vessels from retinal images by combining existing Gabor Wavelet (GW) method with automatic thresholding. Green channel image is extracted from color retinal image and used to produce Gabor feature image using GW. Both green channel image and Gabor feature image undergo vessel-enhancement step in order to highlight blood vessels. Next, the two vessel-enhanced images are transformed to binary images using automatic thresholding before combined to produce the final vessel output. Combining the images results in significant improvement of blood vessel extraction performance compared to using individual image. Effectiveness of the proposed method was proven via comparative analysis with existing methods validated using publicly available database, DRIVE.

An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.

Experimental implementation of array-compressed parallel transmission at 7 tesla.

PubMed

Yan, Xinqiang; Cao, Zhipeng; Grissom, William A

2016-06-01

To implement and validate a hardware-based array-compressed parallel transmission (acpTx) system. In array-compressed parallel transmission, a small number of transmit channels drive a larger number of transmit coils, which are connected via an array compression network that implements optimized coil-to-channel combinations. A two channel-to-eight coil array compression network was developed using power splitters, attenuators and phase shifters, and a simulation was performed to investigate the effects of coil coupling on power dissipation in a simplified network. An eight coil transmit array was constructed using induced current elimination decoupling, and the coil and network were validated in benchtop measurements, B1+ mapping scans, and an accelerated spiral excitation experiment. The developed attenuators came within 0.08 dB of the desired attenuations, and reflection coefficients were -22 dB or better. The simulation demonstrated that up to 3× more power was dissipated in the network when coils were poorly isolated (-9.6 dB), versus well-isolated (-31 dB). Compared to split circularly-polarized coil combinations, the additional degrees of freedom provided by the array compression network led to 54% lower squared excitation error in the spiral experiment. Array-compressed parallel transmission was successfully implemented in a hardware system. Further work is needed to develop remote network tuning and to minimize network power dissipation. Magn Reson Med 75:2545-2552, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Perceptually tuned low-bit-rate video codec for ATM networks

NASA Astrophysics Data System (ADS)

Chou, Chun-Hsien

1996-02-01

In order to maintain high visual quality in transmitting low bit-rate video signals over asynchronous transfer mode (ATM) networks, a layered coding scheme that incorporates the human visual system (HVS), motion compensation (MC), and conditional replenishment (CR) is presented in this paper. An empirical perceptual model is proposed to estimate the spatio- temporal just-noticeable distortion (STJND) profile for each frame, by which perceptually important (PI) prediction-error signals can be located. Because of the limited channel capacity of the base layer, only coded data of motion vectors, the PI signals within a small strip of the prediction-error image and, if there are remaining bits, the PI signals outside the strip are transmitted by the cells of the base-layer channel. The rest of the coded data are transmitted by the second-layer cells which may be lost due to channel error or network congestion. Simulation results show that visual quality of the reconstructed CIF sequence is acceptable when the capacity of the base-layer channel is allocated with 2 multiplied by 64 kbps and the cells of the second layer are all lost.

A Power-Efficient Clustering Protocol for Coal Mine Face Monitoring with Wireless Sensor Networks Under Channel Fading Conditions

PubMed Central

Ren, Peng; Qian, Jiansheng

2016-01-01

This study proposes a novel power-efficient and anti-fading clustering based on a cross-layer that is specific to the time-varying fading characteristics of channels in the monitoring of coal mine faces with wireless sensor networks. The number of active sensor nodes and a sliding window are set up such that the optimal number of cluster heads (CHs) is selected in each round. Based on a stable expected number of CHs, we explore the channel efficiency between nodes and the base station by using a probe frame and the joint surplus energy in assessing the CH selection. Moreover, the sending power of a node in different periods is regulated by the signal fade margin method. The simulation results demonstrate that compared with several common algorithms, the power-efficient and fading-aware clustering with a cross-layer (PEAFC-CL) protocol features a stable network topology and adaptability under signal time-varying fading, which effectively prolongs the lifetime of the network and reduces network packet loss, thus making it more applicable to the complex and variable environment characteristic of a coal mine face. PMID:27338380

IP voice over ATM satellite: experimental results over satellite channels

NASA Astrophysics Data System (ADS)

Saraf, Koroush A.; Butts, Norman P.

1999-01-01

IP telephony, a new technology to provide voice communication over traditional data networks, has the potential to revolutionize telephone communication within the modern enterprise. This innovation uses packetization techniques to carry voice conversations over IP networks. This packet switched technology promises new integrated services, and lower cost long-distance communication compared to traditional circuit switched telephone networks. Future satellites will need to carry IP traffic efficiently in order to stay competitive in servicing the global data- networking and global telephony infrastructure. However, the effects of Voice over IP over switched satellite channels have not been investigated in detail. To fully understand the effects of satellite channels on Voice over IP quality; several experiments were conducted at Lockheed Martin Telecommunications' Satellite Integration Lab. The result of those experiments along with suggested improvements for voice communication over satellite are presented in this document. First, a detailed introduction of IP telephony as a suitable technology for voice communication over future satellites is presented. This is followed by procedures for the experiments, along with results and strategies. In conclusion we hope that these capability demonstrations will alleviate any uncertainty regarding the applicability of this technology to satellite networks.

To Each According to its Degree: The Meritocracy and Topocracy of Embedded Markets

NASA Astrophysics Data System (ADS)

Borondo, J.; Borondo, F.; Rodriguez-Sickert, C.; Hidalgo, C. A.

2014-01-01

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

To each according to its degree: the meritocracy and topocracy of embedded markets.

PubMed

Borondo, J; Borondo, F; Rodriguez-Sickert, C; Hidalgo, C A

2014-01-21

A system is said to be meritocratic if the compensation and power available to individuals is determined by their abilities and merits. A system is topocratic if the compensation and power available to an individual is determined primarily by her position in a network. Here we introduce a model that is perfectly meritocratic for fully connected networks but that becomes topocratic for sparse networks-like the ones in society. In the model, individuals produce and sell content, but also distribute the content produced by others when they belong to the shortest path connecting a buyer and a seller. The production and distribution of content defines two channels of compensation: a meritocratic channel, where individuals are compensated for the content they produce, and a topocratic channel, where individual compensation is based on the number of shortest paths that go through them in the network. We solve the model analytically and show that the distribution of payoffs is meritocratic only if the average degree of the nodes is larger than a root of the total number of nodes. We conclude that, in the light of this model, the sparsity and structure of networks represents a fundamental constraint to the meritocracy of societies.

The extraction of Φ – N total cross section from d ( γ , p K + K - ) n

DOE PAGES

Qian, X.; Chen, W.; Gao, H.; ...

2009-10-01

We report on the first measurement of the differential cross section ofmore » $$\\phi$$-meson photoproduction for the $$d(\\gamma,pK^{+}K^{-})n$$ exclusive reaction channel. The experiment was performed using a \\textcolor{black}{tagged-photon} beam and the CEBAF Large Acceptance Spectrometer (CLAS) at Jefferson Lab. A combined analysis using data from the $$d(\\gamma,pK^{+}K^{-})n$$ channel and those from a previous publication on coherent $$\\phi$$ production on the deuteron has been carried out to extract the $$\\phi-N$$ total cross section, $$\\sigma_{\\phi N}$$. The extracted $$\\phi-N$$ total cross section favors a value above 20 mb. This value is larger than the value extracted using vector-meson dominance models for $$\\phi$$ photoproduction on the proton.« less

Social network extraction based on Web: 3. the integrated superficial method

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Sitompul, O. S.; Noah, S. A.

2018-03-01

The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n - 1)/2 for n social actors.

Hardware and Software Integration to Support Real-Time Space Link Emulation

NASA Technical Reports Server (NTRS)

Murawski, Robert; Bhasin, Kul; Bittner, David; Sweet, Aaron; Coulter, Rachel; Schwab, Devin

2012-01-01

Prior to operational use, communications hardware and software must be thoroughly tested and verified. In space-link communications, field testing equipment can be prohibitively expensive and cannot test to non-ideal situations. In this paper, we show how software and hardware emulation tools can be used to accurately model the characteristics of a satellite communication channel in a lab environment. We describe some of the challenges associated with developing an emulation lab and present results to demonstrate the channel modeling. We then show how network emulation software can be used to extend a hardware emulation model without requiring additional network and channel simulation hardware.

Hardware and Software Integration to Support Real-Time Space-Link Emulation

NASA Technical Reports Server (NTRS)

Murawski, Robert; Bhasin, Kul; Bittner, David

2012-01-01

Prior to operational use, communications hardware and software must be thoroughly tested and verified. In space-link communications, field testing equipment can be prohibitively expensive and cannot test to non-ideal situations. In this paper, we show how software and hardware emulation tools can be used to accurately model the characteristics of a satellite communication channel in a lab environment. We describe some of the challenges associated with developing an emulation lab and present results to demonstrate the channel modeling. We then show how network emulation software can be used to extend a hardware emulation model without requiring additional network and channel simulation hardware.

Protograph LDPC Codes Over Burst Erasure Channels

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Sam; Jones, Christopher

2006-01-01

In this paper we design high rate protograph based LDPC codes suitable for binary erasure channels. To simplify the encoder and decoder implementation for high data rate transmission, the structure of codes are based on protographs and circulants. These LDPC codes can improve data link and network layer protocols in support of communication networks. Two classes of codes were designed. One class is designed for large block sizes with an iterative decoding threshold that approaches capacity of binary erasure channels. The other class is designed for short block sizes based on maximizing minimum stopping set size. For high code rates and short blocks the second class outperforms the first class.

Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks.

PubMed

Tran, Son N; d'Avila Garcez, Artur S

2018-02-01

Developments in deep learning have seen the use of layerwise unsupervised learning combined with supervised learning for fine-tuning. With this layerwise approach, a deep network can be seen as a more modular system that lends itself well to learning representations. In this paper, we investigate whether such modularity can be useful to the insertion of background knowledge into deep networks, whether it can improve learning performance when it is available, and to the extraction of knowledge from trained deep networks, and whether it can offer a better understanding of the representations learned by such networks. To this end, we use a simple symbolic language-a set of logical rules that we call confidence rules-and show that it is suitable for the representation of quantitative reasoning in deep networks. We show by knowledge extraction that confidence rules can offer a low-cost representation for layerwise networks (or restricted Boltzmann machines). We also show that layerwise extraction can produce an improvement in the accuracy of deep belief networks. Furthermore, the proposed symbolic characterization of deep networks provides a novel method for the insertion of prior knowledge and training of deep networks. With the use of this method, a deep neural-symbolic system is proposed and evaluated, with the experimental results indicating that modularity through the use of confidence rules and knowledge insertion can be beneficial to network performance.

Face recognition via Gabor and convolutional neural network

NASA Astrophysics Data System (ADS)

Lu, Tongwei; Wu, Menglu; Lu, Tao

2018-04-01

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

Inter-subunit interactions across the upper voltage sensing-pore domain interface contribute to the concerted pore opening transition of Kv channels.

PubMed

Shem-Ad, Tzilhav; Irit, Orr; Yifrach, Ofer

2013-01-01

The tight electro-mechanical coupling between the voltage-sensing and pore domains of Kv channels lies at the heart of their fundamental roles in electrical signaling. Structural data have identified two voltage sensor pore inter-domain interaction surfaces, thus providing a framework to explain the molecular basis for the tight coupling of these domains. While the contribution of the intra-subunit lower domain interface to the electro-mechanical coupling that underlies channel opening is relatively well understood, the contribution of the inter-subunit upper interface to channel gating is not yet clear. Relying on energy perturbation and thermodynamic coupling analyses of tandem-dimeric Shaker Kv channels, we show that mutation of upper interface residues from both sides of the voltage sensor-pore domain interface stabilizes the closed channel state. These mutations, however, do not affect slow inactivation gating. We, moreover, find that upper interface residues form a network of state-dependent interactions that stabilize the open channel state. Finally, we note that the observed residue interaction network does not change during slow inactivation gating. The upper voltage sensing-pore interaction surface thus only undergoes conformational rearrangements during channel activation gating. We suggest that inter-subunit interactions across the upper domain interface mediate allosteric communication between channel subunits that contributes to the concerted nature of the late pore opening transition of Kv channels.

Spatially Controlled Relay Beamforming

NASA Astrophysics Data System (ADS)

Kalogerias, Dionysios

This thesis is about fusion of optimal stochastic motion control and physical layer communications. Distributed, networked communication systems, such as relay beamforming networks (e.g., Amplify & Forward (AF)), are typically designed without explicitly considering how the positions of the respective nodes might affect the quality of the communication. Optimum placement of network nodes, which could potentially improve the quality of the communication, is not typically considered. However, in most practical settings in physical layer communications, such as relay beamforming, the Channel State Information (CSI) observed by each node, per channel use, although it might be (modeled as) random, it is both spatially and temporally correlated. It is, therefore, reasonable to ask if and how the performance of the system could be improved by (predictively) controlling the positions of the network nodes (e.g., the relays), based on causal side (CSI) information, and exploitting the spatiotemporal dependencies of the wireless medium. In this work, we address this problem in the context of AF relay beamforming networks. This novel, cyber-physical system approach to relay beamforming is termed as "Spatially Controlled Relay Beamforming". First, we discuss wireless channel modeling, however, in a rigorous, Bayesian framework. Experimentally accurate and, at the same time, technically precise channel modeling is absolutely essential for designing and analyzing spatially controlled communication systems. In this work, we are interested in two distinct spatiotemporal statistical models, for describing the behavior of the log-scale magnitude of the wireless channel: 1. Stationary Gaussian Fields: In this case, the channel is assumed to evolve as a stationary, Gaussian stochastic field in continuous space and discrete time (say, for instance, time slots). Under such assumptions, spatial and temporal statistical interactions are determined by a set of time and space invariant parameters, which completely determine the mean and covariance of the underlying Gaussian measure. This model is relatively simple to describe, and can be sufficiently characterized, at least for our purposes, both statistically and topologically. Additionally, the model is rather versatile and there is existing experimental evidence, supporting its practical applicability. Our contributions are summarized in properly formulating the whole spatiotemporal model in a completely rigorous mathematical setting, under a convenient measure theoretic framework. Such framework greatly facilitates formulation of meaningful stochastic control problems, where the wireless channel field (or a function of it) can be regarded as a stochastic optimization surface.. 2. Conditionally Gaussian Fields, when conditioned on a Markovian channel state: This is a completely novel approach to wireless channel modeling. In this approach, the communication medium is assumed to behave as a partially observable (or hidden) system, where a hidden, global, temporally varying underlying stochastic process, called the channel state, affects the spatial interactions of the actual channel magnitude, evaluated at any set of locations in the plane. More specifically, we assume that, conditioned on the channel state, the wireless channel constitutes an observable, conditionally Gaussian stochastic process. The channel state evolves in time according to a known, possibly non stationary, non Gaussian, low dimensional Markov kernel. Recognizing the intractability of general nonlinear state estimation, we advocate the use of grid based approximate nonlinear filters as an effective and robust means for recursive tracking of the channel state. We also propose a sequential spatiotemporal predictor for tracking the channel gains at any point in time and space, providing real time sequential estimates for the respective channel gain map. In this context, our contributions are multifold. Except for the introduction of the layered channel model previously described, this line of research has resulted in a number of general, asymptotic convergence results, advancing the theory of grid-based approximate nonlinear stochastic filtering. In particular, sufficient conditions, ensuring asymptotic optimality are relaxed, and, at the same time, the mode of convergence is strengthened. Although the need for such results initiated as an attempt to theoretically characterize the performance of the proposed approximate methods for statistical inference, in regard to the proposed channel modeling approach, they turn out to be of fundamental importance in the areas of nonlinear estimation and stochastic control. The experimental validation of the proposed channel model, as well as the related parameter estimation problem, termed as "Markovian Channel Profiling (MCP)", fundamentally important for any practical deployment, are subject of current, ongoing research. Second, adopting the first of the two aforementioned channel modeling approaches, we consider the spatially controlled relay beamforming problem for an AF network with a single source, a single destination, and multiple, controlled at will, relay nodes. (Abstract shortened by ProQuest.).

Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis

DTIC Science & Technology

1989-08-01

Automatic Line Network Extraction from Aerial Imangery of Urban Areas Sthrough KnowledghBased Image Analysis N 04 Final Technical ReportI December...Automatic Line Network Extraction from Aerial Imagery of Urban Areas through Knowledge Based Image Analysis Accesion For NTIS CRA&I DTIC TAB 0...paittern re’ognlition. blac’kboardl oriented symbollic processing, knowledge based image analysis , image understanding, aer’ial imsagery, urban area, 17