Optical CDMA components requirements

NASA Astrophysics Data System (ADS)

Chan, James K.

1998-08-01

Optical CDMA is a complementary multiple access technology to WDMA. Optical CDMA potentially provides a large number of virtual optical channels for IXC, LEC and CLEC or supports a large number of high-speed users in LAN. In a network, it provides asynchronous, multi-rate, multi-user communication with network scalability, re-configurability (bandwidth on demand), and network security (provided by inherent CDMA coding). However, optical CDMA technology is less mature in comparison to WDMA. The components requirements are also different from WDMA. We have demonstrated a video transport/switching system over a distance of 40 Km using discrete optical components in our laboratory. We are currently pursuing PIC implementation. In this paper, we will describe the optical CDMA concept/features, the demonstration system, and the requirements of some critical optical components such as broadband optical source, broadband optical amplifier, spectral spreading/de- spreading, and fixed/programmable mask.

Forecasting the short-term passenger flow on high-speed railway with neural networks.

PubMed

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway.

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

SCM: A method to improve network service layout efficiency with network evolution.

PubMed

Zhao, Qi; Zhang, Chuanhao; Zhao, Zheng

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of "software defined network + network function virtualization" (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently.

Digital echocardiography 2002: now is the time

NASA Technical Reports Server (NTRS)

Thomas, James D.; Greenberg, Neil L.; Garcia, Mario J.

2002-01-01

The ability to acquire echocardiographic images digitally, store and transfer these data using the DICOM standard, and routinely analyze examinations exists today and allows the implementation of a digital echocardiography laboratory. The purpose of this review article is to outline the critical components of a digital echocardiography laboratory, discuss general strategies for implementation, and put forth some of the pitfalls that we have encountered in our own implementation. The major components of the digital laboratory include (1) digital echocardiography machines with network output, (2) a switched high-speed network, (3) a high throughput server with abundant local storage, (4) a reliable low-cost archive, (5) software to manage information, and (6) support mechanisms for software and hardware. Implementation strategies can vary from a complete vendor solution providing all components (hardware, software, support), to a strategy similar to our own where standard computer and networking hardware are used with specialized software for management of image and measurement information.

Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

NASA Technical Reports Server (NTRS)

Sanders, Adam M. (Inventor); Strawser, Philip A. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor)

2015-01-01

A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

Tuning stochastic transition rates in a bistable genetic network.

NASA Astrophysics Data System (ADS)

Chickarmane, Vijay; Peterson, Carsten

2009-03-01

We investigate the stochastic dynamics of a simple genetic network, a toggle switch, in which the system makes transitions between the two alternative states. Our interest is in exploring whether such stochastic transitions, which occur due to the intrinsic noise such as transcriptional and degradation events, can be slowed down/speeded up, without changing the mean expression levels of the two genes, which comprise the toggle network. Such tuning is achieved by linking a signaling network to the toggle switch. The signaling network comprises of a protein, which can exist either in an active (phosphorylated) or inactive (dephosphorylated) form, and where its state is determined by one of the genetic network components. The active form of the protein in turn feeds back on the dynamics of the genetic network. We find that the rate of stochastic transitions from one state to the other, is determined essentially by the speed of phosphorylation, and hence the rate can be modulated by varying the phosphatase levels. We hypothesize that such a network architecture can be implemented as a general mechanism for controlling transition rates and discuss applications in population studies of two differentiated cell lineages, ex: the myeloid/erythroid lineage in hematopoiesis.

Forecasting the Short-Term Passenger Flow on High-Speed Railway with Neural Networks

PubMed Central

Xie, Mei-Quan; Li, Xia-Miao; Zhou, Wen-Liang; Fu, Yan-Bing

2014-01-01

Short-term passenger flow forecasting is an important component of transportation systems. The forecasting result can be applied to support transportation system operation and management such as operation planning and revenue management. In this paper, a divide-and-conquer method based on neural network and origin-destination (OD) matrix estimation is developed to forecast the short-term passenger flow in high-speed railway system. There are three steps in the forecasting method. Firstly, the numbers of passengers who arrive at each station or depart from each station are obtained from historical passenger flow data, which are OD matrices in this paper. Secondly, short-term passenger flow forecasting of the numbers of passengers who arrive at each station or depart from each station based on neural network is realized. At last, the OD matrices in short-term time are obtained with an OD matrix estimation method. The experimental results indicate that the proposed divide-and-conquer method performs well in forecasting the short-term passenger flow on high-speed railway. PMID:25544838

Spacecraft Will Communicate "on the Fly"

NASA Technical Reports Server (NTRS)

Laufenberg, Lawrence

2003-01-01

As NASA probes deeper into space, the distance between sensor and scientist increases, as does the time delay. NASA needs to close that gap, while integrating more spacecraft types and missions-from near-Earth orbit to deep space. To speed and integrate communications from space missions to scientists on Earth and back again. NASA needs a comprehensive, high-performance communications network. To this end, the CICT Programs Space Communications (SC) Project is providing technologies for building the Space Internet which will consist of large backbone network, mid-size access networks linked to the backbones, and smaller, ad-hoc network linked to the access network. A key component will be mobile, wireless networks for spacecraft flying in different configurations.

Reliability issues of free-space communications systems and networks

NASA Astrophysics Data System (ADS)

Willebrand, Heinz A.

2003-04-01

Free space optics (FSO) is a high-speed point-to-point connectivity solution traditionally used in the enterprise campus networking market for building-to-building LAN connectivity. However, more recently some wire line and wireless carriers started to deploy FSO systems in their networks. The requirements on FSO system reliability, meaing both system availability and component reliability, are far more stringent in the carrier market when compared to the requirements in the enterprise market segment. This paper tries to outline some of the aspects that are important to ensure carrier class system reliability.

JPARSS: A Java Parallel Network Package for Grid Computing

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

Chen, Jie; Akers, Walter; Chen, Ying

2002-03-01

The emergence of high speed wide area networks makes grid computinga reality. However grid applications that need reliable data transfer still have difficulties to achieve optimal TCP performance due to network tuning of TCP window size to improve bandwidth and to reduce latency on a high speed wide area network. This paper presents a Java package called JPARSS (Java Parallel Secure Stream (Socket)) that divides data into partitions that are sent over several parallel Java streams simultaneously and allows Java or Web applications to achieve optimal TCP performance in a grid environment without the necessity of tuning TCP window size.more » This package enables single sign-on, certificate delegation and secure or plain-text data transfer using several security components based on X.509 certificate and SSL. Several experiments will be presented to show that using Java parallelstreams is more effective than tuning TCP window size. In addition a simple architecture using Web services« less

Near-surface compressional and shear wave speeds constrained by body-wave polarization analysis

NASA Astrophysics Data System (ADS)

Park, Sunyoung; Ishii, Miaki

2018-06-01

A new technique to constrain near-surface seismic structure that relates body-wave polarization direction to the wave speed immediately beneath a seismic station is presented. The P-wave polarization direction is only sensitive to shear wave speed but not to compressional wave speed, while the S-wave polarization direction is sensitive to both wave speeds. The technique is applied to data from the High-Sensitivity Seismograph Network in Japan, and the results show that the wave speed estimates obtained from polarization analysis are compatible with those from borehole measurements. The lateral variations in wave speeds correlate with geological and physical features such as topography and volcanoes. The technique requires minimal computation resources, and can be used on any number of three-component teleseismic recordings, opening opportunities for non-invasive and inexpensive study of the shallowest (˜100 m) crustal structures.

SCM: A method to improve network service layout efficiency with network evolution

PubMed Central

Zhao, Qi; Zhang, Chuanhao

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of “software defined network + network function virtualization” (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently. PMID:29267299

Embedded diagnostic, prognostic, and health management system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Barajas, Leandro G. (Inventor); Strawser, Philip A (Inventor); Sanders, Adam M (Inventor); Reiland, Matthew J (Inventor)

2013-01-01

A robotic system includes a humanoid robot with multiple compliant joints, each moveable using one or more of the actuators, and having sensors for measuring control and feedback data. A distributed controller controls the joints and other integrated system components over multiple high-speed communication networks. Diagnostic, prognostic, and health management (DPHM) modules are embedded within the robot at the various control levels. Each DPHM module measures, controls, and records DPHM data for the respective control level/connected device in a location that is accessible over the networks or via an external device. A method of controlling the robot includes embedding a plurality of the DPHM modules within multiple control levels of the distributed controller, using the DPHM modules to measure DPHM data within each of the control levels, and recording the DPHM data in a location that is accessible over at least one of the high-speed communication networks.

Slow-down or speed-up of inter- and intra-cluster diffusion of controversial knowledge in stubborn communities based on a small world network

NASA Astrophysics Data System (ADS)

Ausloos, Marcel

2015-06-01

Diffusion of knowledge is expected to be huge when agents are open minded. The report concerns a more difficult diffusion case when communities are made of stubborn agents. Communities having markedly different opinions are for example the Neocreationist and Intelligent Design Proponents (IDP), on one hand, and the Darwinian Evolution Defenders (DED), on the other hand. The case of knowledge diffusion within such communities is studied here on a network based on an adjacency matrix built from time ordered selected quotations of agents, whence for inter- and intra-communities. The network is intrinsically directed and not necessarily reciprocal. Thus, the adjacency matrices have complex eigenvalues; the eigenvectors present complex components. A quantification of the slow-down or speed-up effects of information diffusion in such temporal networks, with non-Markovian contact sequences, can be made by comparing the real time dependent (directed) network to its counterpart, the time aggregated (undirected) network, - which has real eigenvalues. In order to do so, small world networks which both contain an odd number of nodes are studied and compared to similar networks with an even number of nodes. It is found that (i) the diffusion of knowledge is more difficult on the largest networks; (ii) the network size influences the slowing-down or speeding-up diffusion process. Interestingly, it is observed that (iii) the diffusion of knowledge is slower in IDP and faster in DED communities. It is suggested that the finding can be "rationalized", if some "scientific quality" and "publication habit" is attributed to the agents, as common sense would guess. This finding offers some opening discussion toward tying scientific knowledge to belief.

Optoelectronics components and technology for optical networking in China: recent progress and future trends

NASA Astrophysics Data System (ADS)

Jiang, Shan; Liu, Shuihua

2004-04-01

Current optical communication systems are more and more relying on the advanced opto-electronic components. A series of revolutionary optical and optoelectronics components technology accounts for the fast progress and field deployment of high-capacity telecommunication and data-transmission systems. Since 1990s, the optical communication industry in China entered a high-speed development period and its wide deployment had already established the solid base for China information infrastructure. In this presentation, the main progress of optoelectronics components and technology in China are reviewed, which includes semiconductor laser diode/photo receiver, fiber optical amplifier, DWDM multiplexer/de-multiplexer, dispersion compensation components and all optical network node components, such as optical switch, OADM, tunable optical filters and variable optical attenuators, etc. Integration discrete components into monolithic/hybrid platform component is an inevitable choice for the consideration of performance, mass production and cost reduction. The current status and the future trends of OEIC and PIC components technology in China will also be discuss mainly on the monolithic integration DFB LD + EA modulator, and planar light-wave circuit (PLC) technology, etc.

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

PubMed Central

Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks.

PubMed

Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

Investigating end-to-end security in the fifth generation wireless capabilities and IoT extensions

NASA Astrophysics Data System (ADS)

Uher, J.; Harper, J.; Mennecke, R. G.; Patton, P.; Farroha, B.

2016-05-01

The emerging 5th generation wireless network will be architected and specified to meet the vision of allowing the billions of devices and millions of human users to share spectrum to communicate and deliver services. The expansion of wireless networks from its current role to serve these diverse communities of interest introduces new paradigms that require multi-tiered approaches. The introduction of inherently low security components, like IoT devices, necessitates that critical data be better secured to protect the networks and users. Moreover high-speed communications that are meant to enable the autonomous vehicles require ultra reliable and low latency paths. This research explores security within the proposed new architectures and the cross interconnection of the highly protected assets with low cost/low security components forming the overarching 5th generation wireless infrastructure.

Control system to reduce the effects of friction in drive trains of continuous-path-positioning systems. [Patent application

DOEpatents

Green, W.L.

1980-12-01

An improved continuous-path-positioning servo-control system is provided for reducing the effects of friction arising at very low cutting speeds in the drive trains of numerically controlled cutting machines, and the like. The improvement comprises a feed forward network for altering the gain of the servo-control loop at low positioning velocities to prevent stick-slip movement of the cutting tool holder being positioned by the control system. The feed forward network shunts conventional lag-compensators in the control loop, or loops, so that the error signal used for positioning varies linearly when the value is small, but being limited for larger values. Thus, at higher positioning speeds there is little effect of the added component upon the control being achieved.

Integrated communication and control systems. I - Analysis

NASA Technical Reports Server (NTRS)

Halevi, Yoram; Ray, Asok

1988-01-01

The paper presents the results of an ICCS analysis focusing on discrete-time control systems subject to time-varying delays. The present analytical technique is applicable to integrated dynamic systems such as those encountered in advanced aircraft, spacecraft, and the real-time control of robots and machine tools via a high-speed network within an autonomous manufacturing environment. The significance of data latency and missynchronization between individual system components in ICCS networks is discussed in view of the time-varying delays.

Do you see what I hear: experiments in multi-channel sound and 3D visualization for network monitoring?

NASA Astrophysics Data System (ADS)

Ballora, Mark; Hall, David L.

2010-04-01

Detection of intrusions is a continuing problem in network security. Due to the large volumes of data recorded in Web server logs, analysis is typically forensic, taking place only after a problem has occurred. This paper describes a novel method of representing Web log information through multi-channel sound, while simultaneously visualizing network activity using a 3-D immersive environment. We are exploring the detection of intrusion signatures and patterns, utilizing human aural and visual pattern recognition ability to detect intrusions as they occur. IP addresses and return codes are mapped to an informative and unobtrusive listening environment to act as a situational sound track of Web traffic. Web log data is parsed and formatted using Python, then read as a data array by the synthesis language SuperCollider [1], which renders it as a sonification. This can be done either for the study of pre-existing data sets or in monitoring Web traffic in real time. Components rendered aurally include IP address, geographical information, and server Return Codes. Users can interact with the data, speeding or slowing the speed of representation (for pre-existing data sets) or "mixing" sound components to optimize intelligibility for tracking suspicious activity.

High-speed railway real-time localization auxiliary method based on deep neural network

NASA Astrophysics Data System (ADS)

Chen, Dongjie; Zhang, Wensheng; Yang, Yang

2017-11-01

High-speed railway intelligent monitoring and management system is composed of schedule integration, geographic information, location services, and data mining technology for integration of time and space data. Assistant localization is a significant submodule of the intelligent monitoring system. In practical application, the general access is to capture the image sequences of the components by using a high-definition camera, digital image processing technique and target detection, tracking and even behavior analysis method. In this paper, we present an end-to-end character recognition method based on a deep CNN network called YOLO-toc for high-speed railway pillar plate number. Different from other deep CNNs, YOLO-toc is an end-to-end multi-target detection framework, furthermore, it exhibits a state-of-art performance on real-time detection with a nearly 50fps achieved on GPU (GTX960). Finally, we realize a real-time but high-accuracy pillar plate number recognition system and integrate natural scene OCR into a dedicated classification YOLO-toc model.

The fiber-optic high-speed data bus for a new generation of military aircraft

NASA Astrophysics Data System (ADS)

Uhlhorn, Roger W.

1991-02-01

The avionic suite for the next generation of military aircraft is being designed with component and module commonality in mind in order to control recurring costs and capitalize on economy of scale. The backbone of the suite fashioned out of these modular building blocks is the fiber-optic bit-serial time-division multiplexed high-speed data bus (HSDB), operating at 50 Mb/s, which provides command and control communications among most of the aircraft subsystems and can be used to provide communications for a fly-by-light flight-control system or for the block transfer of data between mass memories and data processors. The fiber-optic HSDB is examined from the top down, beginning with an overview of the evolution of avionic architectures. A review is given of the standardization activity associated with development of the network, the protocols chosen to implement the desired communication functions, configuration options, and the fiber-optic components used in the bus interfaces or other active nodes of the network. It is believed that the utility of the bus extends beyond aircraft to spacecraft, ships, and land vehicles.

Study on pattern recognition of Raman spectrum based on fuzzy neural network

NASA Astrophysics Data System (ADS)

Zheng, Xiangxiang; Lv, Xiaoyi; Mo, Jiaqing

2017-10-01

Hydatid disease is a serious parasitic disease in many regions worldwide, especially in Xinjiang, China. Raman spectrum of the serum of patients with echinococcosis was selected as the research object in this paper. The Raman spectrum of blood samples from healthy people and patients with echinococcosis are measured, of which the spectrum characteristics are analyzed. The fuzzy neural network not only has the ability of fuzzy logic to deal with uncertain information, but also has the ability to store knowledge of neural network, so it is combined with the Raman spectrum on the disease diagnosis problem based on Raman spectrum. Firstly, principal component analysis (PCA) is used to extract the principal components of the Raman spectrum, reducing the network input and accelerating the prediction speed and accuracy of Network based on remaining the original data. Then, the information of the extracted principal component is used as the input of the neural network, the hidden layer of the network is the generation of rules and the inference process, and the output layer of the network is fuzzy classification output. Finally, a part of samples are randomly selected for the use of training network, then the trained network is used for predicting the rest of the samples, and the predicted results are compared with general BP neural network to illustrate the feasibility and advantages of fuzzy neural network. Success in this endeavor would be helpful for the research work of spectroscopic diagnosis of disease and it can be applied in practice in many other spectral analysis technique fields.

Prefrontal, posterior parietal and sensorimotor network activity underlying speed control during walking

PubMed Central

Bulea, Thomas C.; Kim, Jonghyun; Damiano, Diane L.; Stanley, Christopher J.; Park, Hyung-Soon

2015-01-01

Accumulating evidence suggests cortical circuits may contribute to control of human locomotion. Here, noninvasive electroencephalography (EEG) recorded from able-bodied volunteers during a novel treadmill walking paradigm was used to assess neural correlates of walking. A systematic processing method, including a recently developed subspace reconstruction algorithm, reduced movement-related EEG artifact prior to independent component analysis and dipole source localization. We quantified cortical activity while participants tracked slow and fast target speeds across two treadmill conditions: an active mode that adjusted belt speed based on user movements and a passive mode reflecting a typical treadmill. Our results reveal frequency specific, multi-focal task related changes in cortical oscillations elicited by active walking. Low γ band power, localized to the prefrontal and posterior parietal cortices, was significantly increased during double support and early swing phases, critical points in the gait cycle since the active controller adjusted speed based on pelvis position and swing foot velocity. These phasic γ band synchronizations provide evidence that prefrontal and posterior parietal networks, previously implicated in visuo-spatial and somotosensory integration, are engaged to enhance lower limb control during gait. Sustained μ and β band desynchronization within sensorimotor cortex, a neural correlate for movement, was observed during walking thereby validating our methods for isolating cortical activity. Our results also demonstrate the utility of EEG recorded during locomotion for probing the multi-regional cortical networks which underpin its execution. For example, the cortical network engagement elicited by the active treadmill suggests that it may enhance neuroplasticity for more effective motor training. PMID:26029077

Prediction Of Tensile And Shear Strength Of Friction Surfaced Tool Steel Deposit By Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Manzoor Hussain, M.; Pitchi Raju, V.; Kandasamy, J.; Govardhan, D.

2018-04-01

Friction surface treatment is well-established solid technology and is used for deposition, abrasion and corrosion protection coatings on rigid materials. This novel process has wide range of industrial applications, particularly in the field of reclamation and repair of damaged and worn engineering components. In this paper, we present the prediction of tensile and shear strength of friction surface treated tool steel using ANN for simulated results of friction surface treatment. This experiment was carried out to obtain tool steel coatings of low carbon steel parts by changing contribution process parameters essentially friction pressure, rotational speed and welding speed. The simulation is performed by a 33-factor design that takes into account the maximum and least limits of the experimental work performed with the 23-factor design. Neural network structures, such as the Feed Forward Neural Network (FFNN), were used to predict tensile and shear strength of tool steel sediments caused by friction.

Next Generation Space Telescope Integrated Science Module Data System

NASA Technical Reports Server (NTRS)

Schnurr, Richard G.; Greenhouse, Matthew A.; Jurotich, Matthew M.; Whitley, Raymond; Kalinowski, Keith J.; Love, Bruce W.; Travis, Jeffrey W.; Long, Knox S.

1999-01-01

The Data system for the Next Generation Space Telescope (NGST) Integrated Science Module (ISIM) is the primary data interface between the spacecraft, telescope, and science instrument systems. This poster includes block diagrams of the ISIM data system and its components derived during the pre-phase A Yardstick feasibility study. The poster details the hardware and software components used to acquire and process science data for the Yardstick instrument compliment, and depicts the baseline external interfaces to science instruments and other systems. This baseline data system is a fully redundant, high performance computing system. Each redundant computer contains three 150 MHz power PC processors. All processors execute a commercially available real time multi-tasking operating system supporting, preemptive multi-tasking, file management and network interfaces. These six processors in the system are networked together. The spacecraft interface baseline is an extension of the network, which links the six processors. The final selection for Processor busses, processor chips, network interfaces, and high-speed data interfaces will be made during mid 2002.

Waveform-based spaceborne GNSS-R wind speed observation: Demonstration and analysis using UK TechDemoSat-1 data

NASA Astrophysics Data System (ADS)

Wang, Feng; Yang, Dongkai; Zhang, Bo; Li, Weiqiang

2018-03-01

This paper explores two types of mathematical functions to fit single- and full-frequency waveform of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R), respectively. The metrics of the waveforms, such as the noise floor, peak magnitude, mid-point position of the leading edge, leading edge slope and trailing edge slope, can be derived from the parameters of the proposed models. Because the quality of the UK TDS-1 data is not at the level required by remote sensing mission, the waveforms buried in noise or from ice/land are removed by defining peak-to-mean ratio, cosine similarity of the waveform before wind speed are retrieved. The single-parameter retrieval models are developed by comparing the peak magnitude, leading edge slope and trailing edge slope derived from the parameters of the proposed models with in situ wind speed from the ASCAT scatterometer. To improve the retrieval accuracy, three types of multi-parameter observations based on the principle component analysis (PCA), minimum variance (MV) estimator and Back Propagation (BP) network are implemented. The results indicate that compared to the best results of the single-parameter observation, the approaches based on the principle component analysis and minimum variance could not significantly improve retrieval accuracy, however, the BP networks obtain improvement with the RMSE of 2.55 m/s and 2.53 m/s for single- and full-frequency waveform, respectively.

Ultra-thin silicon (UTSi) on insulator CMOS transceiver and time-division multiplexed switch chips for smart pixel integration

NASA Astrophysics Data System (ADS)

Zhang, Liping; Sawchuk, Alexander A.

2001-12-01

We describe the design, fabrication and functionality of two different 0.5 micron CMOS optoelectronic integrated circuit (OEIC) chips based on the Peregrine Semiconductor Ultra-Thin Silicon on insulator technology. The Peregrine UTSi silicon- on-sapphire (SOS) technology is a member of the silicon-on- insulator (SOI) family. The low-loss synthetic sapphire substrate is optically transparent and has good thermal conductivity and coefficient of thermal expansion properties, which meet the requirements for flip-chip bonding of VCSELs and other optoelectronic input-output components. One chip contains transceiver and network components, including four channel high-speed CMOS transceiver modules, pseudo-random bit stream (PRBS) generators, a voltage controlled oscillator (VCO) and other test circuits. The transceiver chips can operate in both self-testing mode and networking mode. An on- chip clock and true-single-phase-clock (TSPC) D-flip-flop have been designed to generate a PRBS at over 2.5 Gb/s for the high-speed transceiver arrays to operate in self-testing mode. In the networking mode, an even number of transceiver chips forms a ring network through free-space or fiber ribbon interconnections. The second chip contains four channel optical time-division multiplex (TDM) switches, optical transceiver arrays, an active pixel detector and additional test devices. The eventual applications of these chips will require monolithic OEICs with integrated optical input and output. After fabrication and testing, the CMOS transceiver array dies will be packaged with 850 nm vertical cavity surface emitting lasers (VCSELs), and metal-semiconductor- metal (MSM) or GaAs p-i-n detector die arrays to achieve high- speed optical interconnections. The hybrid technique could be either wire bonding or flip-chip bonding of the CMOS SOS smart-pixel arrays with arrays of VCSELs and photodetectors onto an optoelectronic chip carrier as a multi-chip module (MCM).

High-speed and high-fidelity system and method for collecting network traffic

DOEpatents

Weigle, Eric H [Los Alamos, NM

2010-08-24

A system is provided for the high-speed and high-fidelity collection of network traffic. The system can collect traffic at gigabit-per-second (Gbps) speeds, scale to terabit-per-second (Tbps) speeds, and support additional functions such as real-time network intrusion detection. The present system uses a dedicated operating system for traffic collection to maximize efficiency, scalability, and performance. A scalable infrastructure and apparatus for the present system is provided by splitting the work performed on one host onto multiple hosts. The present system simultaneously addresses the issues of scalability, performance, cost, and adaptability with respect to network monitoring, collection, and other network tasks. In addition to high-speed and high-fidelity network collection, the present system provides a flexible infrastructure to perform virtually any function at high speeds such as real-time network intrusion detection and wide-area network emulation for research purposes.

Ultrahigh-speed ultrahigh-resolution adaptive optics: optical coherence tomography system for in-vivo small animal retinal imaging

NASA Astrophysics Data System (ADS)

Jian, Yifan; Xu, Jing; Zawadzki, Robert J.; Sarunic, Marinko V.

2013-03-01

Small animal models of human retinal diseases are a critical component of vision research. In this report, we present an ultrahigh-resolution ultrahigh-speed adaptive optics optical coherence tomography (AO-OCT) system for small animal retinal imaging (mouse, fish, etc.). We adapted our imaging system to different types of small animals in accordance with the optical properties of their eyes. Results of AO-OCT images of small animal retinas acquired with AO correction are presented. Cellular structures including nerve fiber bundles, capillary networks and detailed double-cone photoreceptors are visualized.

Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

NASA Technical Reports Server (NTRS)

Tobagi, Fouad A.; Dalgic, Ismail; Pang, Joseph

1990-01-01

The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.

In situ health monitoring for bogie systems of CRH380 train on Beijing-Shanghai high-speed railway

NASA Astrophysics Data System (ADS)

Hong, Ming; Wang, Qiang; Su, Zhongqing; Cheng, Li

2014-04-01

Based on the authors' research efforts over the years, an in situ structural health monitoring (SHM) technique taking advantage of guided elastic waves has been developed and deployed via an online diagnosis system. The technique and the system were recently implemented on China's latest high-speed train (CRH380CL) operated on Beijing-Shanghai High-Speed Railway. The system incorporated modularized components including active sensor network, active wave generation, multi-channel data acquisition, signal processing, data fusion, and results presentation. The sensor network, inspired by a new concept—"decentralized standard sensing", was integrated into the bogie frames during the final assembly of CRH380CL, to generate and acquire bogie-guided ultrasonic waves, from which a wide array of signal features were extracted. Fusion of signal features through a diagnostic imaging algorithm led to a graphic illustration of the overall health state of the bogie in a real-time and intuitive manner. The in situ experimentation covered a variety of high-speed train operation events including startup, acceleration/deceleration, full-speed operation (300 km/h), emergency braking, track change, as well as full stop. Mock-up damage affixed to the bogie was identified quantitatively and visualized in images. This in situ testing has demonstrated the feasibility, effectiveness, sensitivity, and reliability of the developed SHM technique and the system towards real-world applications.

New VLBI Observing System 'OCTAVE-Family' to Support VDIF Specifications with 10 GigE for VERA, JVN, and Japanese e-VLBI (OCTAVE)

NASA Astrophysics Data System (ADS)

Oyama, T.; Kono, Y.; Suzuki, S.; Mizuno, S.; Bushimata, T.; Jike, T.; Kawaguchi, N.; Kobayashi, H.; Kimura, M.

2012-12-01

The new VLBI observing system (OCTAVE-Family) has been designed and developed based on the VSI-H and VDIF specifications at NAOJ (National Astronomical Observatory of Japan). It consists of 1) a high speed 8-Gsps 3-bit ADC (OCTAD) enabling us to acquire not only wide intermediate frequencies but also radio frequencies up to 50 GHz, 2) a converter (OCTAVIA) between one 10 GigE port and four 2 Gbps input and output ports conformable to VSI-H, 3) new recorders (OCTADISK and OCTADISK2) at rates of 4.5 Gbps and above 8 Gbps, and 4) a high speed software correlator system (OCTACOR) using GICO3 which was developed by NICT. These OCTAVE systems are connected via 10 GigE network with VDIF and VSI specifications. These components are used for VERA, JVN (Japanese VLBI network), and KJJVC (Korea-Japan Joint VLBI Correlator).

Continuous high speed coherent one-way quantum key distribution.

PubMed

Stucki, Damien; Barreiro, Claudio; Fasel, Sylvain; Gautier, Jean-Daniel; Gay, Olivier; Gisin, Nicolas; Thew, Rob; Thoma, Yann; Trinkler, Patrick; Vannel, Fabien; Zbinden, Hugo

2009-08-03

Quantum key distribution (QKD) is the first commercial quantum technology operating at the level of single quanta and is a leading light for quantum-enabled photonic technologies. However, controlling these quantum optical systems in real world environments presents significant challenges. For the first time, we have brought together three key concepts for future QKD systems: a simple high-speed protocol; high performance detection; and integration both, at the component level and for standard fibre network connectivity. The QKD system is capable of continuous and autonomous operation, generating secret keys in real time. Laboratory and field tests were performed and comparisons made with robust InGaAs avalanche photodiodes and superconducting detectors. We report the first real world implementation of a fully functional QKD system over a 43 dB-loss (150 km) transmission line in the Swisscom fibre optic network where we obtained average real-time distribution rates over 3 hours of 2.5 bps.

Quality of service provision assessment in the healthcare information and telecommunications infrastructures.

PubMed

Babulak, Eduard

2006-01-01

The continuous increase in the complexity and the heterogeneity of corporate and healthcare telecommunications infrastructures will require new assessment methods of quality of service (QoS) provision that are capable of addressing all engineering and social issues with much faster speeds. Speed and accessibility to any information at any time from anywhere will create global communications infrastructures with great performance bottlenecks that may put in danger human lives, power supplies, national economy and security. Regardless of the technology supporting the information flows, the final verdict on the QoS is made by the end user. The users' perception of telecommunications' network infrastructure QoS provision is critical to the successful business management operation of any organization. As a result, it is essential to assess the QoS Provision in the light of user's perception. This article presents a cost effective methodology to assess the user's perception of quality of service provision utilizing the existing Staffordshire University Network (SUN) by adding a component of measurement to the existing model presented by Walker. This paper presents the real examples of CISCO Networking Solutions for Health Care givers and offers a cost effective approach to assess the QoS provision within the campus network, which could be easily adapted to any health care organization or campus network in the world.

Digital optical computers at the optoelectronic computing systems center

NASA Technical Reports Server (NTRS)

Jordan, Harry F.

1991-01-01

The Digital Optical Computing Program within the National Science Foundation Engineering Research Center for Opto-electronic Computing Systems has as its specific goal research on optical computing architectures suitable for use at the highest possible speeds. The program can be targeted toward exploiting the time domain because other programs in the Center are pursuing research on parallel optical systems, exploiting optical interconnection and optical devices and materials. Using a general purpose computing architecture as the focus, we are developing design techniques, tools and architecture for operation at the speed of light limit. Experimental work is being done with the somewhat low speed components currently available but with architectures which will scale up in speed as faster devices are developed. The design algorithms and tools developed for a general purpose, stored program computer are being applied to other systems such as optimally controlled optical communication networks.

Airborne space laser communication system and experiments

NASA Astrophysics Data System (ADS)

Li, Xiao-Ming; Zhang, Li-zhong; Meng, Li-Xin

2015-11-01

Airborne space laser communication is characterized by its high speed, anti-electromagnetic interference, security, easy to assign. It has broad application in the areas of integrated space-ground communication networking, military communication, anti-electromagnetic communication. This paper introduce the component and APT system of the airborne laser communication system design by Changchun university of science and technology base on characteristic of airborne laser communication and Y12 plan, especially introduce the high communication speed and long distance communication experiment of the system that among two Y12 plans. In the experiment got the aim that the max communication distance 144Km, error 10-6 2.5Gbps - 10-7 1.5Gbps capture probability 97%, average capture time 20s. The experiment proving the adaptability of the APT and the high speed long distance communication.

Optimal forwarding ratio on dynamical networks with heterogeneous mobility

NASA Astrophysics Data System (ADS)

Gan, Yu; Tang, Ming; Yang, Hanxin

2013-05-01

Since the discovery of non-Poisson statistics of human mobility trajectories, more attention has been paid to understand the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate packet forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged at small and large high-speed value. It is also interesting to find that a slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from the local structural heterogeneity of low-speed agents.

Distinct sets of locomotor modules control the speed and modes of human locomotion

PubMed Central

Yokoyama, Hikaru; Ogawa, Tetsuya; Kawashima, Noritaka; Shinya, Masahiro; Nakazawa, Kimitaka

2016-01-01

Although recent vertebrate studies have revealed that different spinal networks are recruited in locomotor mode- and speed-dependent manners, it is unknown whether humans share similar neural mechanisms. Here, we tested whether speed- and mode-dependence in the recruitment of human locomotor networks exists or not by statistically extracting locomotor networks. From electromyographic activity during walking and running over a wide speed range, locomotor modules generating basic patterns of muscle activities were extracted using non-negative matrix factorization. The results showed that the number of modules changed depending on the modes and speeds. Different combinations of modules were extracted during walking and running, and at different speeds even during the same locomotor mode. These results strongly suggest that, in humans, different spinal locomotor networks are recruited while walking and running, and even in the same locomotor mode different networks are probably recruited at different speeds. PMID:27805015

Neural Network Modeling of UH-60A Pilot Vibration

NASA Technical Reports Server (NTRS)

Kottapalli, Sesi

2003-01-01

Full-scale flight-test pilot floor vibration is modeled using neural networks and full-scale wind tunnel test data for low speed level flight conditions. Neural network connections between the wind tunnel test data and the tlxee flight test pilot vibration components (vertical, lateral, and longitudinal) are studied. Two full-scale UH-60A Black Hawk databases are used. The first database is the NASMArmy UH-60A Airloads Program flight test database. The second database is the UH-60A rotor-only wind tunnel database that was acquired in the NASA Ames SO- by 120- Foot Wind Tunnel with the Large Rotor Test Apparatus (LRTA). Using neural networks, the flight-test pilot vibration is modeled using the wind tunnel rotating system hub accelerations, and separately, using the hub loads. The results show that the wind tunnel rotating system hub accelerations and the operating parameters can represent the flight test pilot vibration. The six components of the wind tunnel N/rev balance-system hub loads and the operating parameters can also represent the flight test pilot vibration. The present neural network connections can significandy increase the value of wind tunnel testing.

Advanced optical components for next-generation photonic networks

NASA Astrophysics Data System (ADS)

Yoo, S. J. B.

2003-08-01

Future networks will require very high throughput, carrying dominantly data-centric traffic. The role of Photonic Networks employing all-optical systems will become increasingly important in providing scalable bandwidth, agile reconfigurability, and low-power consumptions in the future. In particular, the self-similar nature of data traffic indicates that packet switching and burst switching will be beneficial in the Next Generation Photonic Networks. While the natural conclusion is to pursue Photonic Packet Switching and Photonic Burst Switching systems, there are significant challenges in realizing such a system due to practical limitations in optical component technologies. Lack of a viable all-optical memory technology will continue to drive us towards exploring rapid reconfigurability in the wavelength domain. We will introduce and discuss the advanced optical component technologies behind the Photonic Packet Routing system designed and demonstrated at UC Davis. The system is capable of packet switching and burst switching, as well as circuit switching with 600 psec switching speed and scalability to 42 petabit/sec aggregated switching capacity. By utilizing a combination of rapidly tunable wavelength conversion and a uniform-loss cyclic frequency (ULCF) arrayed waveguide grating router (AWGR), the system is capable of rapidly switching the packets in wavelength, time, and space domains. The label swapping module inside the Photonic Packet Routing system containing a Mach-Zehnder wavelength converter and a narrow-band fiber Bragg-grating achieves all-optical label swapping with optical 2R (potentially 3R) regeneration while maintaining optical transparency for the data payload. By utilizing the advanced optical component technologies, the Photonic Packet Routing system successfully demonstrated error-free, cascaded, multi-hop photonic packet switching and routing with optical-label swapping. This paper will review the advanced optical component technologies and their role in the Next Generation Photonic Networks.

Capillary red blood cell velocimetry by phase-resolved optical coherence tomography

NASA Astrophysics Data System (ADS)

Tang, Jianbo; Erdener, Sefik Evren; Fu, Buyin; Boas, David A.

2018-02-01

Quantitative measurement of blood flow velocity in capillaries is challenging due to their small size (around 5-10 μm), and the discontinuity and single-file feature of RBCs flowing in a capillary. In this work, we present a phase-resolved Optical Coherence Tomography (OCT) method for accurate measurement of the red blood cell (RBC) speed in cerebral capillaries. To account for the discontinuity of RBCs flowing in capillaries, we applied an M-mode scanning strategy that repeated A-scans at each scanning position for an extended time. As the capillary size is comparable to the OCT resolution size (3.5×3.5×3.5μm), we applied a high pass filter to remove the stationary signal component so that the phase information of the dynamic component (i.e. from the moving RBC) could be enhanced to provide an accurate estimate of the RBC axial speed. The phase-resolved OCT method accurately quantifies the axial velocity of RBC's from the phase shift of the dynamic component of the signal. We validated our measurements by RBC passage velocimetry using the signal magnitude of the same OCT time series data. These proposed method of capillary velocimetry proved to be a robust method of mapping capillary RBC speeds across the micro-vascular network.

Systems and technologies for high-speed inter-office/datacenter interface

NASA Astrophysics Data System (ADS)

Sone, Y.; Nishizawa, H.; Yamamoto, S.; Fukutoku, M.; Yoshimatsu, T.

2017-01-01

Emerging requirements for inter-office/inter-datacenter short reach links for data center interconnects (DCI) and metro transport networks have led to various inter-office and inter-datacenter optical interface technologies. These technologies are bringing significant changes to systems and network architectures. In this paper, we present a system and ZR optical interface technologies for DCI and metro transport networks, then introduce the latest challenges facing the system framework. There are two trends in reach extension; one is to use Ethernet and the other is to use digital coherent technologies. The first approach achieves reach extension while using as many existing Ethernet components as possible. It offers low costs as reuses the cost-effective components created for the large Ethernet market. The second approach adopts low-cost and low power coherent DSPs that implement the minimal set long haul transmission functions. This paper introduces an architecture that integrates both trends. The architecture satisfies both datacom and telecom needs with a common control and management interface and automated configuration.

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

Dykstra, Dave; Garzoglio, Gabriele; Kim, Hyunwoo

As of 2012, a number of US Department of Energy (DOE) National Laboratories have access to a 100 Gb/s wide-area network backbone. The ESnet Advanced Networking Initiative (ANI) project is intended to develop a prototype network, based on emerging 100 Gb/s Ethernet technology. The ANI network will support DOE's science research programs. A 100 Gb/s network test bed is a key component of the ANI project. The test bed offers the opportunity for early evaluation of 100Gb/s network infrastructure for supporting the high impact data movement typical of science collaborations and experiments. In order to make effective use of thismore » advanced infrastructure, the applications and middleware currently used by the distributed computing systems of large-scale science need to be adapted and tested within the new environment, with gaps in functionality identified and corrected. As a user of the ANI test bed, Fermilab aims to study the issues related to end-to-end integration and use of 100 Gb/s networks for the event simulation and analysis applications of physics experiments. In this paper we discuss our findings from evaluating existing HEP Physics middleware and application components, including GridFTP, Globus Online, etc. in the high-speed environment. These will include possible recommendations to the system administrators, application and middleware developers on changes that would make production use of the 100 Gb/s networks, including data storage, caching and wide area access.« less

A Continuum Model of Actin Waves in Dictyostelium discoideum

PubMed Central

Khamviwath, Varunyu; Hu, Jifeng; Othmer, Hans G.

2013-01-01

Actin waves are complex dynamical patterns of the dendritic network of filamentous actin in eukaryotes. We developed a model of actin waves in PTEN-deficient Dictyostelium discoideum by deriving an approximation of the dynamics of discrete actin filaments and combining it with a signaling pathway that controls filament branching. This signaling pathway, together with the actin network, contains a positive feedback loop that drives the actin waves. Our model predicts the structure, composition, and dynamics of waves that are consistent with existing experimental evidence, as well as the biochemical dependence on various protein partners. Simulation suggests that actin waves are initiated when local actin network activity, caused by an independent process, exceeds a certain threshold. Moreover, diffusion of proteins that form a positive feedback loop with the actin network alone is sufficient for propagation of actin waves at the observed speed of . Decay of the wave back can be caused by scarcity of network components, and the shape of actin waves is highly dependent on the filament disassembly rate. The model allows retraction of actin waves and captures formation of new wave fronts in broken waves. Our results demonstrate that a delicate balance between a positive feedback, filament disassembly, and local availability of network components is essential for the complex dynamics of actin waves. PMID:23741312

Method and system for determining induction motor speed

DOEpatents

Parlos, Alexander G.; Bharadwaj, Raj M.

2004-03-30

A non-linear, semi-parametric neural network-based adaptive filter is utilized to determine the dynamic speed of a rotating rotor within an induction motor, without the explicit use of a speed sensor, such as a tachometer, is disclosed. The neural network-based filter is developed using actual motor current measurements, voltage measurements, and nameplate information. The neural network-based adaptive filter is trained using an estimated speed calculator derived from the actual current and voltage measurements. The neural network-based adaptive filter uses voltage and current measurements to determine the instantaneous speed of a rotating rotor. The neural network-based adaptive filter also includes an on-line adaptation scheme that permits the filter to be readily adapted for new operating conditions during operations.

High-speed quantum networking by ship

NASA Astrophysics Data System (ADS)

Devitt, Simon J.; Greentree, Andrew D.; Stephens, Ashley M.; van Meter, Rodney

2016-11-01

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet.

High-speed quantum networking by ship

PubMed Central

Devitt, Simon J.; Greentree, Andrew D.; Stephens, Ashley M.; Van Meter, Rodney

2016-01-01

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet. PMID:27805001

High-speed quantum networking by ship.

PubMed

Devitt, Simon J; Greentree, Andrew D; Stephens, Ashley M; Van Meter, Rodney

2016-11-02

Networked entanglement is an essential component for a plethora of quantum computation and communication protocols. Direct transmission of quantum signals over long distances is prevented by fibre attenuation and the no-cloning theorem, motivating the development of quantum repeaters, designed to purify entanglement, extending its range. Quantum repeaters have been demonstrated over short distances, but error-corrected, global repeater networks with high bandwidth require new technology. Here we show that error corrected quantum memories installed in cargo containers and carried by ship can provide a exible connection between local networks, enabling low-latency, high-fidelity quantum communication across global distances at higher bandwidths than previously proposed. With demonstrations of technology with sufficient fidelity to enable topological error-correction, implementation of the quantum memories is within reach, and bandwidth increases with improvements in fabrication. Our approach to quantum networking avoids technological restrictions of repeater deployment, providing an alternate path to a worldwide Quantum Internet.

Plasmonic integrated circuits comprising metal waveguides, multiplexer/demultiplexer, detectors, and logic circuits on a silicon substrate

NASA Astrophysics Data System (ADS)

Fukuda, M.; Ota, M.; Sumimura, A.; Okahisa, S.; Ito, M.; Ishii, Y.; Ishiyama, T.

2017-05-01

A plasmonic integrated circuit configuration comprising plasmonic and electronic components is presented and the feasibility for high-speed signal processing applications is discussed. In integrated circuits, plasmonic signals transmit data at high transfer rates with light velocity. Plasmonic and electronic components such as wavelength-divisionmultiplexing (WDM) networks comprising metal wires, plasmonic multiplexers/demultiplexers, and crossing metal wires are connected via plasmonic waveguides on the nanometer or micrometer scales. To merge plasmonic and electronic components, several types of plasmonic components were developed. To ensure that the plasmonic components could be easily fabricated and monolithically integrated onto a silicon substrate using silicon complementary metal-oxide-semiconductor (CMOS)-compatible processes, the components were fabricated on a Si substrate and made from silicon, silicon oxides, and metal; no other materials were used in the fabrication. The plasmonic components operated in the 1300- and 1550-nm-wavelength bands, which are typically employed in optical fiber communication systems. The plasmonic logic circuits were formed by patterning a silicon oxide film on a metal film, and the operation as a half adder was confirmed. The computed plasmonic signals can propagate through the plasmonic WDM networks and be connected to electronic integrated circuits at high data-transfer rates.

Application of new electro-optic technology to Space Station Freedom data management system

NASA Technical Reports Server (NTRS)

Husbands, C. R.; Girard, M. M.

1993-01-01

A low risk design methodology to permit the local bus structures to support increased data carrying capacities and to speed messages and data flow between nodes or stations on the Space Station Freedom Data Management System in anticipation of growing requirements was evaluated and recommended. The recommended design employs a collateral fiber optic technique that follows a NATO avionic standard that is developed, tested, and available. Application of this process will permit a potential 25 fold increase in data transfer performance on the local wire bus network with a fiber optic network, maintaining the functionality of the low-speed bus and supporting all of the redundant transmission and fault detection capabilities designed into the existing system. The application of wavelength division multiplexing (WDM) technology to both the local data bus and global data bus segments of the Data Management System to support anticipated additional highspeed data transmission requirements was also examined. Techniques were examined to provide a dual wavelength implementation of the fiber optic collateral networks. This dual wavelength implementation would permit each local bus to support two simultaneous high-speed transfers on the same fiber optic bus structure and operate within the limits of the existing protocol standard. A second WDM study examined the use of spectral sliced technology to provide a fourfold increase in the Fiber Distributed Data Interface (FDDI) global bus networks without requiring modifications to the existing installed cable plant. Computer simulations presented indicated that this data rate improvement can be achieved with commercially available optical components.

The creation and early implementation of a high speed fiber optic network for a university health sciences center.

PubMed Central

Schueler, J. D.; Mitchell, J. A.; Forbes, S. M.; Neely, R. C.; Goodman, R. J.; Branson, D. K.

1991-01-01

In late 1989 the University of Missouri Health Sciences Center began the process of creating an extensive fiber optic network throughout its facilities, with the intent to provide networked computer access to anyone in the Center desiring such access, regardless of geographic location or organizational affiliation. A committee representing all disciplines within the Center produced and, in conjunction with independent consultants, approved a comprehensive design for the network. Installation of network backbone components commenced in the second half of 1990 and was completed in early 1991. As the network entered its initial phases of operation, the first realities of this important new resource began to manifest themselves as enhanced functional capacity in the Health Sciences Center. This paper describes the development of the network, with emphasis on its design criteria, installation, early operation, and management. Also included are discussions on its organizational impact and its evolving significance as a medical community resource. PMID:1807660

Orbit Determination Using Vinti’s Solution

DTIC Science & Technology

2016-09-15

Surveillance Network STK Systems Tool Kit TBP Two Body Problem TLE Two-line Element Set xv Acronym Definition UKF Unscented Kalman Filter WPAFB Wright...simplicity, stability, and speed. On the other hand, Kalman filters would be best suited for sequential estimation of stochastic or random components of a...be likened to how an Unscented Kalman Filter samples a system’s nonlinearities directly, avoiding linearizing the dynamics in the partials matrices

A comparison of high-speed links, their commercial support and ongoing R&D activities

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

Gonzalez, H.L.; Barsotti, E.; Zimmermann, S.

Technological advances and a demanding market have forced the development of higher bandwidth communication standards for networks, data links and busses. Most of these emerging standards are gathering enough momentum that their widespread availability and lower prices are anticipated. The hardware and software that support the physical media for most of these links is currently available, allowing the user community to implement fairly high-bandwidth data links and networks with commercial components. Also, switches needed to support these networks are available or being developed. The commercial suppose of high-bandwidth data links, networks and switching fabrics provides a powerful base for themore » implementation of high-bandwidth data acquisition systems. A large data acquisition system like the one for the Solenoidal Detector Collaboration (SDC) at the SSC can benefit from links and networks that support an integrated systems engineering approach, for initialization, downloading, diagnostics, monitoring, hardware integration and event data readout. The issue that our current work addresses is the possibility of having a channel/network that satisfies the requirements of an integrated data acquisition system. In this paper we present a brief description of high-speed communication links and protocols that we consider of interest for high energy physic High Performance Parallel Interface (HIPPI). Serial HIPPI, Fibre Channel (FC) and Scalable Coherent Interface (SCI). In addition, the initial work required to implement an SDC-like data acquisition system is described.« less

A comparison of high-speed links, their commercial support and ongoing R D activities

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

Gonzalez, H.L.; Barsotti, E.; Zimmermann, S.

Technological advances and a demanding market have forced the development of higher bandwidth communication standards for networks, data links and busses. Most of these emerging standards are gathering enough momentum that their widespread availability and lower prices are anticipated. The hardware and software that support the physical media for most of these links is currently available, allowing the user community to implement fairly high-bandwidth data links and networks with commercial components. Also, switches needed to support these networks are available or being developed. The commercial suppose of high-bandwidth data links, networks and switching fabrics provides a powerful base for themore » implementation of high-bandwidth data acquisition systems. A large data acquisition system like the one for the Solenoidal Detector Collaboration (SDC) at the SSC can benefit from links and networks that support an integrated systems engineering approach, for initialization, downloading, diagnostics, monitoring, hardware integration and event data readout. The issue that our current work addresses is the possibility of having a channel/network that satisfies the requirements of an integrated data acquisition system. In this paper we present a brief description of high-speed communication links and protocols that we consider of interest for high energy physic High Performance Parallel Interface (HIPPI). Serial HIPPI, Fibre Channel (FC) and Scalable Coherent Interface (SCI). In addition, the initial work required to implement an SDC-like data acquisition system is described.« less

A Study of the IEEE 802.16 MAC Layer and its Utility in Augmenting the ADNS Architecture to Provide Adaptable Intra-Strike Group High-Speed Packet Switched Data, Imagery, and Voice Communications

DTIC Science & Technology

2005-09-01

This research explores the need for a high throughput, high speed network for use in a network centric wartime environment and how commercial...Automated Digital Network System (ADNS). This research explores the need for a high-throughput, high-speed network for use in a network centric ...1 C. DEPARTMENT OF DEFENSE (DOD) DESIRED END STATE ..............2 1. DOD Transformation to Network Centric Warfare (NCW) Operations

Application of Bluetooth technology to rural freeway speed data collection ; executive summary report.

DOT National Transportation Integrated Search

2012-10-01

The Ohio Department of Transportation (ODOT) currently employs a network of side fire speed radar devices to measure travel speeds and travel times on their interstate network. While these devices measure the instantaneous spot speed, segment level s...

Soft optics in intelligent optical networks

NASA Astrophysics Data System (ADS)

Shue, Chikong; Cao, Yang

2001-10-01

In addition to the recent advances in Hard-optics that pushes the optical transmission speed, distance, wave density and optical switching capacity, Soft-optics provides the necessary intelligence and control software that reduces operational costs, increase efficiency, and enhances revenue generating services by automating optimal optical circuit placement and restoration, and enabling value-added new services like Optical VPN. This paper describes the advances in 1) Overall Hard-optics and Soft-optics 2) Layered hierarchy of Soft-optics 3) Component of Soft-optics, including hard-optics drivers, Management Soft-optics, Routing Soft-optics and System Soft-optics 4) Key component of Routing and System Soft-optics, namely optical routing and signaling (including UNI/NNI and GMPLS signaling). In summary, the soft-optics on a new generation of OXC's enables Intelligent Optical Networks to provide just-in-time service delivery and fast restoration, and real-time capacity management that eliminates stranded bandwidth. It reduces operational costs and provides new revenue opportunities.

Firewall systems: the next generation

NASA Astrophysics Data System (ADS)

McGhie, Lynda L.

1996-01-01

To be competitive in today's globally connected marketplace, a company must ensure that their internal network security methodologies and supporting policies are current and reflect an overall understanding of today's technology and its resultant threats. Further, an integrated approach to information security should ensure that new ways of sharing information and doing business are accommodated; such as electronic commerce, high speed public broadband network services, and the federally sponsored National Information Infrastructure. There are many challenges, and success is determined by the establishment of a solid and firm baseline security architecture that accommodate today's external connectivity requirements, provides transitional solutions that integrate with evolving and dynamic technologies, and ultimately acknowledges both the strategic and tactical goals of an evolving network security architecture and firewall system. This paper explores the evolution of external network connectivity requirements, the associated challenges and the subsequent development and evolution of firewall security systems. It makes the assumption that a firewall is a set of integrated and interoperable components, coming together to form a `SYSTEM' and must be designed, implement and managed as such. A progressive firewall model will be utilized to illustrates the evolution of firewall systems from earlier models utilizing separate physical networks, to today's multi-component firewall systems enabling secure heterogeneous and multi-protocol interfaces.

Trend on High-speed Power Line Communication Technology

NASA Astrophysics Data System (ADS)

Ogawa, Osamu

High-speed power line communication (PLC) is useful technology to easily build the communication networks, because construction of new infrastructure is not necessary. In Europe and America, PLC has been used for broadband networks since the beginning of 21th century. In Japan, high-speed PLC was deregulated only indoor usage in 2006. Afterward it has been widely used for home area network, LAN in hotels and school buildings and so on. And recently, PLC is greatly concerned as communication technology for smart grid network. In this paper, the author surveys the high-speed PLC technology and its current status.

Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

PubMed

Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

2015-01-01

The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

Recent advancements towards green optical networks

NASA Astrophysics Data System (ADS)

Davidson, Alan; Glesk, Ivan; Buis, Adrianus; Wang, Junjia; Chen, Lawrence

2014-12-01

Recent years have seen a rapid growth in demand for ultra high speed data transmission with end users expecting fast, high bandwidth network access. With this rapid growth in demand, data centres are under pressure to provide ever increasing data rates through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present technology based on well-established CMOS technology is becoming increasingly difficult to scale and consequently data networks are struggling to satisfy current network demand. In this paper the interrelated issues of electronic scalability, power consumption, limited copper interconnect bandwidth and the limited speed of CMOS electronics will be explored alongside the tremendous bandwidth potential of optical fibre based photonic networks. Some applications of photonics to help alleviate the speed and latency in data networks will be discussed.

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

XUNET experimental high-speed network testbed CRADA 1136, DOE TTI No. 92-MULT-020-B2

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

Palmer, R.E.

1996-04-01

XUNET is a research program with AT&T and other partners to study high-speed wide area communication between local area networks over a backbone using Asynchronous Transfer Mode (ATM) switches. Important goals of the project are to develop software techniques for network control and management, and applications for high-speed networks. The project entails building a testbed between member sites to explore performance issues for mixed network traffic such as congestion control, multimedia communications protocols, segmentation and reassembly of ATM cells, and overall data throughput rates.

Analysis of the electrical harmonic characteristics of a slip recovery variable speed generating system for wind turbine applications

NASA Astrophysics Data System (ADS)

Herrera, J. I.; Reddoch, T. W.

1988-02-01

Variable speed electric generating technology can enhance the general use of wind energy in electric utility applications. This enhancement results from two characteristic properties of variable speed wind turbine generators: an improvement in drive train damping characteristics, which results in reduced structural loading on the entire wind turbine system, and an improvement in the overall efficiency by using a more sophisticated electrical generator. Electronic converter systems are the focus of this investigation -- in particular, the properties of a wound-rotor induction generator with the slip recovery system and direct-current link converter. Experience with solid-state converter systems in large wind turbines is extremely limited. This report presents measurements of electrical performances of the slip recovery system and is limited to the terminal characteristics of the system. Variable speed generating systems working effectively in utility applications will require a satisfactory interface between the turbine/generator pair and the utility network. The electrical testing described herein focuses largely on the interface characteristics of the generating system. A MOD-O wind turbine was connected to a very strong system; thus, the voltage distortion was low and the total harmonic distortion in the utility voltage was less than 3 percent (within the 5 percent limit required by most utilities). The largest voltage component of a frequency below 60 Hz was 40 dB down from the 60-Hz less than component.

A novel application of artificial neural network for wind speed estimation

NASA Astrophysics Data System (ADS)

Fang, Da; Wang, Jianzhou

2017-05-01

Providing accurate multi-steps wind speed estimation models has increasing significance, because of the important technical and economic impacts of wind speed on power grid security and environment benefits. In this study, the combined strategies for wind speed forecasting are proposed based on an intelligent data processing system using artificial neural network (ANN). Generalized regression neural network and Elman neural network are employed to form two hybrid models. The approach employs one of ANN to model the samples achieving data denoising and assimilation and apply the other to predict wind speed using the pre-processed samples. The proposed method is demonstrated in terms of the predicting improvements of the hybrid models compared with single ANN and the typical forecasting method. To give sufficient cases for the study, four observation sites with monthly average wind speed of four given years in Western China were used to test the models. Multiple evaluation methods demonstrated that the proposed method provides a promising alternative technique in monthly average wind speed estimation.

Reliability analysis of degradable networks with modified BPR

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Jia, Bin; Zhu, Hua-Bing

2017-12-01

In this paper, the effect of the speed limit on degradable networks with capacity restrictions and the forced flow is investigated. The link performance function considering the road capacity is proposed. Additionally, the probability density distribution and the cumulative distribution of link travel time are introduced in the degradable network. By the mean of distinguishing the value of the speed limit, four cases are discussed, respectively. Means and variances of link travel time and route one of the degradable road network are calculated. Besides, by the mean of performing numerical simulation experiments in a specific network, it is found that the speed limit strategy can reduce the travel time budget and mean travel time of link and route. Moreover, it reveals that the speed limit strategy can cut down variances of the travel time of networks to some extent.

Mapping a sensory-motor network onto a structural and functional ground plan in the hindbrain.

PubMed

Koyama, Minoru; Kinkhabwala, Amina; Satou, Chie; Higashijima, Shin-ichi; Fetcho, Joseph

2011-01-18

The hindbrain of larval zebrafish contains a relatively simple ground plan in which the neurons throughout it are arranged into stripes that represent broad neuronal classes that differ in transmitter identity, morphology, and transcription factor expression. Within the stripes, neurons are stacked continuously according to age as well as structural and functional properties, such as axonal extent, input resistance, and the speed at which they are recruited during movements. Here we address the question of how particular networks among the many different sensory-motor networks in hindbrain arise from such an orderly plan. We use a combination of transgenic lines and pairwise patch recording to identify excitatory and inhibitory interneurons in the hindbrain network for escape behaviors initiated by the Mauthner cell. We map this network onto the ground plan to show that an individual hindbrain network is built by drawing components in predictable ways from the underlying broad patterning of cell types stacked within stripes according to their age and structural and functional properties. Many different specialized hindbrain networks may arise similarly from a simple early patterning.

Brain networks involved in tactile speed classification of moving dot patterns: the effects of speed and dot periodicity

PubMed Central

Yang, Jiajia; Kitada, Ryo; Kochiyama, Takanori; Yu, Yinghua; Makita, Kai; Araki, Yuta; Wu, Jinglong; Sadato, Norihiro

2017-01-01

Humans are able to judge the speed of an object’s motion by touch. Research has suggested that tactile judgment of speed is influenced by physical properties of the moving object, though the neural mechanisms underlying this process remain poorly understood. In the present study, functional magnetic resonance imaging was used to investigate brain networks that may be involved in tactile speed classification and how such networks may be affected by an object’s texture. Participants were asked to classify the speed of 2-D raised dot patterns passing under their right middle finger. Activity in the parietal operculum, insula, and inferior and superior frontal gyri was positively related to the motion speed of dot patterns. Activity in the postcentral gyrus and superior parietal lobule was sensitive to dot periodicity. Psycho-physiological interaction (PPI) analysis revealed that dot periodicity modulated functional connectivity between the parietal operculum (related to speed) and postcentral gyrus (related to dot periodicity). These results suggest that texture-sensitive activity in the primary somatosensory cortex and superior parietal lobule influences brain networks associated with tactually-extracted motion speed. Such effects may be related to the influence of surface texture on tactile speed judgment. PMID:28145505

Upper Mantle Shear Wave Structure Beneath North America From Multi-mode Surface Wave Tomography

NASA Astrophysics Data System (ADS)

Yoshizawa, K.; Ekström, G.

2008-12-01

The upper mantle structure beneath the North American continent has been investigated from measurements of multi-mode phase speeds of Love and Rayleigh waves. To estimate fundamental-mode and higher-mode phase speeds of surface waves from a single seismogram at regional distances, we have employed a method of nonlinear waveform fitting based on a direct model-parameter search using the neighbourhood algorithm (Yoshizawa & Kennett, 2002). The method of the waveform analysis has been fully automated by employing empirical quantitative measures for evaluating the accuracy/reliability of estimated multi-mode phase dispersion curves, and thus it is helpful in processing the dramatically increasing numbers of seismic data from the latest regional networks such as USArray. As a first step toward modeling the regional anisotropic shear-wave velocity structure of the North American upper mantle with extended vertical resolution, we have applied the method to long-period three-component records of seismic stations in North America, which mostly comprise the GSN and US regional networks as well as the permanent and transportable USArray stations distributed by the IRIS DMC. Preliminary multi-mode phase-speed models show large-scale patterns of isotropic heterogeneity, such as a strong velocity contrast between the western and central/eastern United States, which are consistent with the recent global and regional models (e.g., Marone, et al. 2007; Nettles & Dziewonski, 2008). We will also discuss radial anisotropy of shear wave speed beneath North America from multi-mode dispersion measurements of Love and Rayleigh waves.

CATO: a CAD tool for intelligent design of optical networks and interconnects

NASA Astrophysics Data System (ADS)

Chlamtac, Imrich; Ciesielski, Maciej; Fumagalli, Andrea F.; Ruszczyk, Chester; Wedzinga, Gosse

1997-10-01

Increasing communication speed requirements have created a great interest in very high speed optical and all-optical networks and interconnects. The design of these optical systems is a highly complex task, requiring the simultaneous optimization of various parts of the system, ranging from optical components' characteristics to access protocol techniques. Currently there are no computer aided design (CAD) tools on the market to support the interrelated design of all parts of optical communication systems, thus the designer has to rely on costly and time consuming testbed evaluations. The objective of the CATO (CAD tool for optical networks and interconnects) project is to develop a prototype of an intelligent CAD tool for the specification, design, simulation and optimization of optical communication networks. CATO allows the user to build an abstract, possible incomplete, model of the system, and determine its expected performance. Based on design constraints provided by the user, CATO will automatically complete an optimum design, using mathematical programming techniques, intelligent search methods and artificial intelligence (AI). Initial design and testing of a CATO prototype (CATO-1) has been completed recently. The objective was to prove the feasibility of combining AI techniques, simulation techniques, an optical device library and a graphical user interface into a flexible CAD tool for obtaining optimal communication network designs in terms of system cost and performance. CATO-1 is an experimental tool for designing packet-switching wavelength division multiplexing all-optical communication systems using a LAN/MAN ring topology as the underlying network. The two specific AI algorithms incorporated are simulated annealing and a genetic algorithm. CATO-1 finds the optimal number of transceivers for each network node, using an objective function that includes the cost of the devices and the overall system performance.

Efficient spiking neural network model of pattern motion selectivity in visual cortex.

PubMed

Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

2014-07-01

Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

Permeability Estimation of Rock Reservoir Based on PCA and Elman Neural Networks

NASA Astrophysics Data System (ADS)

Shi, Ying; Jian, Shaoyong

2018-03-01

an intelligent method which based on fuzzy neural networks with PCA algorithm, is proposed to estimate the permeability of rock reservoir. First, the dimensionality reduction process is utilized for these parameters by principal component analysis method. Further, the mapping relationship between rock slice characteristic parameters and permeability had been found through fuzzy neural networks. The estimation validity and reliability for this method were tested with practical data from Yan’an region in Ordos Basin. The result showed that the average relative errors of permeability estimation for this method is 6.25%, and this method had the better convergence speed and more accuracy than other. Therefore, by using the cheap rock slice related information, the permeability of rock reservoir can be estimated efficiently and accurately, and it is of high reliability, practicability and application prospect.

The convergence analysis of SpikeProp algorithm with smoothing L1∕2 regularization.

PubMed

Zhao, Junhong; Zurada, Jacek M; Yang, Jie; Wu, Wei

2018-07-01

Unlike the first and the second generation artificial neural networks, spiking neural networks (SNNs) model the human brain by incorporating not only synaptic state but also a temporal component into their operating model. However, their intrinsic properties require expensive computation during training. This paper presents a novel algorithm to SpikeProp for SNN by introducing smoothing L 1∕2 regularization term into the error function. This algorithm makes the network structure sparse, with some smaller weights that can be eventually removed. Meanwhile, the convergence of this algorithm is proved under some reasonable conditions. The proposed algorithms have been tested for the convergence speed, the convergence rate and the generalization on the classical XOR-problem, Iris problem and Wisconsin Breast Cancer classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Networking via wireless bridge produces greater speed and flexibility, lowers cost.

PubMed

1998-10-01

Wireless computer networking. Computer connectivity is essential in today's high-tech health care industry. But telephone lines aren't fast enough, and high-speed connections like T-1 lines are costly. Read about an Ohio community hospital that installed a wireless network "bridge" to connect buildings that are miles apart, creating a reliable high-speed link that costs one-tenth of a T-1 line.

The science of computing - Parallel computation

NASA Technical Reports Server (NTRS)

Denning, P. J.

1985-01-01

Although parallel computation architectures have been known for computers since the 1920s, it was only in the 1970s that microelectronic components technologies advanced to the point where it became feasible to incorporate multiple processors in one machine. Concommitantly, the development of algorithms for parallel processing also lagged due to hardware limitations. The speed of computing with solid-state chips is limited by gate switching delays. The physical limit implies that a 1 Gflop operational speed is the maximum for sequential processors. A computer recently introduced features a 'hypercube' architecture with 128 processors connected in networks at 5, 6 or 7 points per grid, depending on the design choice. Its computing speed rivals that of supercomputers, but at a fraction of the cost. The added speed with less hardware is due to parallel processing, which utilizes algorithms representing different parts of an equation that can be broken into simpler statements and processed simultaneously. Present, highly developed computer languages like FORTRAN, PASCAL, COBOL, etc., rely on sequential instructions. Thus, increased emphasis will now be directed at parallel processing algorithms to exploit the new architectures.

Optical calibration of a new two-way optical component network analyzer

NASA Astrophysics Data System (ADS)

Tsao, Shyh-Lin; Ko, Chih-Han; Liou, Tai-Chi

2003-12-01

High-speed fiber communications show promising results recently [1,2]. Using of lightwave technology for measuring S parameters with optical component becoming important. For this purpose to develop a two-way network analyzer has been reported [3]. In this paper, we report the calibration method of a new two-way lightwave component analyze for applying in fiber optical signal processing elements. The background error and circulator wavelength response are all calibrated. We have designed a new probe for two-way optical component network analyzer. The probe is composed of frequency division multiplexer(FDM), electrical circulator, optical transmitter, optical receiver, and an optical circulator. We design 2-D grating structures as frequency division. The PCB we adopted is Kinstan GD1530 160 whose relative dielectric constantɛ= 4.3, length= 120 mm, and height= 1.8 mm. Two dimensional non-metal covered array square pads are designed on FR4 Glass-Epoxy board for FDM. The FDM can be achieved by the two dimensional non-metalized covered array square pads. Finally we use a single fiber ring resonator filter as our test samples. Comparing the numerical and experimental results, test the device we made. References [1] D. D. Curtis and E. E. Ames,"Optical Test Set for Microwave Fiber-Optic Network Analysis," IEEE Transactions on Microwave Theory and Techniques. , vol. 38, NO.5, pp. 552-559, 1990. [2] J. A. C. Bingham,"Multicarrier modulation for data transmission: an idea whose time has come," IEEE Commun. Magazine., pp. 5 -14, 1990. [3] M. Nakazawa, K. Suzuki, and Y. Kimura, " 3.2-5 Gbps 100km error-free soliton transmission with erbium amplifiers and repenters," IEEE Photonics Tech Lett.,vol.2,pp.216-219,1990.

Traffic sign recognition based on deep convolutional neural network

NASA Astrophysics Data System (ADS)

Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

2017-11-01

Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

Analysis of the electrical harmonic characteristics of a slip recovery variable speed generating system for wind turbine applications

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

Herrera, J.I.; Reddoch, T.W.

1988-02-01

Variable speed electric generating technology can enhance the general use of wind energy in electric utility applications. This enhancement results from two characteristic properties of variable speed wind turbine generators: an improvement in drive train damping characteristics, which results in reduced structural loading on the entire wind turbine system, and an improvement in the overall efficiency by using a more sophisticated electrical generator. Electronic converter systems are the focus of this investigation -- in particular, the properties of a wound-rotor induction generator with the slip recovery system and direct-current link converter. Experience with solid-state converter systems in large wind turbinesmore » is extremely limited. This report presents measurements of electrical performances of the slip recovery system and is limited to the terminal characteristics of the system. Variable speed generating systems working effectively in utility applications will require a satisfactory interface between the turbine/generator pair and the utility network. The electrical testing described herein focuses largely on the interface characteristics of the generating system. A MOD-O wind turbine was connected to a very strong system; thus, the voltage distortion was low and the total harmonic distortion in the utility voltage was less than 3% (within the 5% limit required by most utilities). The largest voltage component of a frequency below 60 Hz was 40 dB down from the 60-Hz< component. 8 refs., 14 figs., 8 tabs.« less

Neural networks supporting switching, hypothesis testing, and rule application

PubMed Central

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S.; Seger, Carol A.

2015-01-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example “choose the blue letter.” Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. PMID:26197092

Neural networks supporting switching, hypothesis testing, and rule application.

PubMed

Liu, Zhiya; Braunlich, Kurt; Wehe, Hillary S; Seger, Carol A

2015-10-01

We identified dynamic changes in recruitment of neural connectivity networks across three phases of a flexible rule learning and set-shifting task similar to the Wisconsin Card Sort Task: switching, rule learning via hypothesis testing, and rule application. During fMRI scanning, subjects viewed pairs of stimuli that differed across four dimensions (letter, color, size, screen location), chose one stimulus, and received feedback. Subjects were informed that the correct choice was determined by a simple unidimensional rule, for example "choose the blue letter". Once each rule had been learned and correctly applied for 4-7 trials, subjects were cued via either negative feedback or visual cues to switch to learning a new rule. Task performance was divided into three phases: Switching (first trial after receiving the switch cue), hypothesis testing (subsequent trials through the last error trial), and rule application (correct responding after the rule was learned). We used both univariate analysis to characterize activity occurring within specific regions of the brain, and a multivariate method, constrained principal component analysis for fMRI (fMRI-CPCA), to investigate how distributed regions coordinate to subserve different processes. As hypothesized, switching was subserved by a limbic network including the ventral striatum, thalamus, and parahippocampal gyrus, in conjunction with cortical salience network regions including the anterior cingulate and frontoinsular cortex. Activity in the ventral striatum was associated with switching regardless of how switching was cued; visually cued shifts were associated with additional visual cortical activity. After switching, as subjects moved into the hypothesis testing phase, a broad fronto-parietal-striatal network (associated with the cognitive control, dorsal attention, and salience networks) increased in activity. This network was sensitive to rule learning speed, with greater extended activity for the slowest learning speed late in the time course of learning. As subjects shifted from hypothesis testing to rule application, activity in this network decreased and activity in the somatomotor and default mode networks increased. Copyright © 2015 Elsevier Ltd. All rights reserved.

Scientific Visualization in High Speed Network Environments

NASA Technical Reports Server (NTRS)

Vaziri, Arsi; Kutler, Paul (Technical Monitor)

1997-01-01

In several cases, new visualization techniques have vastly increased the researcher's ability to analyze and comprehend data. Similarly, the role of networks in providing an efficient supercomputing environment have become more critical and continue to grow at a faster rate than the increase in the processing capabilities of supercomputers. A close relationship between scientific visualization and high-speed networks in providing an important link to support efficient supercomputing is identified. The two technologies are driven by the increasing complexities and volume of supercomputer data. The interaction of scientific visualization and high-speed networks in a Computational Fluid Dynamics simulation/visualization environment are given. Current capabilities supported by high speed networks, supercomputers, and high-performance graphics workstations at the Numerical Aerodynamic Simulation Facility (NAS) at NASA Ames Research Center are described. Applied research in providing a supercomputer visualization environment to support future computational requirements are summarized.

Thermal Error Test and Intelligent Modeling Research on the Spindle of High Speed CNC Machine Tools

NASA Astrophysics Data System (ADS)

Luo, Zhonghui; Peng, Bin; Xiao, Qijun; Bai, Lu

2018-03-01

Thermal error is the main factor affecting the accuracy of precision machining. Through experiments, this paper studies the thermal error test and intelligent modeling for the spindle of vertical high speed CNC machine tools in respect of current research focuses on thermal error of machine tool. Several testing devices for thermal error are designed, of which 7 temperature sensors are used to measure the temperature of machine tool spindle system and 2 displacement sensors are used to detect the thermal error displacement. A thermal error compensation model, which has a good ability in inversion prediction, is established by applying the principal component analysis technology, optimizing the temperature measuring points, extracting the characteristic values closely associated with the thermal error displacement, and using the artificial neural network technology.

The Brave New World of Wireless Technologies: A Primer for Educators.

ERIC Educational Resources Information Center

Boerner, Gerald L.

2002-01-01

Discusses the use of wireless local area networks (WLANs) on college campuses. Highlights include traditional wired networks; cost, speed, and reliability; wireless networking standards; mobility; installation speed, simplicity, and flexibility; reduced cost of ownership; scalability; security issues; and a glossary of WLAN terms. (LRW)

A network-based training environment: a medical image processing paradigm.

PubMed

Costaridou, L; Panayiotakis, G; Sakellaropoulos, P; Cavouras, D; Dimopoulos, J

1998-01-01

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

Extinction Dynamics and Control in Adaptive Networks

NASA Astrophysics Data System (ADS)

Schwartz, Ira; Shaw, Leah; Hindes, Jason

Disease control is of paramount importance in public health. Moreover, models of disease spread are an important component in implementing effective vaccination and treatment campaigns. However, human behavior in response to an outbreak has only recently been included in epidemic models on networks. Here we develop the mathematical machinery to describe the dynamics of extinction in finite populations that include human adaptive behavior. The formalism enables us to compute the optimal, fluctuation-induced path to extinction, and predict the average extinction time in adaptive networks as a function of the adaptation rate. We find that both observables have several unique scalings depending on the relative speed of infection and adaptivity. Finally, we discuss how the theory can be used to design optimal control programs in general networks, by coupling the effective force of noise with treatment and human behavior. Research supported by U.S. Naval Research Laboratory funding (Grant No. N0001414WX00023) and the Office of Naval Research (Grant No. N0001414WX20610).

Thalamic structures and associated cognitive functions: Relations with age and aging.

PubMed

Fama, Rosemary; Sullivan, Edith V

2015-07-01

The thalamus, with its cortical, subcortical, and cerebellar connections, is a critical node in networks supporting cognitive functions known to decline in normal aging, including component processes of memory and executive functions of attention and information processing. The macrostructure, microstructure, and neural connectivity of the thalamus changes across the adult lifespan. Structural and functional magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) have demonstrated, regional thalamic volume shrinkage and microstructural degradation, with anterior regions generally more compromised than posterior regions. The integrity of selective thalamic nuclei and projections decline with advancing age, particularly those in thalamofrontal, thalamoparietal, and thalamolimbic networks. This review presents studies that assess the relations between age and aging and the structure, function, and connectivity of the thalamus and associated neural networks and focuses on their relations with processes of attention, speed of information processing, and working and episodic memory. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intra-building telecommunications cabling standards for Sandia National Laboratories, New Mexico

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

Adams, R.L.

1993-08-01

This document establishes a working standard for all telecommunications cable installations at Sandia National Laboratories, New Mexico. It is based on recent national commercial cabling standards. The topics addressed are Secure and Open/Restricted Access telecommunications environments and both twisted-pair and optical-fiber components of communications media. Some of the state-of-the-art technologies that will be supported by the intrabuilding cable infrastructure are Circuit and Packet Switched Networks (PBX/5ESS Voice and Low-Speed Data), Local Area Networks (Ethernet, Token Ring, Fiber and Copper Distributed Data Interface), and Wide Area Networks (Asynchronous Transfer Mode). These technologies can be delivered to every desk and can transportmore » data at rates sufficient to support all existing applications (such as Voice, Text and graphics, Still Images, Full-motion Video), as well as applications to be defined in the future.« less

Hierarchy Bayesian model based services awareness of high-speed optical access networks

NASA Astrophysics Data System (ADS)

Bai, Hui-feng

2018-03-01

As the speed of optical access networks soars with ever increasing multiple services, the service-supporting ability of optical access networks suffers greatly from the shortage of service awareness. Aiming to solve this problem, a hierarchy Bayesian model based services awareness mechanism is proposed for high-speed optical access networks. This approach builds a so-called hierarchy Bayesian model, according to the structure of typical optical access networks. Moreover, the proposed scheme is able to conduct simple services awareness operation in each optical network unit (ONU) and to perform complex services awareness from the whole view of system in optical line terminal (OLT). Simulation results show that the proposed scheme is able to achieve better quality of services (QoS), in terms of packet loss rate and time delay.

Distributed Large Data-Object Environments: End-to-End Performance Analysis of High Speed Distributed Storage Systems in Wide Area ATM Networks

NASA Technical Reports Server (NTRS)

Johnston, William; Tierney, Brian; Lee, Jason; Hoo, Gary; Thompson, Mary

1996-01-01

We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

PubMed

Ranganayaki, V; Deepa, S N

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems

PubMed Central

Ranganayaki, V.; Deepa, S. N.

2016-01-01

Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature. PMID:27034973

How Fast Can Networks Synchronize? A Random Matrix Theory Approach

NASA Astrophysics Data System (ADS)

Timme, Marc; Wolf, Fred; Geisel, Theo

2004-03-01

Pulse-coupled oscillators constitute a paradigmatic class of dynamical systems interacting on networks because they model a variety of biological systems including flashing fireflies and chirping crickets as well as pacemaker cells of the heart and neural networks. Synchronization is one of the most simple and most prevailing kinds of collective dynamics on such networks. Here we study collective synchronization [1] of pulse-coupled oscillators interacting on asymmetric random networks. Using random matrix theory we analytically determine the speed of synchronization in such networks in dependence on the dynamical and network parameters [2]. The speed of synchronization increases with increasing coupling strengths. Surprisingly, however, it stays finite even for infinitely strong interactions. The results indicate that the speed of synchronization is limited by the connectivity of the network. We discuss the relevance of our findings to general equilibration processes on complex networks. [5mm] [1] M. Timme, F. Wolf, T. Geisel, Phys. Rev. Lett. 89:258701 (2002). [2] M. Timme, F. Wolf, T. Geisel, cond-mat/0306512 (2003).

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

NASA Astrophysics Data System (ADS)

Wang, Shengling; Cui, Yong; Koodli, Rajeev; Hou, Yibin; Huang, Zhangqin

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

Link and Network Layers Design for Ultra-High-Speed Terahertz-Band Communications Networks

DTIC Science & Technology

2017-01-01

throughput, and identify the optimal parameter values for their design (Sec. 6.2.3). Moreover, we validate and test the scheme with experimental data obtained...LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH- SPEED TERAHERTZ-BAND COMMUNICATIONS NETWORKS STATE UNIVERSITY OF NEW YORK (SUNY) AT BUFFALO JANUARY...TYPE FINAL TECHNICAL REPORT 3. DATES COVERED (From - To) FEB 2015 – SEP 2016 4. TITLE AND SUBTITLE LINK AND NETWORK LAYERS DESIGN FOR ULTRA-HIGH

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction.

PubMed

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-04-10

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks.

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction

PubMed Central

Ma, Xiaolei; Dai, Zhuang; He, Zhengbing; Ma, Jihui; Wang, Yong; Wang, Yunpeng

2017-01-01

This paper proposes a convolutional neural network (CNN)-based method that learns traffic as images and predicts large-scale, network-wide traffic speed with a high accuracy. Spatiotemporal traffic dynamics are converted to images describing the time and space relations of traffic flow via a two-dimensional time-space matrix. A CNN is applied to the image following two consecutive steps: abstract traffic feature extraction and network-wide traffic speed prediction. The effectiveness of the proposed method is evaluated by taking two real-world transportation networks, the second ring road and north-east transportation network in Beijing, as examples, and comparing the method with four prevailing algorithms, namely, ordinary least squares, k-nearest neighbors, artificial neural network, and random forest, and three deep learning architectures, namely, stacked autoencoder, recurrent neural network, and long-short-term memory network. The results show that the proposed method outperforms other algorithms by an average accuracy improvement of 42.91% within an acceptable execution time. The CNN can train the model in a reasonable time and, thus, is suitable for large-scale transportation networks. PMID:28394270

Mathematical model of a gene regulatory network reconciles effects of genetic perturbations on hematopoietic stem cell emergence.

PubMed

Narula, Jatin; Williams, C J; Tiwari, Abhinav; Marks-Bluth, Jonathon; Pimanda, John E; Igoshin, Oleg A

2013-07-15

Interlinked gene regulatory networks (GRNs) are vital for the spatial and temporal control of gene expression during development. The hematopoietic transcription factors (TFs) Scl, Gata2 and Fli1 form one such densely connected GRN which acts as a master regulator of embryonic hematopoiesis. This triad has been shown to direct the specification of the hemogenic endothelium and emergence of hematopoietic stem cells (HSCs) in response to Notch1 and Bmp4-Smad signaling. Here we employ previously published data to construct a mathematical model of this GRN network and use this model to systematically investigate the network dynamical properties. Our model uses a statistical-thermodynamic framework to describe the combinatorial regulation of gene expression and reconciles, mechanistically, several previously published but unexplained results from different genetic perturbation experiments. In particular, our results demonstrate how the interactions of Runx1, an essential hematopoietic TF, with components of the Bmp4 signaling pathway allow it to affect triad activation and acts as a key regulator of HSC emergence. We also explain why heterozygous deletion of this essential TF, Runx1, speeds up the network dynamics leading to accelerated HSC emergence. Taken together our results demonstrate that the triad, a master-level controller of definitive hematopoiesis, is an irreversible bistable switch whose dynamical properties are modulated by Runx1 and components of the Bmp4 signaling pathway. Copyright © 2013 Elsevier Inc. All rights reserved.

40-Gbps optical backbone network deep packet inspection based on FPGA

NASA Astrophysics Data System (ADS)

Zuo, Yuan; Huang, Zhiping; Su, Shaojing

2014-11-01

In the era of information, the big data, which contains huge information, brings about some problems, such as high speed transmission, storage and real-time analysis and process. As the important media for data transmission, the Internet is the significant part for big data processing research. With the large-scale usage of the Internet, the data streaming of network is increasing rapidly. The speed level in the main fiber optic communication of the present has reached 40Gbps, even 100Gbps, therefore data on the optical backbone network shows some features of massive data. Generally, data services are provided via IP packets on the optical backbone network, which is constituted with SDH (Synchronous Digital Hierarchy). Hence this method that IP packets are directly mapped into SDH payload is named POS (Packet over SDH) technology. Aiming at the problems of real time process of high speed massive data, this paper designs a process system platform based on ATCA for 40Gbps POS signal data stream recognition and packet content capture, which employs the FPGA as the CPU. This platform offers pre-processing of clustering algorithms, service traffic identification and data mining for the following big data storage and analysis with high efficiency. Also, the operational procedure is proposed in this paper. Four channels of 10Gbps POS signal decomposed by the analysis module, which chooses FPGA as the kernel, are inputted to the flow classification module and the pattern matching component based on TCAM. Based on the properties of the length of payload and net flows, buffer management is added to the platform to keep the key flow information. According to data stream analysis, DPI (deep packet inspection) and flow balance distribute, the signal is transmitted to the backend machine through the giga Ethernet ports on back board. Practice shows that the proposed platform is superior to the traditional applications based on ASIC and NP.

Functional Connectivity in Multiple Cortical Networks Is Associated with Performance Across Cognitive Domains in Older Adults.

PubMed

Shaw, Emily E; Schultz, Aaron P; Sperling, Reisa A; Hedden, Trey

2015-10-01

Intrinsic functional connectivity MRI has become a widely used tool for measuring integrity in large-scale cortical networks. This study examined multiple cortical networks using Template-Based Rotation (TBR), a method that applies a priori network and nuisance component templates defined from an independent dataset to test datasets of interest. A priori templates were applied to a test dataset of 276 older adults (ages 65-90) from the Harvard Aging Brain Study to examine the relationship between multiple large-scale cortical networks and cognition. Factor scores derived from neuropsychological tests represented processing speed, executive function, and episodic memory. Resting-state BOLD data were acquired in two 6-min acquisitions on a 3-Tesla scanner and processed with TBR to extract individual-level metrics of network connectivity in multiple cortical networks. All results controlled for data quality metrics, including motion. Connectivity in multiple large-scale cortical networks was positively related to all cognitive domains, with a composite measure of general connectivity positively associated with general cognitive performance. Controlling for the correlations between networks, the frontoparietal control network (FPCN) and executive function demonstrated the only significant association, suggesting specificity in this relationship. Further analyses found that the FPCN mediated the relationships of the other networks with cognition, suggesting that this network may play a central role in understanding individual variation in cognition during aging.

Silicon-Germanium Fast Packet Switch Developed for Communications Satellites

NASA Technical Reports Server (NTRS)

Quintana, Jorge A.

1999-01-01

Emerging multimedia applications and future satellite systems will require high-speed switching networks to accommodate high data-rate traffic among thousands of potential users. This will require advanced switching devices to enable communication between satellites. The NASA Lewis Research Center has been working closely with industry to develop a state-of-the-art fast packet switch (FPS) to fulfill this requirement. Recently, the Satellite Industry Task Force identified the need for high-capacity onboard processing switching components as one of the "grand challenges" for the satellite industry in the 21st century. In response to this challenge, future generations of onboard processing satellites will require low power and low mass components to enable transmission of services in the 100 gigabit (1011 bits) per second (Gbps) range.

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

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

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A high-speed network for cardiac image review.

PubMed

Elion, J L; Petrocelli, R R

1994-01-01

A high-speed fiber-based network for the transmission and display of digitized full-motion cardiac images has been developed. Based on Asynchronous Transfer Mode (ATM), the network is scaleable, meaning that the same software and hardware is used for a small local area network or for a large multi-institutional network. The system can handle uncompressed digital angiographic images, considered to be at the "high-end" of the bandwidth requirements. Along with the networking, a general-purpose multi-modality review station has been implemented without specialized hardware. This station can store a full injection sequence in "loop RAM" in a 512 x 512 format, then interpolate to 1024 x 1024 while displaying at 30 frames per second. The network and review stations connect to a central file server that uses a virtual file system to make a large high-speed RAID storage disk and associated off-line storage tapes and cartridges all appear as a single large file system to the software. In addition to supporting archival storage and review, the system can also digitize live video using high-speed Direct Memory Access (DMA) from the frame grabber to present uncompressed data to the network. Fully functional prototypes have provided the proof of concept, with full deployment in the institution planned as the next stage.

A high-speed network for cardiac image review.

PubMed Central

Elion, J. L.; Petrocelli, R. R.

1994-01-01

A high-speed fiber-based network for the transmission and display of digitized full-motion cardiac images has been developed. Based on Asynchronous Transfer Mode (ATM), the network is scaleable, meaning that the same software and hardware is used for a small local area network or for a large multi-institutional network. The system can handle uncompressed digital angiographic images, considered to be at the "high-end" of the bandwidth requirements. Along with the networking, a general-purpose multi-modality review station has been implemented without specialized hardware. This station can store a full injection sequence in "loop RAM" in a 512 x 512 format, then interpolate to 1024 x 1024 while displaying at 30 frames per second. The network and review stations connect to a central file server that uses a virtual file system to make a large high-speed RAID storage disk and associated off-line storage tapes and cartridges all appear as a single large file system to the software. In addition to supporting archival storage and review, the system can also digitize live video using high-speed Direct Memory Access (DMA) from the frame grabber to present uncompressed data to the network. Fully functional prototypes have provided the proof of concept, with full deployment in the institution planned as the next stage. PMID:7949964

Understanding characteristics in multivariate traffic flow time series from complex network structure

NASA Astrophysics Data System (ADS)

Yan, Ying; Zhang, Shen; Tang, Jinjun; Wang, Xiaofei

2017-07-01

Discovering dynamic characteristics in traffic flow is the significant step to design effective traffic managing and controlling strategy for relieving traffic congestion in urban cities. A new method based on complex network theory is proposed to study multivariate traffic flow time series. The data were collected from loop detectors on freeway during a year. In order to construct complex network from original traffic flow, a weighted Froenius norm is adopt to estimate similarity between multivariate time series, and Principal Component Analysis is implemented to determine the weights. We discuss how to select optimal critical threshold for networks at different hour in term of cumulative probability distribution of degree. Furthermore, two statistical properties of networks: normalized network structure entropy and cumulative probability of degree, are utilized to explore hourly variation in traffic flow. The results demonstrate these two statistical quantities express similar pattern to traffic flow parameters with morning and evening peak hours. Accordingly, we detect three traffic states: trough, peak and transitional hours, according to the correlation between two aforementioned properties. The classifying results of states can actually represent hourly fluctuation in traffic flow by analyzing annual average hourly values of traffic volume, occupancy and speed in corresponding hours.

Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

DOE PAGES

Tian, Wenhong; Samatova, Nagiza F.

2013-01-01

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based onmore » a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.« less

Synapse-Centric Mapping of Cortical Models to the SpiNNaker Neuromorphic Architecture

PubMed Central

Knight, James C.; Furber, Steve B.

2016-01-01

While the adult human brain has approximately 8.8 × 1010 neurons, this number is dwarfed by its 1 × 1015 synapses. From the point of view of neuromorphic engineering and neural simulation in general this makes the simulation of these synapses a particularly complex problem. SpiNNaker is a digital, neuromorphic architecture designed for simulating large-scale spiking neural networks at speeds close to biological real-time. Current solutions for simulating spiking neural networks on SpiNNaker are heavily inspired by work on distributed high-performance computing. However, while SpiNNaker shares many characteristics with such distributed systems, its component nodes have much more limited resources and, as the system lacks global synchronization, the computation performed on each node must complete within a fixed time step. We first analyze the performance of the current SpiNNaker neural simulation software and identify several problems that occur when it is used to simulate networks of the type often used to model the cortex which contain large numbers of sparsely connected synapses. We then present a new, more flexible approach for mapping the simulation of such networks to SpiNNaker which solves many of these problems. Finally we analyze the performance of our new approach using both benchmarks, designed to represent cortical connectivity, and larger, functional cortical models. In a benchmark network where neurons receive input from 8000 STDP synapses, our new approach allows 4× more neurons to be simulated on each SpiNNaker core than has been previously possible. We also demonstrate that the largest plastic neural network previously simulated on neuromorphic hardware can be run in real time using our new approach: double the speed that was previously achieved. Additionally this network contains two types of plastic synapse which previously had to be trained separately but, using our new approach, can be trained simultaneously. PMID:27683540

Integrated Circuit Chip Improves Network Efficiency

NASA Technical Reports Server (NTRS)

2008-01-01

Prior to 1999 and the development of SpaceWire, a standard for high-speed links for computer networks managed by the European Space Agency (ESA), there was no high-speed communications protocol for flight electronics. Onboard computers, processing units, and other electronics had to be designed for individual projects and then redesigned for subsequent projects, which increased development periods, costs, and risks. After adopting the SpaceWire protocol in 2000, NASA implemented the standard on the Swift mission, a gamma ray burst-alert telescope launched in November 2004. Scientists and developers on the James Webb Space Telescope further developed the network version of SpaceWire. In essence, SpaceWire enables more science missions at a lower cost, because it provides a standard interface between flight electronics components; new systems need not be custom built to accommodate individual missions, so electronics can be reused. New protocols are helping to standardize higher layers of computer communication. Goddard Space Flight Center improved on the ESA-developed SpaceWire by enabling standard protocols, which included defining quality of service and supporting plug-and-play capabilities. Goddard upgraded SpaceWire to make the routers more efficient and reliable, with features including redundant cables, simultaneous discrete broadcast pulses, prevention of network blockage, and improved verification. Redundant cables simplify management because the user does not need to worry about which connection is available, and simultaneous broadcast signals allow multiple users to broadcast low-latency side-band signal pulses across the network using the same resources for data communication. Additional features have been added to the SpaceWire switch to prevent network blockage so that more robust networks can be designed. Goddard s verification environment for the link-and-switch implementation continuously randomizes and tests different parts, constantly anticipating situations, which helps improve communications reliability. It has been tested in many different implementations for compatibility.

Mono-isotope Prediction for Mass Spectra Using Bayes Network.

PubMed

Li, Hui; Liu, Chunmei; Rwebangira, Mugizi Robert; Burge, Legand

2014-12-01

Mass spectrometry is one of the widely utilized important methods to study protein functions and components. The challenge of mono-isotope pattern recognition from large scale protein mass spectral data needs computational algorithms and tools to speed up the analysis and improve the analytic results. We utilized naïve Bayes network as the classifier with the assumption that the selected features are independent to predict mono-isotope pattern from mass spectrometry. Mono-isotopes detected from validated theoretical spectra were used as prior information in the Bayes method. Three main features extracted from the dataset were employed as independent variables in our model. The application of the proposed algorithm to publicMo dataset demonstrates that our naïve Bayes classifier is advantageous over existing methods in both accuracy and sensitivity.

Prediction based Greedy Perimeter Stateless Routing Protocol for Vehicular Self-organizing Network

NASA Astrophysics Data System (ADS)

Wang, Chunlin; Fan, Quanrun; Chen, Xiaolin; Xu, Wanjin

2018-03-01

PGPSR (Prediction based Greedy Perimeter Stateless Routing) is based on and extended the GPSR protocol to adapt to the high speed mobility of the vehicle auto organization network (VANET) and the changes in the network topology. GPSR is used in the VANET network environment, the network loss rate and throughput are not ideal, even cannot work. Aiming at the problems of the GPSR, the proposed PGPSR routing protocol, it redefines the hello and query packet structure, in the structure of the new node speed and direction information, which received the next update before you can take advantage of its speed and direction to predict the position of node and new network topology, select the right the next hop routing and path. Secondly, the update of the outdated node information of the neighbor’s table is deleted in time. The simulation experiment shows the performance of PGPSR is better than that of GPSR.

Radiology: "killer app" for next generation networks?

PubMed

McNeill, Kevin M

2004-03-01

The core principles of digital radiology were well developed by the end of the 1980 s. During the following decade tremendous improvements in computer technology enabled realization of those principles at an affordable cost. In this decade work can focus on highly distributed radiology in the context of the integrated health care enterprise. Over the same period computer networking has evolved from a relatively obscure field used by a small number of researchers across low-speed serial links to a pervasive technology that affects nearly all facets of society. Development directions in network technology will ultimately provide end-to-end data paths with speeds that match or exceed the speeds of data paths within the local network and even within workstations. This article describes key developments in Next Generation Networks, potential obstacles, and scenarios in which digital radiology can become a "killer app" that helps to drive deployment of new network infrastructure.

Which neuropsychological functions predict various processing speed components in children with and without attention-deficit/hyperactivity disorder?

PubMed

Vadnais, Sarah A; Kibby, Michelle Y; Jagger-Rickels, Audreyana C

2018-01-01

We identified statistical predictors of four processing speed (PS) components in a sample of 151 children with and without attention-deficit/hyperactivity disorder (ADHD). Performance on perceptual speed was predicted by visual attention/short-term memory, whereas incidental learning/psychomotor speed was predicted by verbal working memory. Rapid naming was predictive of each PS component assessed, and inhibition predicted all but one task, suggesting a shared need to identify/retrieve stimuli rapidly and inhibit incorrect responding across PS components. Hence, we found both shared and unique predictors of perceptual, cognitive, and output speed, suggesting more specific terminology should be used in future research on PS in ADHD.

A Study of Quality of Service Communication for High-Speed Packet-Switching Computer Sub-Networks

NASA Technical Reports Server (NTRS)

Cui, Zhenqian

1999-01-01

With the development of high-speed networking technology, computer networks, including local-area networks (LANs), wide-area networks (WANs) and the Internet, are extending their traditional roles of carrying computer data. They are being used for Internet telephony, multimedia applications such as conferencing and video on demand, distributed simulations, and other real-time applications. LANs are even used for distributed real-time process control and computing as a cost-effective approach. Differing from traditional data transfer, these new classes of high-speed network applications (video, audio, real-time process control, and others) are delay sensitive. The usefulness of data depends not only on the correctness of received data, but also the time that data are received. In other words, these new classes of applications require networks to provide guaranteed services or quality of service (QoS). Quality of service can be defined by a set of parameters and reflects a user's expectation about the underlying network's behavior. Traditionally, distinct services are provided by different kinds of networks. Voice services are provided by telephone networks, video services are provided by cable networks, and data transfer services are provided by computer networks. A single network providing different services is called an integrated-services network.

Structural vulnerability of the French swine industry trade network to the spread of infectious diseases.

PubMed

Rautureau, S; Dufour, B; Durand, B

2012-07-01

The networks generated by live animal movements are the principal vector for the propagation of infectious agents between farms, and their topology strongly affects how fast a disease may spread. The structural characteristics of networks may thus provide indicators of network vulnerability to the spread of infectious disease. This study applied social network analysis methods to describe the French swine trade network. Initial analysis involved calculating several parameters to characterize networks and then identifying high-risk subgroups of holdings for different time scales. Holding-specific centrality measurements ('degree', 'betweenness' and 'ingoing infection chain'), which summarize the place and the role of holdings in the network, were compared according to the production type. In addition, network components and communities, areas where connectedness is particularly high and could influence the speed and the extent of a disease, were identified and analysed. Dealer holdings stood out because of their high centrality values suggesting that these holdings may control the flow of animals in part of the network. Herds with growing units had higher values for degree and betweenness centrality, representing central positions for both spreading and receiving disease, whereas herds with finishing units had higher values for in-degree and ingoing infection chain centrality values and appeared more vulnerable with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases. This reflects the dynamics of the swine trade with downward movements along the production chain. But, the significant heterogeneity of farms with several production units did not reveal any particular type of production for targeting disease surveillance or control. Besides, no giant strong connected component was observed, the network being rather organized according to communities of small or medium size (<20% of network size). Because of this fragmentation, the swine trade network appeared less structurally vulnerable than ruminant trade networks. This fragmentation is explained by the hierarchical structure, which thus limits the structural vulnerability of the global trade network. However, inside communities, the hierarchical structure of the swine production system would favour the spread of an infectious agent (especially if introduced in breeding herds).

Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

PubMed

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

Fluid power network for centralized electricity generation in offshore wind farms

NASA Astrophysics Data System (ADS)

Jarquin-Laguna, A.

2014-06-01

An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network.

SpaceWire: IP, Components, Development Support and Test Equipment

NASA Astrophysics Data System (ADS)

Parkes, S.; McClements, C.; Mills, S.; Martin, I.

SpaceWire is a communications network for use onboard spacecraft. It is designed to connect high data-rate sensors, large solid-state memories, processing units and the downlink telemetry subsystem providing an integrated data-handling network. SpaceWire links are serial, high-speed (2 Mbits/sec to 400 Mbits/sec), bi-directional, full-duplex, pointto- point data links which connect together SpaceWire equipment. Application information is sent along a SpaceWire link in discrete packets. Control and time information can also be sent along SpaceWire links. SpaceWire is defined in the ECSS-E50-12A standard [1]. With the adoption of SpaceWire on many space missions the ready availability of intellectual property (IP) cores, components, software drivers, development support, and test equipment becomes a major issue for those developing satellites and their electronic subsystems. This paper describes the work being done at the University of Dundee and STAR-Dundee Ltd with ESA, BNSC and internal funding to make these essential items available. STAR-Dundee is a spin-out company of the University of Dundee set up specifically to support users of SpaceWire.

Efficient Use of Distributed Systems for Scientific Applications

NASA Technical Reports Server (NTRS)

Taylor, Valerie; Chen, Jian; Canfield, Thomas; Richard, Jacques

2000-01-01

Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.

Traffic safety effects of new speed limits in Sweden.

PubMed

Vadeby, Anna; Forsman, Åsa

2018-05-01

The effects of speed, both positive and negative, make speed a primary target for policy action. Driving speeds affect the risk of being involved in a crash and the injury severity as well as the noise and exhaust emissions. Starting 2008, the Swedish Transport Administration performed a review of the speed limits on the national rural road network. This review resulted in major changes of the speed limits on the rural road network. It was predominantly roads with a low traffic safety standard and unsatisfactory road sides that were selected for reduced speed limits, as well as roads with a good traffic safety record being selected for an increase in speed limits. During 2008 and 2009, speed limit changed on approximately 20,500km of roads, out of which approximately 2700km were assigned an increase, and 17,800km were assigned a reduction in speed limits. The aim of this study is predominantly to describe and analyse the longterm traffic safety effect of increased, as well as, reduced speed limits, but also to analyse the changes in actual driving speeds due to the changed speed limits. Traffic safety effects are investigated by means of a before and after study with control group and the effects on actual mean speeds are measured by a sampling survey in which speed was measured at randomly selected sites before and after the speed limit changes. Results show a reduction in fatalities on rural roads with reduced speed limit from 90 to 80km/h where the number of fatalities decreased by 14 per year, while no significant changes were seen for the seriously injured. On motorways with an increased speed limit to 120km/h, the number of seriously injured increased by about 15 per year, but no significant changes were seen for the number of deaths. The number of seriously injured increased on all types of motorways, but the worst development was seen for narrow motorways (21.5m wide). For 2+1 roads (a continuous three-lane cross-section with alternating passing lanes and the two directions of travel separated by a median barrier) with decreased speed limit from 110 to 100km/h, the seriously injured decreased by about 16 per year. As regards the change of mean speeds, a decrease in speed limit with 10km/h led to a decrease of mean speeds of around 2-3km/h and an increase of the speed limit with 10km/h resulted in an increase of mean speed by 3km/h. In conclusion, the results show that in total about 17 lives per year have been saved on the road network with changed speed limits. For comparison, 397 road users were killed in total during 2008. The number of seriously injured remain in principle unchanged. It should also be noted that the results are obtained for the road network which changed the speed limits during 2008 and 2009, and it is not certain that the results can be generalised to another road network. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the Relationship Between Solar Wind Speed, Geomagnetic Activity, and the Solar Cycle Using Annual Values

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.

2008-01-01

The aa index can be decomposed into two separate components: the leading sporadic component due to solar activity as measured by sunspot number and the residual or recurrent component due to interplanetary disturbances, such as coronal holes. For the interval 1964-2006, a highly statistically important correlation (r = 0.749) is found between annual averages of the aa index and the solar wind speed (especially between the residual component of aa and the solar wind speed, r = 0.865). Because cyclic averages of aa (and the residual component) have trended upward during cycles 11-23, cyclic averages of solar wind speed are inferred to have also trended upward.

Technical report on prototype intelligent network flow optimization (INFLO) dynamic speed harmonization and queue warning.

DOT National Transportation Integrated Search

2015-06-01

This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale demonstration of the ...

Service oriented network architecture for control and management of home appliances

NASA Astrophysics Data System (ADS)

Hayakawa, Hiroshi; Koita, Takahiro; Sato, Kenya

2005-12-01

Recent advances in multimedia network systems and mechatronics have led to the development of a new generation of applications that associate the use of various multimedia objects with the behavior of multiple robotic actors. The connection of audio and video devices through high speed multimedia networks is expected to make the system more convenient to use. For example, many home appliances, such as a video camera, a display monitor, a video recorder, an audio system and so on, are being equipped with a communication interface in the near future. Recently some platforms (i.e. UPnP1, HAVi2 and so on) are proposed for constructing home networks; however, there are some issues to be solved to realize various services by connecting different equipment via the pervasive peer-to-peer network. UPnP offers network connectivity of PCs of intelligent home appliances, practically, which means to require a PC in the network to control other devices. Meanwhile, HAVi has been developed for intelligent AV equipments with sophisticated functions using high CPU power and large memory. Considering the targets of home alliances are embedded systems, this situation raises issues of software and hardware complexity, cost, power consumption and so on. In this study, we have proposed and developed the service oriented network architecture for control and management of home appliances, named SONICA (Service Oriented Network Interoperability for Component Adaptation), to address these issues described before.

A decentralized training algorithm for Echo State Networks in distributed big data applications.

PubMed

Scardapane, Simone; Wang, Dianhui; Panella, Massimo

2016-06-01

The current big data deluge requires innovative solutions for performing efficient inference on large, heterogeneous amounts of information. Apart from the known challenges deriving from high volume and velocity, real-world big data applications may impose additional technological constraints, including the need for a fully decentralized training architecture. While several alternatives exist for training feed-forward neural networks in such a distributed setting, less attention has been devoted to the case of decentralized training of recurrent neural networks (RNNs). In this paper, we propose such an algorithm for a class of RNNs known as Echo State Networks. The algorithm is based on the well-known Alternating Direction Method of Multipliers optimization procedure. It is formulated only in terms of local exchanges between neighboring agents, without reliance on a coordinating node. Additionally, it does not require the communication of training patterns, which is a crucial component in realistic big data implementations. Experimental results on large scale artificial datasets show that it compares favorably with a fully centralized implementation, in terms of speed, efficiency and generalization accuracy. Copyright © 2015 Elsevier Ltd. All rights reserved.

A continually online-trained neural network controller for brushless DC motor drives

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

Rubaai, A.; Kotaru, R.; Kankam, M.D.

2000-04-01

In this paper, a high-performance controller with simultaneous online identification and control is designed for brushless dc motor drives. The dynamics of the motor/load are modeled online, and controlled using two different neural network based identification and control schemes, as the system is in operation. In the first scheme, an attempt is made to control the rotor angular speed, utilizing a single three-hidden-layer network. The second scheme attempts to control the stator currents, using a predetermined control law as a function of the estimated states. This schemes incorporates three multilayered feedforward neural networks that are online trained, using the Levenburg-Marquadtmore » training algorithm. The control of the direct and quadrature components of the stator current successfully tracked a wide variety of trajectories after relatively short online training periods. The control strategy adapts to the uncertainties of the motor/load dynamics and, in addition, learns their inherent nonlinearities. Simulation results illustrated that a neurocontroller used in conjunction with adaptive control schemes can result in a flexible control device which may be utilized in a wide range of environments.« less

A mathematical model for mesenchymal and chemosensitive cell dynamics.

PubMed

Häcker, Anita

2012-01-01

The structure of an underlying tissue network has a strong impact on cell dynamics. If, in addition, cells alter the network by mechanical and chemical interactions, their movement is called mesenchymal. Important examples for mesenchymal movement include fibroblasts in wound healing and metastatic tumour cells. This paper is focused on the latter. Based on the anisotropic biphasic theory of Barocas and Tranquillo, which models a fibre network and interstitial solution as two-component fluid, a mathematical model for the interactions of cells with a fibre network is developed. A new description for fibre reorientation is given and orientation-dependent proteolysis is added to the model. With respect to cell dynamics, the equation, based on anisotropic diffusion, is extended by haptotaxis and chemotaxis. The chemoattractants are the solute network fragments, emerging from proteolysis, and the epidermal growth factor which may guide the cells to a blood vessel. Moreover the cell migration is impeded at either high or low network density. This new model enables us to study chemotactic cell migration in a complex fibre network and the consequential network deformation. Numerical simulations for the cell migration and network deformation are carried out in two space dimensions. Simulations of cell migration in underlying tissue networks visualise the impact of the network structure on cell dynamics. In a scenario for fibre reorientation between cell clusters good qualitative agreement with experimental results is achieved. The invasion speeds of cells in an aligned and an isotropic fibre network are compared. © Springer-Verlag 2011

Efficient hash tables for network applications.

PubMed

Zink, Thomas; Waldvogel, Marcel

2015-01-01

Hashing has yet to be widely accepted as a component of hard real-time systems and hardware implementations, due to still existing prejudices concerning the unpredictability of space and time requirements resulting from collisions. While in theory perfect hashing can provide optimal mapping, in practice, finding a perfect hash function is too expensive, especially in the context of high-speed applications. The introduction of hashing with multiple choices, d-left hashing and probabilistic table summaries, has caused a shift towards deterministic DRAM access. However, high amounts of rare and expensive high-speed SRAM need to be traded off for predictability, which is infeasible for many applications. In this paper we show that previous suggestions suffer from the false precondition of full generality. Our approach exploits four individual degrees of freedom available in many practical applications, especially hardware and high-speed lookups. This reduces the requirement of on-chip memory up to an order of magnitude and guarantees constant lookup and update time at the cost of only minute amounts of additional hardware. Our design makes efficient hash table implementations cheaper, more predictable, and more practical.

An ultralow power athermal silicon modulator.

PubMed

Timurdogan, Erman; Sorace-Agaskar, Cheryl M; Sun, Jie; Shah Hosseini, Ehsan; Biberman, Aleksandr; Watts, Michael R

2014-06-11

Silicon photonics has emerged as the leading candidate for implementing ultralow power wavelength-division-multiplexed communication networks in high-performance computers, yet current components (lasers, modulators, filters and detectors) consume too much power for the high-speed femtojoule-class links that ultimately will be required. Here we demonstrate and characterize the first modulator to achieve simultaneous high-speed (25 Gb s(-1)), low-voltage (0.5 VPP) and efficient 0.9 fJ per bit error-free operation. This low-energy high-speed operation is enabled by a record electro-optic response, obtained in a vertical p-n junction device that at 250 pm V(-1) (30 GHz V(-1)) is up to 10 times larger than prior demonstrations. In addition, this record electro-optic response is used to compensate for thermal drift over a 7.5 °C temperature range with little additional energy consumption (0.24 fJ per bit for a total energy consumption below 1.03 J per bit). The combined results of highly efficient modulation and electro-optic thermal compensation represent a new paradigm in modulator development and a major step towards single-digit femtojoule-class communications.

Enabling MEMS technologies for communications systems

NASA Astrophysics Data System (ADS)

Lubecke, Victor M.; Barber, Bradley P.; Arney, Susanne

2001-11-01

Modern communications demands have been steadily growing not only in size, but sophistication. Phone calls over copper wires have evolved into high definition video conferencing over optical fibers, and wireless internet browsing. The technology used to meet these demands is under constant pressure to provide increased capacity, speed, and efficiency, all with reduced size and cost. Various MEMS technologies have shown great promise for meeting these challenges by extending the performance of conventional circuitry and introducing radical new systems approaches. A variety of strategic MEMS structures including various cost-effective free-space optics and high-Q RF components are described, along with related practical implementation issues. These components are rapidly becoming essential for enabling the development of progressive new communications systems technologies including all-optical networks, and low cost multi-system wireless terminals and basestations.

Passive and electro-optic polymer photonics and InP electronics integration

NASA Astrophysics Data System (ADS)

Zhang, Z.; Katopodis, V.; Groumas, P.; Konczykowska, A.; Dupuy, J.-.; Beretta, A.; Dede, A.; Miller, E.; Choi, J. H.; Harati, P.; Jorge, F.; Nodjiadjim, V.; Dinu, R.; Cangini, G.; Vannucci, A.; Felipe, D.; Maese-Novo, A.; Keil, N.; Bach, H.-.; Schell, Martin; Avramopoulos, H.; Kouloumentas, Ch.

2015-05-01

Hybrid photonic integration allows individual components to be developed at their best-suited material platforms without sacrificing the overall performance. In the past few years a polymer-enabled hybrid integration platform has been established, comprising 1) EO polymers for constructing low-complexity and low-cost Mach-Zehnder modulators (MZMs) with extremely high modulation bandwidth; 2) InP components for light sources, detectors, and high-speed electronics including MUX drivers and DEMUX circuits; 3) Ceramic (AIN) RF board that links the electronic signals within the package. On this platform, advanced optoelectronic modules have been demonstrated, including serial 100 Gb/s [1] and 2x100 Gb/s [2] optical transmitters, but also 400 Gb/s optoelectronic interfaces for intra-data center networks [3]. To expand the device functionalities to an unprecedented level and at the same time improve the integration compatibility with diversified active / passive photonic components, we have added a passive polymer-based photonic board (polyboard) as the 4th material system. This passive polyboard allows for low-cost fabrication of single-mode waveguide networks, enables fast and convenient integration of various thin-film elements (TFEs) to control the light polarization, and provides efficient thermo-optic elements (TOEs) for wavelength tuning, light amplitude regulation and light-path switching.

Spatial Dynamics of Multilayer Cellular Neural Networks

NASA Astrophysics Data System (ADS)

Wu, Shi-Liang; Hsu, Cheng-Hsiung

2018-02-01

The purpose of this work is to study the spatial dynamics of one-dimensional multilayer cellular neural networks. We first establish the existence of rightward and leftward spreading speeds of the model. Then we show that the spreading speeds coincide with the minimum wave speeds of the traveling wave fronts in the right and left directions. Moreover, we obtain the asymptotic behavior of the traveling wave fronts when the wave speeds are positive and greater than the spreading speeds. According to the asymptotic behavior and using various kinds of comparison theorems, some front-like entire solutions are constructed by combining the rightward and leftward traveling wave fronts with different speeds and a spatially homogeneous solution of the model. Finally, various qualitative features of such entire solutions are investigated.

An Experimental Exploration of the Impact of Network-Level Packet Loss on Network Intrusion Detection

DTIC Science & Technology

2015-08-01

Experimental environment 5 Table 1 Hardware specifications Name Manufacture Model CPU Memory Hard Drive IP Address Bilbo Dell PowerEdge R610 Intel...10 we replayed the same hour of network traffic from the CDX 20093 that we used in our theoretical2 exploration to show the impact of our packet... replay the traffic at arbitrary speeds. Table 3 lists the speed multiplier that we used and the packet loss we observed. Table 3 Network packet loss

Design and Construction of a High-speed Network Connecting All the Protein Crystallography Beamlines at the Photon Factory

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

Matsugaki, Naohiro; Yamada, Yusuke; Igarashi, Noriyuki

2007-01-19

A private network, physically separated from the facility network, was designed and constructed which covered all the four protein crystallography beamlines at the Photon Factory (PF) and Structural Biology Research Center (SBRC). Connecting all the beamlines in the same network allows for simple authentication and a common working environment for a user who uses multiple beamlines. Giga-bit Ethernet wire-speed was achieved for the communication among the beamlines and SBRC buildings.

The relationship between gamma frequency and running speed differs for slow and fast gamma rhythms in freely behaving rats

PubMed Central

Zheng, Chenguang; Bieri, Kevin Wood; Trettel, Sean Gregory; Colgin, Laura Lee

2015-01-01

In hippocampal area CA1 of rats, the frequency of gamma activity has been shown to increase with running speed (Ahmed and Mehta, 2012). This finding suggests that different gamma frequencies simply allow for different timings of transitions across cell assemblies at varying running speeds, rather than serving unique functions. However, accumulating evidence supports the conclusion that slow (~25–55 Hz) and fast (~60–100 Hz) gamma are distinct network states with different functions. If slow and fast gamma constitute distinct network states, then it is possible that slow and fast gamma frequencies are differentially affected by running speed. In this study, we tested this hypothesis and found that slow and fast gamma frequencies change differently as a function of running speed in hippocampal areas CA1 and CA3, and in the superficial layers of the medial entorhinal cortex (MEC). Fast gamma frequencies increased with increasing running speed in all three areas. Slow gamma frequencies changed significantly less across different speeds. Furthermore, at high running speeds, CA3 firing rates were low, and MEC firing rates were high, suggesting that CA1 transitions from CA3 inputs to MEC inputs as running speed increases. These results support the hypothesis that slow and fast gamma reflect functionally distinct states in the hippocampal network, with fast gamma driven by MEC at high running speeds and slow gamma driven by CA3 at low running speeds. PMID:25601003

Validation of Community Models: Identifying Events in Space Weather Model Timelines

NASA Technical Reports Server (NTRS)

MacNeice, Peter

2009-01-01

I develop and document a set of procedures which test the quality of predictions of solar wind speed and polarity of the interplanetary magnetic field (IMF) made by coupled models of the ambient solar corona and heliosphere. The Wang-Sheeley-Arge (WSA) model is used to illustrate the application of these validation procedures. I present an algorithm which detects transitions of the solar wind from slow to high speed. I also present an algorithm which processes the measured polarity of the outward directed component of the IMF. This removes high-frequency variations to expose the longer-scale changes that reflect IMF sector changes. I apply these algorithms to WSA model predictions made using a small set of photospheric synoptic magnetograms obtained by the Global Oscillation Network Group as input to the model. The results of this preliminary validation of the WSA model (version 1.6) are summarized.

A Control Simulation Method of High-Speed Trains on Railway Network with Irregular Influence

NASA Astrophysics Data System (ADS)

Yang, Li-Xing; Li, Xiang; Li, Ke-Ping

2011-09-01

Based on the discrete time method, an effective movement control model is designed for a group of highspeed trains on a rail network. The purpose of the model is to investigate the specific traffic characteristics of high-speed trains under the interruption of stochastic irregular events. In the model, the high-speed rail traffic system is supposed to be equipped with the moving-block signalling system to guarantee maximum traversing capacity of the railway. To keep the safety of trains' movements, some operational strategies are proposed to control the movements of trains in the model, including traction operation, braking operation, and entering-station operation. The numerical simulations show that the designed model can well describe the movements of high-speed trains on the rail network. The research results can provide the useful information not only for investigating the propagation features of relevant delays under the irregular disturbance but also for rerouting and rescheduling trains on the rail network.

A Study of Quality of Service Communication for High-Speed Packet-Switching Computer Sub-Networks

NASA Technical Reports Server (NTRS)

Cui, Zhenqian

1999-01-01

In this thesis, we analyze various factors that affect quality of service (QoS) communication in high-speed, packet-switching sub-networks. We hypothesize that sub-network-wide bandwidth reservation and guaranteed CPU processing power at endpoint systems for handling data traffic are indispensable to achieving hard end-to-end quality of service. Different bandwidth reservation strategies, traffic characterization schemes, and scheduling algorithms affect the network resources and CPU usage as well as the extent that QoS can be achieved. In order to analyze those factors, we design and implement a communication layer. Our experimental analysis supports our research hypothesis. The Resource ReSerVation Protocol (RSVP) is designed to realize resource reservation. Our analysis of RSVP shows that using RSVP solely is insufficient to provide hard end-to-end quality of service in a high-speed sub-network. Analysis of the IEEE 802.lp protocol also supports the research hypothesis.

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

PubMed

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

PubMed Central

Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an “optimal” weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds. PMID:27382627

Circuity analyses of HSR network and high-speed train paths in China

PubMed Central

Zhao, Shuo; Huang, Jie; Shan, Xinghua

2017-01-01

Circuity, defined as the ratio of the shortest network distance to the Euclidean distance between one origin–destination (O-D) pair, can be adopted as a helpful evaluation method of indirect degrees of train paths. In this paper, the maximum circuity of the paths of operated trains is set to be the threshold value of the circuity of high-speed train paths. For the shortest paths of any node pairs, if their circuity is not higher than the threshold value, the paths can be regarded as the reasonable paths. With the consideration of a certain relative or absolute error, we cluster the reasonable paths on the basis of their inclusion relationship and the center path of each class represents a passenger transit corridor. We take the high-speed rail (HSR) network in China at the end of 2014 as an example, and obtain 51 passenger transit corridors, which are alternative sets of train paths. Furthermore, we analyze the circuity distribution of paths of all node pairs in the network. We find that the high circuity of train paths can be decreased with the construction of a high-speed railway line, which indicates that the structure of the HSR network in China tends to be more complete and the HSR network can make the Chinese railway network more efficient. PMID:28945757

A network model of knowledge accumulation through diffusion and upgrade

NASA Astrophysics Data System (ADS)

Zhuang, Enyu; Chen, Guanrong; Feng, Gang

2011-07-01

In this paper, we introduce a model to describe knowledge accumulation through knowledge diffusion and knowledge upgrade in a multi-agent network. Here, knowledge diffusion refers to the distribution of existing knowledge in the network, while knowledge upgrade means the discovery of new knowledge. It is found that the population of the network and the number of each agent’s neighbors affect the speed of knowledge accumulation. Four different policies for updating the neighboring agents are thus proposed, and their influence on the speed of knowledge accumulation and the topology evolution of the network are also studied.

Neural networks for function approximation in nonlinear control

NASA Technical Reports Server (NTRS)

Linse, Dennis J.; Stengel, Robert F.

1990-01-01

Two neural network architectures are compared with a classical spline interpolation technique for the approximation of functions useful in a nonlinear control system. A standard back-propagation feedforward neural network and a cerebellar model articulation controller (CMAC) neural network are presented, and their results are compared with a B-spline interpolation procedure that is updated using recursive least-squares parameter identification. Each method is able to accurately represent a one-dimensional test function. Tradeoffs between size requirements, speed of operation, and speed of learning indicate that neural networks may be practical for identification and adaptation in a nonlinear control environment.

A high performance parallel computing architecture for robust image features

NASA Astrophysics Data System (ADS)

Zhou, Renyan; Liu, Leibo; Wei, Shaojun

2014-03-01

A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.

Distributed downhole drilling network

DOEpatents

Hall, David R.; Hall, Jr., H. Tracy; Fox, Joe; Pixton, David S.

2006-11-21

A high-speed downhole network providing real-time data from downhole components of a drilling strings includes a bottom-hole node interfacing to a bottom-hole assembly located proximate the bottom end of a drill string. A top-hole node is connected proximate the top end of the drill string. One or several intermediate nodes are located along the drill string between the bottom-hole node and the top-hole node. The intermediate nodes are configured to receive and transmit data packets transmitted between the bottom-hole node and the top-hole node. A communications link, integrated into the drill string, is used to operably connect the bottom-hole node, the intermediate nodes, and the top-hole node. In selected embodiments, a personal or other computer may be connected to the top-hole node, to analyze data received from the intermediate and bottom-hole nodes.

Fiber to the home: next generation network

NASA Astrophysics Data System (ADS)

Yang, Chengxin; Guo, Baoping

2006-07-01

Next generation networks capable of carrying converged telephone, television (TV), very high-speed internet, and very high-speed bi-directional data services (like video-on-demand (VOD), Game etc.) strategy for Fiber To The Home (FTTH) is presented. The potential market is analyzed. The barriers and some proper strategy are also discussed. Several technical problems like various powering methods, optical fiber cables, and different network architecture are discussed too.

Label swapper device for spectral amplitude coded optical packet networks monolithically integrated on InP.

PubMed

Muñoz, P; García-Olcina, R; Habib, C; Chen, L R; Leijtens, X J M; de Vries, T; Robbins, D; Capmany, J

2011-07-04

In this paper the design, fabrication and experimental characterization of an spectral amplitude coded (SAC) optical label swapper monolithically integrated on Indium Phosphide (InP) is presented. The device has a footprint of 4.8x1.5 mm2 and is able to perform label swapping operations required in SAC at a speed of 155 Mbps. The device was manufactured in InP using a multiple purpose generic integration scheme. Compared to previous SAC label swapper demonstrations, using discrete component assembly, this label swapper chip operates two order of magnitudes faster.

NASA electronic message experiment and study: Detailed test plans

NASA Technical Reports Server (NTRS)

1979-01-01

A methodology for evaluating the utility of high speed digital facsimile as a component of the projected NASA-wide electronic message network is presented. Equipment checkout, operator familiarization, pretest calibration, and the development of procedures are addressed. An experimental test program of the facsimile message service which will carry duplicates of the actual messages sent by other means is highlighted. Also, an operational test program during which messages will be sent on a regular basis in order to accumulate the information that will be used to evaluate system performance and project future growth is described.

Time-dependent seismic tomography of the Coso geothermal area, 1996-2004

USGS Publications Warehouse

Julian, B.R.; Foulger, G.R.

2005-01-01

The permanent 18-station network of three-component digital seismometers at the seismically active Coso geothermal area, California, provides high-quality microearthquake (MEQ) data that are well suited to investigating temporal variations in structure related to processes within the geothermal reservoir. A preliminary study [Julian, et al., 2003; Julian, et al., 2004] comparing data from 1996 and 2003 found significant variations in the ratio of the seismic wave-speeds, Vp/Vs, at shallow depths over this time interval. This report describes results of a more detailed study of each year from 1996 through 2004.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

Reference ability neural networks and behavioral performance across the adult life span.

PubMed

Habeck, Christian; Eich, Teal; Razlighi, Ray; Gazes, Yunglin; Stern, Yaakov

2018-05-15

To better understand the impact of aging, along with other demographic and brain health variables, on the neural networks that support different aspects of cognitive performance, we applied a brute-force search technique based on Principal Components Analysis to derive 4 corresponding spatial covariance patterns (termed Reference Ability Neural Networks -RANNs) from a large sample of participants across the age range. 255 clinically healthy, community-dwelling adults, aged 20-77, underwent fMRI while performing 12 tasks, 3 tasks for each of the following cognitive reference abilities: Episodic Memory, Reasoning, Perceptual Speed, and Vocabulary. The derived RANNs (1) showed selective activation to their specific cognitive domain and (2) correlated with behavioral performance. Quasi out-of-sample replication with Monte-Carlo 5-fold cross validation was built into our approach, and all patterns indicated their corresponding reference ability and predicted performance in held-out data to a degree significantly greater than chance level. RANN-pattern expression for Episodic Memory, Reasoning and Vocabulary were associated selectively with age, while the pattern for Perceptual Speed showed no such age-related influences. For each participant we also looked at residual activity unaccounted for by the RANN-pattern derived for the cognitive reference ability. Higher residual activity was associated with poorer brain-structural health and older age, but -apart from Vocabulary-not with cognitive performance, indicating that older participants with worse brain-structural health might recruit alternative neural resources to maintain performance levels. Copyright © 2018 Elsevier Inc. All rights reserved.

The Near-Earth Meteoroid Flux, Speed Distribution, and Uncertainty

NASA Technical Reports Server (NTRS)

Moorhead, Althea; Cooke, William J.; Brown, Peter G.; Campbell-Brown, Margaret; Moser, Danielle E.

2016-01-01

Meteoroids are known to pose a threat to spacecraft; they can puncture components, disturb spacecraft attitude, and possibly create secondary electrical effects. Accurate environment models are therefore critical for mitigating meteoroid-related risks. While there are several meteoroid environment models available for assessing spacecraft risk, the uncertainties associated with these models are not well understood. Because meteoroid properties are derived from indirect observations such as meteors and impact craters, the uncertainty in the meteoroid flux is potentially quite large. We combine existing meteoroid flux measurements with new radar and optical meteor data to improve our characterization of the meteoroid flux onto the Earth and its velocity distribution. We use data extracted from the NASA all-sky network, the Canadian Automated Meteor Observatory, and the Canadian Meteor Orbit Radar. We improve our characterization of the observed meteoroid speed distribution by incorporating modern descriptions of the ionization efficiency (e.g., Thomas et al., 2016). We also present estimates of the uncertainties associated with our meteoroid flux distribution. Finally, we discuss the implications for spacecraft. Our model is constrained by the cratering rate on the space-facing surface of LDEF, and thus the risk posed to spacecraft by meteoroid-induced physical damage is the least uncertain component of our model. Other sources of risk, however, may vary. For instance, a lower average meteoroid speed would require a higher meteoroid mass flux in order to match the LDEF crater counts, leading to higher predicted rates of attitude disturbances.

Limits to high-speed simulations of spiking neural networks using general-purpose computers.

PubMed

Zenke, Friedemann; Gerstner, Wulfram

2014-01-01

To understand how the central nervous system performs computations using recurrent neuronal circuitry, simulations have become an indispensable tool for theoretical neuroscience. To study neuronal circuits and their ability to self-organize, increasing attention has been directed toward synaptic plasticity. In particular spike-timing-dependent plasticity (STDP) creates specific demands for simulations of spiking neural networks. On the one hand a high temporal resolution is required to capture the millisecond timescale of typical STDP windows. On the other hand network simulations have to evolve over hours up to days, to capture the timescale of long-term plasticity. To do this efficiently, fast simulation speed is the crucial ingredient rather than large neuron numbers. Using different medium-sized network models consisting of several thousands of neurons and off-the-shelf hardware, we compare the simulation speed of the simulators: Brian, NEST and Neuron as well as our own simulator Auryn. Our results show that real-time simulations of different plastic network models are possible in parallel simulations in which numerical precision is not a primary concern. Even so, the speed-up margin of parallelism is limited and boosting simulation speeds beyond one tenth of real-time is difficult. By profiling simulation code we show that the run times of typical plastic network simulations encounter a hard boundary. This limit is partly due to latencies in the inter-process communications and thus cannot be overcome by increased parallelism. Overall, these results show that to study plasticity in medium-sized spiking neural networks, adequate simulation tools are readily available which run efficiently on small clusters. However, to run simulations substantially faster than real-time, special hardware is a prerequisite.

Attention networks in adolescent anorexia nervosa.

PubMed

Weinbach, Noam; Sher, Helene; Lock, James D; Henik, Avishai

2018-03-01

Anorexia nervosa (AN) usually develops during adolescence when considerable structural and functional brain changes are taking place. Neurocognitive inefficiencies have been consistently found in adults with enduring AN and were suggested to play a role in maintaining the disorder. However, such findings are inconsistent in children and adolescents with AN. The current study conducted a comprehensive assessment of attention networks in adolescents with AN who were not severely underweight during the study using an approach that permits disentangling independent components of attention. Twenty partially weight-restored adolescents with AN (AN-WR) and 24 healthy adolescents performed the Attention Network Test which assesses the efficiency of three main attention networks-executive control, orienting, and alerting. The results revealed abnormal function in the executive control network among adolescents with AN-WR. Specifically, adolescents with AN-WR demonstrated superior ability to suppress attention to task-irrelevant information while focusing on a central task. Moreover, the alerting network modulated this ability. No difference was found between the groups in the speed of orienting attention, but reorienting attention to a target resulted in higher error rates in the AN-WR group. The findings suggest that adolescents with AN have attentional abnormalities that cannot be explained by a state of starvation. These attentional dysregulations may underlie clinical phenotypes of the disorder such as increased attention of details.

Resting-state functional connectivity in multiple sclerosis: an examination of group differences and individual differences.

PubMed

Janssen, Alisha L; Boster, Aaron; Patterson, Beth A; Abduljalil, Amir; Prakash, Ruchika Shaurya

2013-11-01

Multiple sclerosis (MS) is a neurodegenerative, inflammatory disease of the central nervous system, resulting in physical and cognitive disturbances. The goal of the current study was to examine the association between network integrity and composite measures of cognition and disease severity in individuals with relapsing-remitting MS (RRMS), relative to healthy controls. All participants underwent a neuropsychological and neuroimaging session, where resting-state data was collected. Independent component analysis and dual regression were employed to examine network integrity in individuals with MS, relative to healthy controls. The MS sample exhibited less connectivity in the motor and visual networks, relative to healthy controls, after controlling for group differences in gray matter volume. However, no alterations were observed in the frontoparietal, executive control, or default-mode networks, despite previous evidence of altered neuronal patterns during tasks of exogenous processing. Whole-brain, voxel-wise regression analyses with disease severity and processing speed composites were also performed to elucidate the brain-behavior relationship with neuronal network integrity. Individuals with higher levels of disease severity demonstrated reduced intra-network connectivity of the motor network, and the executive control network, while higher disease burden was associated with greater inter-network connectivity between the medial visual network and areas involved in visuomotor learning. Our findings underscore the importance of examining resting-state oscillations in this population, both as a biomarker of disease progression and a potential target for therapeutic intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

High speed fiber optics local area networks: Design and implementation

NASA Technical Reports Server (NTRS)

Tobagi, Fouad A.

1988-01-01

The design of high speed local area networks (HSLAN) for communication among distributed devices requires solving problems in three areas: (1) the network medium and its topology; (2) the medium access control; and (3) the network interface. Considerable progress has been made in all areas. Accomplishments are divided into two groups according to their theoretical or experimental nature. A brief summary is given in Section 2, including references to papers which appeared in the literature, as well as to Ph.D. dissertations and technical reports published at Stanford University.

On-board fault diagnostics for fly-by-light flight control systems using neural network flight processors

NASA Astrophysics Data System (ADS)

Urnes, James M., Sr.; Cushing, John; Bond, William E.; Nunes, Steve

1996-10-01

Fly-by-Light control systems offer higher performance for fighter and transport aircraft, with efficient fiber optic data transmission, electric control surface actuation, and multi-channel high capacity centralized processing combining to provide maximum aircraft flight control system handling qualities and safety. The key to efficient support for these vehicles is timely and accurate fault diagnostics of all control system components. These diagnostic tests are best conducted during flight when all facts relating to the failure are present. The resulting data can be used by the ground crew for efficient repair and turnaround of the aircraft, saving time and money in support costs. These difficult to diagnose (Cannot Duplicate) fault indications average 40 - 50% of maintenance activities on today's fighter and transport aircraft, adding significantly to fleet support cost. Fiber optic data transmission can support a wealth of data for fault monitoring; the most efficient method of fault diagnostics is accurate modeling of the component response under normal and failed conditions for use in comparison with the actual component flight data. Neural Network hardware processors offer an efficient and cost-effective method to install fault diagnostics in flight systems, permitting on-board diagnostic modeling of very complex subsystems. Task 2C of the ARPA FLASH program is a design demonstration of this diagnostics approach, using the very high speed computation of the Adaptive Solutions Neural Network processor to monitor an advanced Electrohydrostatic control surface actuator linked through a AS-1773A fiber optic bus. This paper describes the design approach and projected performance of this on-line diagnostics system.

Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring network

NASA Astrophysics Data System (ADS)

Laib, Mohamed; Telesca, Luciano; Kanevski, Mikhail

2018-03-01

This paper studies the daily connectivity time series of a wind speed-monitoring network using multifractal detrended fluctuation analysis. It investigates the long-range fluctuation and multifractality in the residuals of the connectivity time series. Our findings reveal that the daily connectivity of the correlation-based network is persistent for any correlation threshold. Further, the multifractality degree is higher for larger absolute values of the correlation threshold.

Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

PubMed Central

Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

2015-01-01

To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

SpaceWire Plug and Play

NASA Technical Reports Server (NTRS)

Rakow, Glenn; McGuirk, Patrick; Kimmery, Clifford; Jaffe, Paul

2006-01-01

The ability to rapidly deploy inexpensive satellites to meet tactical goals has become an important goal for military space systems. In fact, Operationally Responsive Space (ORS) has been in the spotlight at the highest levels. The Office of the Secretary of Defense (OSD) has identified that the critical next step is developing the bus standards and modular interfaces. Historically, satellite components have been constructed based on bus standards and standardized interfaces. However, this has not been done to a degree, which would allow the rapid deployment of a satellite. Advancements in plug-and-play (PnP) technologies for terrestrial applications can serve as a baseline model for a PnP approach for satellite applications. Since SpaceWire (SpW) has become a de facto standard for satellite high-speed (greater than 200Mbp) on-board communications, it has become important for SpW to adapt to this Plug and Play (PnP) environment. Because SpW is simply a bulk transport protocol and lacks built-in PnP features, several changes are required to facilitate PnP with SpW. The first is for Host(s) to figure out what the network looks like, i.e., how pieces of the network, routers and nodes, are connected together; network mapping, and to receive notice of changes to the network. The second is for the components connected to the network to be understood so that they can communicate. The first element, network topology mapping & change of status indication, is being defined (topic of this paper). The second element describing how components are to communicate has been defined by ARFL with the electronic data sheets known as XTEDS. The first element, network mapping, is recent activities performed by Air Force Research Lab (ARFL), Naval Research Lab (NRL), NASA and US industry (Honeywell, Clearwater, FL, and others). This work has resulted in the development of a protocol that will perform the lower level functions of network mapping and Change Of Status (COS) indication required by Plug 'n' Play over SpaceWire. This work will be presented to the SpaceWire working group for standardization under European Cooperation for Space Standardization (ECSS) and to obtain a permanent Protocol ID (see SpaceWire Protocol ID: What Does it Mean to You; IEEE Aerospace Conference 2006). The portion of the Plug 'n' Play protocol that will be described in this paper is how the Host(s) of a SpaceWire network map the network and detect additions and deletions of devices on a SpaceWire network.

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Cortical Specializations Underlying Fast Computations

PubMed Central

Volgushev, Maxim

2016-01-01

The time course of behaviorally relevant environmental events sets temporal constraints on neuronal processing. How does the mammalian brain make use of the increasingly complex networks of the neocortex, while making decisions and executing behavioral reactions within a reasonable time? The key parameter determining the speed of computations in neuronal networks is a time interval that neuronal ensembles need to process changes at their input and communicate results of this processing to downstream neurons. Theoretical analysis identified basic requirements for fast processing: use of neuronal populations for encoding, background activity, and fast onset dynamics of action potentials in neurons. Experimental evidence shows that populations of neocortical neurons fulfil these requirements. Indeed, they can change firing rate in response to input perturbations very quickly, within 1 to 3 ms, and encode high-frequency components of the input by phase-locking their spiking to frequencies up to 300 to 1000 Hz. This implies that time unit of computations by cortical ensembles is only few, 1 to 3 ms, which is considerably faster than the membrane time constant of individual neurons. The ability of cortical neuronal ensembles to communicate on a millisecond time scale allows for complex, multiple-step processing and precise coordination of neuronal activity in parallel processing streams, while keeping the speed of behavioral reactions within environmentally set temporal constraints. PMID:25689988

Empirical study of the role of the topology in spreading on communication networks

NASA Astrophysics Data System (ADS)

Medvedev, Alexey; Kertesz, Janos

2017-03-01

Topological aspects, like community structure, and temporal activity patterns, like burstiness, have been shown to severely influence the speed of spreading in temporal networks. We study the influence of the topology on the susceptible-infected (SI) spreading on time stamped communication networks, as obtained from a dataset of mobile phone records. We consider city level networks with intra- and inter-city connections. The networks using only intra-city links are usually sparse, where the spreading depends mainly on the average degree. The inter-city links serve as bridges in spreading, speeding up considerably the process. We demonstrate the effect also on model simulations.

Calculating a checksum with inactive networking components in a computing system

DOEpatents

Aho, Michael E; Chen, Dong; Eisley, Noel A; Gooding, Thomas M; Heidelberger, Philip; Tauferner, Andrew T

2014-12-16

Calculating a checksum utilizing inactive networking components in a computing system, including: identifying, by a checksum distribution manager, an inactive networking component, wherein the inactive networking component includes a checksum calculation engine for computing a checksum; sending, to the inactive networking component by the checksum distribution manager, metadata describing a block of data to be transmitted by an active networking component; calculating, by the inactive networking component, a checksum for the block of data; transmitting, to the checksum distribution manager from the inactive networking component, the checksum for the block of data; and sending, by the active networking component, a data communications message that includes the block of data and the checksum for the block of data.

Calculating a checksum with inactive networking components in a computing system

DOEpatents

Aho, Michael E; Chen, Dong; Eisley, Noel A; Gooding, Thomas M; Heidelberger, Philip; Tauferner, Andrew T

2015-01-27

Calculating a checksum utilizing inactive networking components in a computing system, including: identifying, by a checksum distribution manager, an inactive networking component, wherein the inactive networking component includes a checksum calculation engine for computing a checksum; sending, to the inactive networking component by the checksum distribution manager, metadata describing a block of data to be transmitted by an active networking component; calculating, by the inactive networking component, a checksum for the block of data; transmitting, to the checksum distribution manager from the inactive networking component, the checksum for the block of data; and sending, by the active networking component, a data communications message that includes the block of data and the checksum for the block of data.

H.R. 1757--High Performance Computing and High Speed Networking Applications Act of 1993. Hearings before the Subcommittee on Science of the Committee on Science, Space, and Technology. House of Representatives, One Hundred Third Congress, First Session (April 27, May 6, May 11, 1993).

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. House Committee on Science, Space and Technology.

This document contains the transcript of three hearings on the High Speed Performance Computing and High Speed Networking Applications Act of 1993 (H.R. 1757). The hearings were designed to obtain specific suggestions for improvements to the legislation and alternative or additional application areas that should be pursued. Testimony and prepared…

Devices and circuits for nanoelectronic implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

Turel, Ozgur

Biological neural networks perform complicated information processing tasks at speeds better than conventional computers based on conventional algorithms. This has inspired researchers to look into the way these networks function, and propose artificial networks that mimic their behavior. Unfortunately, most artificial neural networks, either software or hardware, do not provide either the speed or the complexity of a human brain. Nanoelectronics, with high density and low power dissipation that it provides, may be used in developing more efficient artificial neural networks. This work consists of two major contributions in this direction. First is the proposal of the CMOL concept, hybrid CMOS-molecular hardware [1-8]. CMOL may circumvent most of the problems in posed by molecular devices, such as low yield, vet provide high active device density, ˜1012/cm 2. The second contribution is CrossNets, artificial neural networks that are based on CMOL. We showed that CrossNets, with their fault tolerance, exceptional speed (˜ 4 to 6 orders of magnitude faster than biological neural networks) can perform any task any artificial neural network can perform. Moreover, there is a hope that if their integration scale is increased to that of human cerebral cortex (˜ 1010 neurons and ˜ 1014 synapses), they may be capable of performing more advanced tasks.

Data storage and retrieval system abstract

NASA Technical Reports Server (NTRS)

Matheson, Barbara

1992-01-01

The STX mass storage system design is intended for environments requiring high speed access to large volumes of data (terabyte and greater). Prior to commitment to a product design plan, STX conducted an exhaustive study of the commercially available off-the-shelf hardware and software. STX also conducted research into the area of emerging technologies in networks and storage media so that the design could easily accommodate new interfaces and peripherals as they came on the market. All the selected system elements were brought together in a demo suite sponsored jointly by STX and ALLIANT where the system elements were evaluated based on actual operation using a client-server mirror image configuration. Testing was conducted to assess the various component overheads and results were compared against vendor data claims. The resultant system, while adequate to meet our capacity requirements, fell short of transfer speed expectations. A product team lead by STX was assembled and chartered with solving the bottleneck issues. Optimization efforts yielded a 60 percent improvement in throughput performance. The ALLIANT computer platform provided the I/O flexibility needed to accommodate a multitude of peripheral interfaces including the following: up to twelve 25MB/s VME I/O channels; up to five HiPPI I/O full duplex channels; IPI-s, SCSI, SMD, and RAID disk array support; standard networking software support for TCP/IP, NFS, and FTP; open architecture based on standard RISC processors; and V.4/POSIX-based operating system (Concentrix). All components including the software are modular in design and can be reconfigured as needs and system uses change. Users can begin with a small system and add modules as needed in the field. Most add-ons can be accomplished seamlessly without revision, recompilation or re-linking of software.

Data storage and retrieval system abstract

NASA Astrophysics Data System (ADS)

Matheson, Barbara

1992-09-01

The STX mass storage system design is intended for environments requiring high speed access to large volumes of data (terabyte and greater). Prior to commitment to a product design plan, STX conducted an exhaustive study of the commercially available off-the-shelf hardware and software. STX also conducted research into the area of emerging technologies in networks and storage media so that the design could easily accommodate new interfaces and peripherals as they came on the market. All the selected system elements were brought together in a demo suite sponsored jointly by STX and ALLIANT where the system elements were evaluated based on actual operation using a client-server mirror image configuration. Testing was conducted to assess the various component overheads and results were compared against vendor data claims. The resultant system, while adequate to meet our capacity requirements, fell short of transfer speed expectations. A product team lead by STX was assembled and chartered with solving the bottleneck issues. Optimization efforts yielded a 60 percent improvement in throughput performance. The ALLIANT computer platform provided the I/O flexibility needed to accommodate a multitude of peripheral interfaces including the following: up to twelve 25MB/s VME I/O channels; up to five HiPPI I/O full duplex channels; IPI-s, SCSI, SMD, and RAID disk array support; standard networking software support for TCP/IP, NFS, and FTP; open architecture based on standard RISC processors; and V.4/POSIX-based operating system (Concentrix). All components including the software are modular in design and can be reconfigured as needs and system uses change. Users can begin with a small system and add modules as needed in the field. Most add-ons can be accomplished seamlessly without revision, recompilation or re-linking of software.

Cognitive benefit and cost of acute stress is differentially modulated by individual brain state

PubMed Central

Hermans, Erno J.; Fernández, Guillén

2017-01-01

Abstract Acute stress is associated with beneficial as well as detrimental effects on cognition in different individuals. However, it is not yet known how stress can have such opposing effects. Stroop-like tasks typically show this dissociation: stress diminishes speed, but improves accuracy. We investigated accuracy and speed during a stroop-like task of 120 healthy male subjects after an experimental stress induction or control condition in a randomized, counter-balanced cross-over design; we assessed brain–behavior associations and determined the influence of individual brain connectivity patterns on these associations, which may moderate the effect and help identify stress resilience factors. In the mean, stress was associated to increase in accuracy, but decrease in speed. Accuracy was associated to brain activation in a distributed set of brain regions overlapping with the executive control network (ECN) and speed to temporo-parietal activation. In line with a stress-related large-scale network reconfiguration, individuals showing an upregulation of the salience and down-regulation of the executive-control network under stress displayed increased speed, but decreased performance. In contrast, individuals who upregulate their ECN under stress show improved performance. Our results indicate that the individual large-scale brain network balance under acute stress moderates cognitive consequences of threat. PMID:28402480

Cognitive benefit and cost of acute stress is differentially modulated by individual brain state.

PubMed

Kohn, Nils; Hermans, Erno J; Fernández, Guillén

2017-07-01

Acute stress is associated with beneficial as well as detrimental effects on cognition in different individuals. However, it is not yet known how stress can have such opposing effects. Stroop-like tasks typically show this dissociation: stress diminishes speed, but improves accuracy. We investigated accuracy and speed during a stroop-like task of 120 healthy male subjects after an experimental stress induction or control condition in a randomized, counter-balanced cross-over design; we assessed brain-behavior associations and determined the influence of individual brain connectivity patterns on these associations, which may moderate the effect and help identify stress resilience factors. In the mean, stress was associated to increase in accuracy, but decrease in speed. Accuracy was associated to brain activation in a distributed set of brain regions overlapping with the executive control network (ECN) and speed to temporo-parietal activation. In line with a stress-related large-scale network reconfiguration, individuals showing an upregulation of the salience and down-regulation of the executive-control network under stress displayed increased speed, but decreased performance. In contrast, individuals who upregulate their ECN under stress show improved performance. Our results indicate that the individual large-scale brain network balance under acute stress moderates cognitive consequences of threat. © The Author (2017). Published by Oxford University Press.

Semantic encoding of relational databases in wireless networks

NASA Astrophysics Data System (ADS)

Benjamin, David P.; Walker, Adrian

2005-03-01

Semantic Encoding is a new, patented technology that greatly increases the speed of transmission of distributed databases over networks, especially over ad hoc wireless networks, while providing a novel method of data security. It reduces bandwidth consumption and storage requirements, while speeding up query processing, encryption and computation of digital signatures. We describe the application of Semantic Encoding in a wireless setting and provide an example of its operation in which a compression of 290:1 would be achieved.

NASCOM system development plan: System description, capabilities, and plans, FY 94-2

NASA Technical Reports Server (NTRS)

1994-01-01

The Nascom System Development Plan (NSDP) for FY 94-2 contains 17 sections. It is a management document containing the approved plan for maintaining the Nascom Network System. Topics covered include an overview of Nascom systems and services, major ground communication support systems, low-speed data system, voice system, high-speed data system, Nascom support for NASA networks, Nascom planning for NASA missions, and network upgrade and advanced systems developments and plans.

Gain modulation by an urgency signal controls the speed-accuracy trade-off in a network model of a cortical decision circuit.

PubMed

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C

2011-01-01

The speed-accuracy trade-off (SAT) is ubiquitous in decision tasks. While the neural mechanisms underlying decisions are generally well characterized, the application of decision-theoretic methods to the SAT has been difficult to reconcile with experimental data suggesting that decision thresholds are inflexible. Using a network model of a cortical decision circuit, we demonstrate the SAT in a manner consistent with neural and behavioral data and with mathematical models that optimize speed and accuracy with respect to one another. In simulations of a reaction time task, we modulate the gain of the network with a signal encoding the urgency to respond. As the urgency signal builds up, the network progresses through a series of processing stages supporting noise filtering, integration of evidence, amplification of integrated evidence, and choice selection. Analysis of the network's dynamics formally characterizes this progression. Slower buildup of urgency increases accuracy by slowing down the progression. Faster buildup has the opposite effect. Because the network always progresses through the same stages, decision-selective firing rates are stereotyped at decision time.

Determination of the geophysical model function of NSCAT and its corresponding variance by the use of neural networks

NASA Astrophysics Data System (ADS)

Mejia, C.; Badran, F.; Bentamy, A.; Crepon, M.; Thiria, S.; Tran, N.

1999-05-01

We have computed two geophysical model functions (one for the vertical and one for the horizontal polarization) for the NASA scatterometer (NSCAT) by using neural networks. These neural network geophysical model functions (NNGMFs) were estimated with NSCAT scatterometer σO measurements collocated with European Centre for Medium-Range Weather Forecasts analyzed wind vectors during the period January 15 to April 15, 1997. We performed a student t test showing that the NNGMFs estimate the NSCAT σO with a confidence level of 95%. Analysis of the results shows that the mean NSCAT signal depends on the incidence angle and the wind speed and presents the classical biharmonic modulation with respect to the wind azimuth. NSCAT σO increases with respect to the wind speed and presents a well-marked change at around 7 m s-1. The upwind-downwind amplitude is higher for the horizontal polarization signal than for vertical polarization, indicating that the use of horizontal polarization can give additional information for wind retrieval. Comparison of the σO computed by the NNGMFs against the NSCAT-measured σO show a quite low rms, except at low wind speeds. We also computed two specific neural networks for estimating the variance associated to these GMFs. The variances are analyzed with respect to geophysical parameters. This led us to compute the geophysical signal-to-noise ratio, i.e., Kp. The Kp values are quite high at low wind speed and decrease at high wind speed. At constant wind speed the highest Kp are at crosswind directions, showing that the crosswind values are the most difficult to estimate. These neural networks can be expressed as analytical functions, and FORTRAN subroutines can be provided.

The Xpress Transfer Protocol (XTP): A tutorial (expanded version)

NASA Technical Reports Server (NTRS)

Sanders, Robert M.; Weaver, Alfred C.

1990-01-01

The Xpress Transfer Protocol (XTP) is a reliable, real-time, light weight transfer layer protocol. Current transport layer protocols such as DoD's Transmission Control Protocol (TCP) and ISO's Transport Protocol (TP) were not designed for the next generation of high speed, interconnected reliable networks such as fiber distributed data interface (FDDI) and the gigabit/second wide area networks. Unlike all previous transport layer protocols, XTP is being designed to be implemented in hardware as a VLSI chip set. By streamlining the protocol, combining the transport and network layers and utilizing the increased speed and parallelization possible with a VLSI implementation, XTP will be able to provide the end-to-end data transmission rates demanded in high speed networks without compromising reliability and functionality. This paper describes the operation of the XTP protocol and in particular, its error, flow and rate control; inter-networking addressing mechanisms; and multicast support features, as defined in the XTP Protocol Definition Revision 3.4.

Ship-borne measurements of aerosol optical depth over remote oceans and its dependence on wind speed

NASA Astrophysics Data System (ADS)

Smirnov, A.; Sayer, A. M.; Holben, B. N.; Hsu, N. C.; Sakerin, S. M.; Macke, A.; Nelson, N. B.; Courcoux, Y.; Smyth, T. J.; Croot, P. L.; Quinn, P.; Sciare, J.; Gulev, S. K.; Piketh, S.; Losno, R.; Kinne, S. A.; Radionov, V. F.

2011-12-01

Aerosol production sources over the World Ocean and various factors determining aerosol spatial and temporal distribution are important for understanding the Earth's radiation budget and aerosol-cloud interactions. Sea-salt aerosol production, being a major source of aerosol over remote oceans, depends on surface wind speed. Recently in a number of publications the effect of wind speed on aerosol optical depth (AOD) has been presented utilizing coastal, island-based and satellite-based AOD measurements. However, the influence of wind speed on the columnar optical depth is still poorly understood, because not all factors and precursors influencing AOD dependence can be accounted for. The Maritime Aerosol Network (a component of AERONET) data archive provides an excellent opportunity to analyze in depth a relationship between ship-based AOD measurements and wind speed. We considered only data presumably not influenced by urban/industrial continental sources, dust outbreaks, biomass burning, or glaciers and pack ice. Additional restrictions imposed on the data set were acceptance of only points taken not closer than two degrees from the nearest landmass. We present analyses on the effect of surface (deck-level) wind speed (acquired onboard, modeled by NCEP, measured from satellite) on AOD and its spectral dependence. Latitudinal comparison of measured onboard and modeled wind speeds showed relatively small bias, which was higher at high latitudes. Instantaneous AOD measurements and daily means yielded similar relationships with various wind speed subsets (instantaneous ship-based and NCEP, averaged over previous 24 hours, steady, satellite retrieved). We compared regression statistics of optical parameters versus wind speed presented in various papers and based on various satellite and sunphotometer measurements. Overall, despite certain scatter, the current work and a majority of publications showed consistent patterns, with the AOD versus wind speed (range 2-16 m/s) dependence close to linear.

Gelatinized wheat starch influences crystallization behaviour and structure of roll-in shortenings in laminated bakery products.

PubMed

Mattice, Kristin D; Marangoni, Alejandro G

2018-03-15

One hydrogenated and one non-hydrogenated shortening were baked with isolated components of a croissant matrix, including crystalline wheat starch, gelatinized wheat starch, gluten, and formed gluten network. The impact of the matrix components on fat crystallization was analyzed for polymorphism using powder X-ray diffraction, solid fat content by pulsed nuclear magnetic resonance and thermal behaviour by differential scanning calorimetry. When compared to results obtained from croissants prepared with the respective shortenings, samples containing gelatinized wheat starch displayed notably similar results: polymorphic conversion, from the β' to β form over storage, and visually broader peaks in the melting endotherms indicating a greater temperature was required to completely melt all of the fat. All other component mixtures behaved similar to the respective fats in bulk. The measured rate of crystallization was greater in samples containing gelatinized wheat starch, indicating that the gelatinized starch could act as a nucleation site to speed crystallization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Polarization-multiplexed rate-adaptive non-binary-quasi-cyclic-LDPC-coded multilevel modulation with coherent detection for optical transport networks.

PubMed

Arabaci, Murat; Djordjevic, Ivan B; Saunders, Ross; Marcoccia, Roberto M

2010-02-01

In order to achieve high-speed transmission over optical transport networks (OTNs) and maximize its throughput, we propose using a rate-adaptive polarization-multiplexed coded multilevel modulation with coherent detection based on component non-binary quasi-cyclic (QC) LDPC codes. Compared to prior-art bit-interleaved LDPC-coded modulation (BI-LDPC-CM) scheme, the proposed non-binary LDPC-coded modulation (NB-LDPC-CM) scheme not only reduces latency due to symbol- instead of bit-level processing but also provides either impressive reduction in computational complexity or striking improvements in coding gain depending on the constellation size. As the paper presents, compared to its prior-art binary counterpart, the proposed NB-LDPC-CM scheme addresses the needs of future OTNs, which are achieving the target BER performance and providing maximum possible throughput both over the entire lifetime of the OTN, better.

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

HDR {sup 192}Ir source speed measurements using a high speed video camera

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

Fonseca, Gabriel P.; Viana, Rodrigo S. S.; Yoriyaz, Hélio

Purpose: The dose delivered with a HDR {sup 192}Ir afterloader can be separated into a dwell component, and a transit component resulting from the source movement. The transit component is directly dependent on the source speed profile and it is the goal of this study to measure accurate source speed profiles. Methods: A high speed video camera was used to record the movement of a {sup 192}Ir source (Nucletron, an Elekta company, Stockholm, Sweden) for interdwell distances of 0.25–5 cm with dwell times of 0.1, 1, and 2 s. Transit dose distributions were calculated using a Monte Carlo code simulatingmore » the source movement. Results: The source stops at each dwell position oscillating around the desired position for a duration up to (0.026 ± 0.005) s. The source speed profile shows variations between 0 and 81 cm/s with average speed of ∼33 cm/s for most of the interdwell distances. The source stops for up to (0.005 ± 0.001) s at nonprogrammed positions in between two programmed dwell positions. The dwell time correction applied by the manufacturer compensates the transit dose between the dwell positions leading to a maximum overdose of 41 mGy for the considered cases and assuming an air-kerma strength of 48 000 U. The transit dose component is not uniformly distributed leading to over and underdoses, which is within 1.4% for commonly prescribed doses (3–10 Gy). Conclusions: The source maintains its speed even for the short interdwell distances. Dose variations due to the transit dose component are much lower than the prescribed treatment doses for brachytherapy, although transit dose component should be evaluated individually for clinical cases.« less

Periodic fluctuations in correlation-based connectivity density time series: Application to wind speed-monitoring network in Switzerland

NASA Astrophysics Data System (ADS)

Laib, Mohamed; Telesca, Luciano; Kanevski, Mikhail

2018-02-01

In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

High-Performance Computing: Industry Uses of Supercomputers and High-Speed Networks. Report to Congressional Requesters.

ERIC Educational Resources Information Center

General Accounting Office, Washington, DC. Information Management and Technology Div.

This report was prepared in response to a request for information on supercomputers and high-speed networks from the Senate Committee on Commerce, Science, and Transportation, and the House Committee on Science, Space, and Technology. The following information was requested: (1) examples of how various industries are using supercomputers to…

Field trials of 100G and beyond: an operator's point of view

NASA Astrophysics Data System (ADS)

Vorbeck, S.; Schneiders, M.; Weiershausen, W.; Mayer, H.; Schippel, A.; Wagner, P.; Ehrhardt, A.; Braun, R.; Breuer, D.; Drafz, U.; Fritzsche, D.

2011-01-01

In this article we present a summary of the latest 100 Gbps field trials in the network of Deutsche Telekom AG with industry partners. We cover a brown field approach as alien wavelength on existing systems, a green field high speed overlay network approach and a high speed interface router-router coupling.

Marketing Career Speed Networking: A Classroom Event to Foster Career Awareness

ERIC Educational Resources Information Center

Buff, Cheryl L.; O'Connor, Suzanne

2012-01-01

This paper describes the design, implementation, and evaluation of a marketing career speed networking event held during class time in two sections of the consumer behavior class. The event was coordinated through a partnering effort with marketing faculty and the college's Career Center. A total of 57 students participated in the event, providing…

Resting State Default Mode Network Connectivity, Dual Task Performance, Gait Speed, and Postural Sway in Older Adults with Mild Cognitive Impairment

PubMed Central

Crockett, Rachel A.; Hsu, Chun Liang; Best, John R.; Liu-Ambrose, Teresa

2017-01-01

Aging is associated with an increased risk of falling. In particular, older adults with mild cognitive impairment (MCI) are more vulnerable to falling compared with their healthy counterparts. Major contributors to this increased falls risk include a decline in dual task performance, gait speed, and postural sway. Recent evidence highlights the potential influence of the default mode network (DMN), the frontoparietal network (FPN), and the supplementary motor area (SMA) on dual task performance, gait speed, and postural sway. The DMN is active during rest and deactivates during task-oriented processes, to maintain attention and stay on task. The FPN and SMA are involved in top-down attentional control, motor planning, and motor execution. The DMN shows less deactivation during task in older adults with MCI. This lack of deactivation is theorized to increase competition for resources between the DMN and task-related brain regions (e.g., the FPN and SMA), increasing distraction from the task and reducing task performance. However, no study has yet investigated the relationship between the between-network connectivity of the DMN with these regions and dual task walking, gait speed or postural sway. We hypothesized that greater functional connectivity both within the DMN and between DMN–FPN and DMN–SMA, will be associated with poorer performance during dual task walking, slower gait speed, and greater postural sway in older adults with MCI. Forty older adults with MCI were measured on a dual task-walking paradigm, gait speed over a 4-m walk, and postural sway using a sway-meter. Greater within-DMN connectivity was significantly correlated with poorer dual task performance. Furthermore, greater inter-network connectivity between the DMN and SMA was significantly correlated with slower gait speed and greater postural sway on the eyes open floor sway task. Thus, greater resting state DMN functional connectivity may be an underlying neural mechanism for reduced dual task ability, slower gait speed, and greater postural sway, resulting in the increased risk of mobility disability and falling in older adults with MCI. PMID:29311906

Resting State Default Mode Network Connectivity, Dual Task Performance, Gait Speed, and Postural Sway in Older Adults with Mild Cognitive Impairment.

PubMed

Crockett, Rachel A; Hsu, Chun Liang; Best, John R; Liu-Ambrose, Teresa

2017-01-01

Aging is associated with an increased risk of falling. In particular, older adults with mild cognitive impairment (MCI) are more vulnerable to falling compared with their healthy counterparts. Major contributors to this increased falls risk include a decline in dual task performance, gait speed, and postural sway. Recent evidence highlights the potential influence of the default mode network (DMN), the frontoparietal network (FPN), and the supplementary motor area (SMA) on dual task performance, gait speed, and postural sway. The DMN is active during rest and deactivates during task-oriented processes, to maintain attention and stay on task. The FPN and SMA are involved in top-down attentional control, motor planning, and motor execution. The DMN shows less deactivation during task in older adults with MCI. This lack of deactivation is theorized to increase competition for resources between the DMN and task-related brain regions (e.g., the FPN and SMA), increasing distraction from the task and reducing task performance. However, no study has yet investigated the relationship between the between-network connectivity of the DMN with these regions and dual task walking, gait speed or postural sway. We hypothesized that greater functional connectivity both within the DMN and between DMN-FPN and DMN-SMA, will be associated with poorer performance during dual task walking, slower gait speed, and greater postural sway in older adults with MCI. Forty older adults with MCI were measured on a dual task-walking paradigm, gait speed over a 4-m walk, and postural sway using a sway-meter. Greater within-DMN connectivity was significantly correlated with poorer dual task performance. Furthermore, greater inter-network connectivity between the DMN and SMA was significantly correlated with slower gait speed and greater postural sway on the eyes open floor sway task. Thus, greater resting state DMN functional connectivity may be an underlying neural mechanism for reduced dual task ability, slower gait speed, and greater postural sway, resulting in the increased risk of mobility disability and falling in older adults with MCI.

47 CFR 51.5 - Terms and definitions.

Code of Federal Regulations, 2014 CFR

2014-10-01

.... The Communications Act of 1934, as amended. Advanced intelligent network. Advanced intelligent network is a telecommunications network architecture in which call processing, call routing, and network... carrier's network. Advanced services. The term “advanced services” is defined as high speed, switched...

Silicon photonic Mach Zehnder modulators for next-generation short-reach optical communication networks

NASA Astrophysics Data System (ADS)

Lacava, C.; Liu, Z.; Thomson, D.; Ke, Li; Fedeli, J. M.; Richardson, D. J.; Reed, G. T.; Petropoulos, P.

2016-02-01

Communication traffic grows relentlessly in today's networks, and with ever more machines connected to the network, this trend is set to continue for the foreseeable future. It is widely accepted that increasingly faster communications are required at the point of the end users, and consequently optical transmission plays a progressively greater role even in short- and medium-reach networks. Silicon photonic technologies are becoming increasingly attractive for such networks, due to their potential for low cost, energetically efficient, high-speed optical components. A representative example is the silicon-based optical modulator, which has been actively studied. Researchers have demonstrated silicon modulators in different types of structures, such as ring resonators or slow light based devices. These approaches have shown remarkably good performance in terms of modulation efficiency, however their operation could be severely affected by temperature drifts or fabrication errors. Mach-Zehnder modulators (MZM), on the other hand, show good performance and resilience to different environmental conditions. In this paper we present a CMOS-compatible compact silicon MZM. We study the application of the modulator to short-reach interconnects by realizing data modulation using some relevant advanced modulation formats, such as 4-level Pulse Amplitude Modulation (PAM-4) and Discrete Multi-Tone (DMT) modulation and compare the performance of the different systems in transmission.

An ultralow power athermal silicon modulator

PubMed Central

Timurdogan, Erman; Sorace-Agaskar, Cheryl M.; Sun, Jie; Shah Hosseini, Ehsan; Biberman, Aleksandr; Watts, Michael R.

2014-01-01

Silicon photonics has emerged as the leading candidate for implementing ultralow power wavelength–division–multiplexed communication networks in high-performance computers, yet current components (lasers, modulators, filters and detectors) consume too much power for the high-speed femtojoule-class links that ultimately will be required. Here we demonstrate and characterize the first modulator to achieve simultaneous high-speed (25 Gb s−1), low-voltage (0.5 VPP) and efficient 0.9 fJ per bit error-free operation. This low-energy high-speed operation is enabled by a record electro-optic response, obtained in a vertical p–n junction device that at 250 pm V−1 (30 GHz V−1) is up to 10 times larger than prior demonstrations. In addition, this record electro-optic response is used to compensate for thermal drift over a 7.5 °C temperature range with little additional energy consumption (0.24 fJ per bit for a total energy consumption below 1.03 J per bit). The combined results of highly efficient modulation and electro-optic thermal compensation represent a new paradigm in modulator development and a major step towards single-digit femtojoule-class communications. PMID:24915772

The correlates of slow gait and its relation with social network among older adults in Singapore.

PubMed

Shafie, Saleha; Shahwan, Shazana; Abdin, Edimansyah; Vaingankar, Janhavi; Picco, Louisa; Sambasivam, Rajeswari; Zhang, Yunjue; Ng, Li Ling; Chong, Siow Ann; Subramaniam, Mythily

2017-11-01

This study aimed to identify socio-demographic correlates of slow gait speed among Singapore older adult residents and to examine the relationship between slow gait speed and the older adult residents' social network, physical health status, disability and mental health status. Trained interviewers administered the adapted 10/66 research protocol through face-to-face interviews to 2565 respondents aged 60 and over. Information on gait test, socio-demographic characteristics, obesity, social network, physical status and activity, overall health, disability and mental health status were collected. The gait test was completed by 2192 participants. Slow gait was defined as walking speed of 1 standard deviation (SD) below age and gender specific mean gait of the sample. The prevalence of slow gait speed after adjusting for age and gender was 13.7%. Slow gait speed was more prevalent among Indians, respondents with low education, and those who were retired. Those with slow gait speed were significantly associated with lower probability of being unemployed and attending religious activities. They were significantly associated with not being physically active and reported a higher disability score. Older adult residents' socio-demographic factors were found to be associated with gait speed. Those with slow gait speed were not physically active and had less frequent contact with people through religious activities and this might place them at risk of being socially isolated, which can have consequences. Gait speed can be included as a routine assessment tool to identify at-risk groups for interventions which aim to keep the older adults socially engaged and healthy.

Multi-epoch VLBA Imaging of 20 New TeV Blazars: Apparent Jet Speeds

NASA Astrophysics Data System (ADS)

Piner, B. Glenn; Edwards, Philip G.

2018-01-01

We present 88 multi-epoch Very Long Baseline Array (VLBA) images (most at an observing frequency of 8 GHz) of 20 TeV blazars, all of the high-frequency-peaked BL Lac (HBL) class, that have not been previously studied at multiple epochs on the parsec scale. From these 20 sources, we analyze the apparent speeds of 43 jet components that are all detected at four or more epochs. As has been found for other TeV HBLs, the apparent speeds of these components are relatively slow. About two-thirds of the components have an apparent speed that is consistent (within 2σ) with no motion, and some of these components may be stationary patterns whose apparent speed does not relate to the underlying bulk flow speed. In addition, a superluminal tail to the apparent speed distribution of the TeV HBLs is detected for the first time, with eight components in seven sources having a 2σ lower limit on the apparent speed exceeding 1c. We combine the data from these 20 sources with an additional 18 sources from the literature to analyze the complete apparent speed distribution of all 38 TeV HBLs that have been studied with very long baseline interferometry at multiple epochs. The highest 2σ apparent speed lower limit considering all sources is 3.6c. This suggests that bulk Lorentz factors of up to about 4, but probably not much higher, exist in the parsec-scale radio-emitting regions of these sources, consistent with estimates obtained in the radio by other means such as brightness temperatures. This can be reconciled with the high Lorentz factors estimated from the high-energy data if the jet has velocity structures consisting of different emission regions with different Lorentz factors. In particular, we analyze the current apparent speed data for the TeV HBLs in the context of a model with a fast central spine and a slower outer layer.

Optical and Radar Measurements of the Meteor Speed Distribution

NASA Technical Reports Server (NTRS)

Moorhead, A. V.; Brown, P. G.; Campbell-Brown, M. D.; Kingery, A.; Cooke, W. J.

2016-01-01

The observed meteor speed distribution provides information on the underlying orbital distribution of Earth-intersecting meteoroids. It also affects spacecraft risk assessments; faster meteors do greater damage to spacecraft surfaces. Although radar meteor networks have measured the meteor speed distribution numerous times, the shape of the de-biased speed distribution varies widely from study to study. Optical characterizations of the meteoroid speed distribution are fewer in number, and in some cases the original data is no longer available. Finally, the level of uncertainty in these speed distributions is rarely addressed. In this work, we present the optical meteor speed distribution extracted from the NASA and SOMN allsky networks [1, 2] and from the Canadian Automated Meteor Observatory (CAMO) [3]. We also revisit the radar meteor speed distribution observed by the Canadian Meteor Orbit Radar (CMOR) [4]. Together, these data span the range of meteoroid sizes that can pose a threat to spacecraft. In all cases, we present our bias corrections and incorporate the uncertainty in these corrections into uncertainties in our de-biased speed distribution. Finally, we compare the optical and radar meteor speed distributions and discuss the implications for meteoroid environment models.

Parallelization and automatic data distribution for nuclear reactor simulations

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

Liebrock, L.M.

1997-07-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directlymore » affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed.« less

Social network based dynamic transit service through the OMITS system.

DOT National Transportation Integrated Search

2014-02-01

The Open Mode Integrated Transportation System (OMITS) forms a sustainable information infrastructure for communication within and between the mobile/Internet network, the roadway : network, and the users social network. It manipulates the speed g...

Regular Topologies for Gigabit Wide-Area Networks. Volume 1

NASA Technical Reports Server (NTRS)

Shacham, Nachum; Denny, Barbara A.; Lee, Diane S.; Khan, Irfan H.; Lee, Danny Y. C.; McKenney, Paul

1994-01-01

In general terms, this project aimed at the analysis and design of techniques for very high-speed networking. The formal objectives of the project were to: (1) Identify switch and network technologies for wide-area networks that interconnect a large number of users and can provide individual data paths at gigabit/s rates; (2) Quantitatively evaluate and compare existing and proposed architectures and protocols, identify their strength and growth potentials, and ascertain the compatibility of competing technologies; and (3) Propose new approaches to existing architectures and protocols, and identify opportunities for research to overcome deficiencies and enhance performance. The project was organized into two parts: 1. The design, analysis, and specification of techniques and protocols for very-high-speed network environments. In this part, SRI has focused on several key high-speed networking areas, including Forward Error Control (FEC) for high-speed networks in which data distortion is the result of packet loss, and the distribution of broadband, real-time traffic in multiple user sessions. 2. Congestion Avoidance Testbed Experiment (CATE). This part of the project was done within the framework of the DARTnet experimental T1 national network. The aim of the work was to advance the state of the art in benchmarking DARTnet's performance and traffic control by developing support tools for network experimentation, by designing benchmarks that allow various algorithms to be meaningfully compared, and by investigating new queueing techniques that better satisfy the needs of best-effort and reserved-resource traffic. This document is the final technical report describing the results obtained by SRI under this project. The report consists of three volumes: Volume 1 contains a technical description of the network techniques developed by SRI in the areas of FEC and multicast of real-time traffic. Volume 2 describes the work performed under CATE. Volume 3 contains the source code of all software developed under CATE.

Study of bidirectional broadband passive optical network (BPON) using EDFA

NASA Astrophysics Data System (ADS)

Almalaq, Yasser

Optical line terminals (OLTs) and number of optical network units (ONUs) are two main parts of passive optical network (PON). OLT is placed at the central office of the service providers, the ONUs are located near to the end subscribers. When compared with point-to-point design, a PON decreases the number of fiber used and central office components required. Broadband PON (BPON), which is one type of PON, can support high-speed voice, data and video services to subscribers' residential homes and small businesses. In this research, by using erbium doped fiber amplifier (EDFA), the performance of bi-directional BPON is experimented and tested for both downstream and upstream traffic directions. Ethernet PON (E-PON) and gigabit PON (G-PON) are the two other kinds of passive optical network besides BPON. The most beneficial factor of using BPON is it's reduced cost. The cost of the maintenance between the central office and the users' side is suitable because of the use of passive components, such as a splitter in the BPON architecture. In this work, a bidirectional BPON has been analyzed for both downstream and upstream cases by using bit error rate analyzer (BER). BER analyzers test three factors that are the maximum Q factor, minimum bit error rate, and eye height. In other words, parameters such as maximum Q factor, minimum bit error rate, and eye height can be analyzed utilized a BER tester. Passive optical components such as a splitter, optical circulator, and filters have been used in modeling and simulations. A 12th edition Optiwave simulator has been used in order to analyze the bidirectional BPON system. The system has been tested under several conditions such as changing the fiber length, extinction ratio, dispersion, and coding technique. When a long optical fiber above 40km was used, an EDFA was used in order to improve the quality of the signal.

Engineering-Aligned 3D Neural Circuit in Microfluidic Device.

PubMed

Bang, Seokyoung; Na, Sangcheol; Jang, Jae Myung; Kim, Jinhyun; Jeon, Noo Li

2016-01-07

The brain is one of the most important and complex organs in the human body. Although various neural network models have been proposed for in vitro 3D neuronal networks, it has been difficult to mimic functional and structural complexity of the in vitro neural circuit. Here, a microfluidic model of a simplified 3D neural circuit is reported. First, the microfluidic device is filled with Matrigel and continuous flow is delivered across the device during gelation. The fluidic flow aligns the extracellular matrix (ECM) components along the flow direction. Following the alignment of ECM fibers, neurites of primary rat cortical neurons are grown into the Matrigel at the average speed of 250 μm d(-1) and form axon bundles approximately 1500 μm in length at 6 days in vitro (DIV). Additionally, neural networks are developed from presynaptic to postsynaptic neurons at 14 DIV. The establishment of aligned 3D neural circuits is confirmed with the immunostaining of PSD-95 and synaptophysin and the observation of calcium signal transmission. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Path integration of head direction: updating a packet of neural activity at the correct speed using axonal conduction delays.

PubMed

Walters, Daniel; Stringer, Simon; Rolls, Edmund

2013-01-01

The head direction cell system is capable of accurately updating its current representation of head direction in the absence of visual input. This is known as the path integration of head direction. An important question is how the head direction cell system learns to perform accurate path integration of head direction. In this paper we propose a model of velocity path integration of head direction in which the natural time delay of axonal transmission between a linked continuous attractor network and competitive network acts as a timing mechanism to facilitate the correct speed of path integration. The model effectively learns a "look-up" table for the correct speed of path integration. In simulation, we show that the model is able to successfully learn two different speeds of path integration across two different axonal conduction delays, and without the need to alter any other model parameters. An implication of this model is that, by learning look-up tables for each speed of path integration, the model should exhibit a degree of robustness to damage. In simulations, we show that the speed of path integration is not significantly affected by degrading the network through removing a proportion of the cells that signal rotational velocity.

Path Integration of Head Direction: Updating a Packet of Neural Activity at the Correct Speed Using Axonal Conduction Delays

PubMed Central

Walters, Daniel; Stringer, Simon; Rolls, Edmund

2013-01-01

The head direction cell system is capable of accurately updating its current representation of head direction in the absence of visual input. This is known as the path integration of head direction. An important question is how the head direction cell system learns to perform accurate path integration of head direction. In this paper we propose a model of velocity path integration of head direction in which the natural time delay of axonal transmission between a linked continuous attractor network and competitive network acts as a timing mechanism to facilitate the correct speed of path integration. The model effectively learns a “look-up” table for the correct speed of path integration. In simulation, we show that the model is able to successfully learn two different speeds of path integration across two different axonal conduction delays, and without the need to alter any other model parameters. An implication of this model is that, by learning look-up tables for each speed of path integration, the model should exhibit a degree of robustness to damage. In simulations, we show that the speed of path integration is not significantly affected by degrading the network through removing a proportion of the cells that signal rotational velocity. PMID:23526976

High-Performance Computing: High-Speed Computer Networks in the United States, Europe, and Japan. Report to Congressional Requesters.

ERIC Educational Resources Information Center

General Accounting Office, Washington, DC. Information Management and Technology Div.

This report was prepared in response to a request from the Senate Committee on Commerce, Science, and Transportation, and from the House Committee on Science, Space, and Technology, for information on efforts to develop high-speed computer networks in the United States, Europe (limited to France, Germany, Italy, the Netherlands, and the United…

Peregrine System Configuration | High-Performance Computing | NREL

Science.gov Websites

nodes and storage are connected by a high speed InfiniBand network. Compute nodes are diskless with an directories are mounted on all nodes, along with a file system dedicated to shared projects. A brief processors with 64 GB of memory. All nodes are connected to the high speed Infiniband network and and a

Integrated travel network model for studying epidemics: Interplay between journeys and epidemic

PubMed Central

Ruan, Zhongyuan; Wang, Chaoqing; Ming Hui, Pak; Liu, Zonghua

2015-01-01

The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller’s viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading. PMID:26073191

Integrated travel network model for studying epidemics: Interplay between journeys and epidemic

NASA Astrophysics Data System (ADS)

Ruan, Zhongyuan; Wang, Chaoqing; Ming Hui, Pak; Liu, Zonghua

2015-06-01

The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller’s viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading.

Integrated travel network model for studying epidemics: Interplay between journeys and epidemic.

PubMed

Ruan, Zhongyuan; Wang, Chaoqing; Hui, Pak Ming; Liu, Zonghua

2015-06-15

The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller's viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading.

The neural correlates of reading fluency deficits in children.

PubMed

Langer, Nicolas; Benjamin, Christopher; Minas, Jennifer; Gaab, Nadine

2015-06-01

Multiple studies have shown that individuals with a reading disability (RD) demonstrate deficits in posterior left-hemispheric brain regions during reading-related tasks. These studies mainly focused on reading sub-skills, and it remains debated whether such dysfunction is apparent during more ecologically valid reading skills, such as reading fluency. In this fMRI study, reading fluency was systematically varied to characterize neural correlates of reading fluency in 30 children with (RD) and without (typical developing children, TYP) a RD. Sentences were presented at constrained, comfortable, and accelerated speeds, which were determined based on individual reading speed. Behaviorally, RD children displayed decreased performance in several reading-related tasks. Using fMRI, we demonstrated that both TYP and RD children display increased activation in several components of the reading network during fluent reading. When required to read at an accelerated speed, RD children exhibited less activation in the fusiform gyrus (FG) compared with the TYP children. A region of interest analysis substantiated differences in the FG and demonstrated a relationship to behavioral reading performance. These results suggest that the FG plays a key role in fluent reading and that it can be modulated by speed. These results and their implications for remediation strategies should be considered in educational practice. Published by Oxford University Press 2013. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Compressor and Turbine Multidisciplinary Design for Highly Efficient Micro-gas Turbine

NASA Astrophysics Data System (ADS)

Barsi, Dario; Perrone, Andrea; Qu, Yonglei; Ratto, Luca; Ricci, Gianluca; Sergeev, Vitaliy; Zunino, Pietro

2018-06-01

Multidisciplinary design optimization (MDO) is widely employed to enhance turbomachinery components efficiency. The aim of this work is to describe a complete tool for the aero-mechanical design of a radial inflow turbine and a centrifugal compressor. The high rotational speed of such machines and the high exhaust gas temperature (only for the turbine) expose blades to really high stresses and therefore the aerodynamics design has to be coupled with the mechanical one through an integrated procedure. The described approach employs a fully 3D Reynolds Averaged Navier-Stokes (RANS) solver for the aerodynamics and an open source Finite Element Analysis (FEA) solver for the mechanical integrity assessment. Due to the high computational cost of both these two solvers, a meta model, such as an artificial neural network (ANN), is used to speed up the optimization design process. The interaction between two codes, the mesh generation and the post processing of the results are achieved via in-house developed scripting modules. The obtained results are widely presented and discussed.

Grumman WS33 wind system. Phase II: executive summary. Prototype construction and testing

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

Adler, F M; Hinton, P; King, P W

1980-11-01

The configuration of an 8 kW wind turbine generator and its fabrication and pre-delivery testing are discussed. The machine is a three-bladed, down wind turbine designed to interface directly with an electrical utility network. Power is generated in winds between a cut-in speed of 4.0 m/s and a cut-out speed of 22 m/s. A blade pitch control system provides for positioning the rotor at a coarse pitch for start-up, fine pitch for normal running, and a feather position for shut-down. Operation of the machine is controlled by a self-monitoring, programmable logic microprocessor. System components were obtained through a series ofmore » make-buy decisions, tracked and inspected for specification compliance. Only minor modifications from the original design and minor problems of assembly are reported. Four accelerometers were mounted inside the nacelle to determine the accelerations, frequencies and displacements of the system in the three orthogonal axes. A cost analysis is updated. (LEW)« less

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction

PubMed Central

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-01

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods. PMID:29342857

An Adaptive Deghosting Method in Neural Network-Based Infrared Detectors Nonuniformity Correction.

PubMed

Li, Yiyang; Jin, Weiqi; Zhu, Jin; Zhang, Xu; Li, Shuo

2018-01-13

The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods.

High-speed digital wireless battlefield network

NASA Astrophysics Data System (ADS)

Dao, Son K.; Zhang, Yongguang; Shek, Eddie C.; van Buer, Darrel

1999-07-01

In the past two years, the Digital Wireless Battlefield Network consortium that consists of HRL Laboratories, Hughes Network Systems, Raytheon, and Stanford University has participated in the DARPA TRP program to leverage the efforts in the development of commercial digital wireless products for use in the 21st century battlefield. The consortium has developed an infrastructure and application testbed to support the digitized battlefield. The consortium has implemented and demonstrated this network system. Each member is currently utilizing many of the technology developed in this program in commercial products and offerings. These new communication hardware/software and the demonstrated networking features will benefit military systems and will be applicable to the commercial communication marketplace for high speed voice/data multimedia distribution services.

Idealized models of the joint probability distribution of wind speeds

NASA Astrophysics Data System (ADS)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Considerations for the future development of virtual technology as a rehabilitation tool

PubMed Central

Kenyon, Robert V; Leigh, Jason; Keshner, Emily A

2004-01-01

Background Virtual environments (VE) are a powerful tool for various forms of rehabilitation. Coupling VE with high-speed networking [Tele-Immersion] that approaches speeds of 100 Gb/sec can greatly expand its influence in rehabilitation. Accordingly, these new networks will permit various peripherals attached to computers on this network to be connected and to act as fast as if connected to a local PC. This innovation may soon allow the development of previously unheard of networked rehabilitation systems. Rapid advances in this technology need to be coupled with an understanding of how human behavior is affected when immersed in the VE. Methods This paper will discuss various forms of VE that are currently available for rehabilitation. The characteristic of these new networks and examine how such networks might be used for extending the rehabilitation clinic to remote areas will be explained. In addition, we will present data from an immersive dynamic virtual environment united with motion of a posture platform to record biomechanical and physiological responses to combined visual, vestibular, and proprioceptive inputs. A 6 degree-of-freedom force plate provides measurements of moments exerted on the base of support. Kinematic data from the head, trunk, and lower limb was collected using 3-D video motion analysis. Results Our data suggest that when there is a confluence of meaningful inputs, neither vision, vestibular, or proprioceptive inputs are suppressed in healthy adults; the postural response is modulated by all existing sensory signals in a non-additive fashion. Individual perception of the sensory structure appears to be a significant component of the response to these protocols and underlies much of the observed response variability. Conclusion The ability to provide new technology for rehabilitation services is emerging as an important option for clinicians and patients. The use of data mining software would help analyze the incoming data to provide both the patient and the therapist with evaluation of the current treatment and modifications needed for future therapies. Quantification of individual perceptual styles in the VE will support development of individualized treatment programs. The virtual environment can be a valuable tool for therapeutic interventions that require adaptation to complex, multimodal environments. PMID:15679951

Call for Papers: Photonics in Switching

NASA Astrophysics Data System (ADS)

Wosinska, Lena; Glick, Madeleine

2006-04-01

Call for Papers: Photonics in Switching

Guest Editors:

Lena Wosinska, Royal Institute of Technology (KTH) / ICT Sweden Madeleine Glick, Intel Research, Cambridge, UK

Scope of Submission

• WDM node architectures
• Novel device technologies enabling photonics in switching, such as optical switch fabrics, optical memory, and wavelength conversion
• Routing protocols
• WDM switching and routing
• Quality of service
• Performance measurement and evaluation
• Next-generation optical networks: architecture, signaling, and control
• Traffic measurement and field trials
• Optical burst and packet switching
• OBS/OPS node architectures
• Burst/Packet scheduling and routing algorithms
• Contention resolution/avoidance strategies
• Services and applications for OBS/OPS (e.g., grid networks, storage-area networks, etc.)
• Burst assembly and ingress traffic shaping
• Hybrid OBS/TDM or OBS/wavelength routing

Manuscript Submission

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, D.B.

1996-12-31

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor to a plurality of slave processors to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor`s status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer, a digital signal processor, a parallel transfer controller, and two three-port memory devices. A communication switch within each node connects it to a fast parallel hardware channel through which all high density data arrives or leaves the node. 6 figs.

Parallel processing data network of master and slave transputers controlled by a serial control network

DOEpatents

Crosetto, Dario B.

1996-01-01

The present device provides for a dynamically configurable communication network having a multi-processor parallel processing system having a serial communication network and a high speed parallel communication network. The serial communication network is used to disseminate commands from a master processor (100) to a plurality of slave processors (200) to effect communication protocol, to control transmission of high density data among nodes and to monitor each slave processor's status. The high speed parallel processing network is used to effect the transmission of high density data among nodes in the parallel processing system. Each node comprises a transputer (104), a digital signal processor (114), a parallel transfer controller (106), and two three-port memory devices. A communication switch (108) within each node (100) connects it to a fast parallel hardware channel (70) through which all high density data arrives or leaves the node.

Optical Ethernet

NASA Astrophysics Data System (ADS)

Chan, Calvin C. K.; Lam, Cedric F.; Tsang, Danny H. K.

2005-09-01

Call for Papers: Optical Ethernet The Journal of Optical Networking (JON) is soliciting papers for a second feature issue on Optical Ethernet. Ethernet has evolved from a LAN technology connecting desktop computers to a universal broadband network interface. It is not only the vehicle for local data connectivity but also the standard interface for next-generation network equipment such as video servers and IP telephony. High-speed Ethernet has been increasingly assuming the volume of backbone network traffic from SONET/SDH-based circuit applications. It is clear that IP has become the universal network protocol for future converged networks, and Ethernet is becoming the ubiquitous link layer for connectivity. Network operators have been offering Ethernet services for several years. Problems and new requirements in Ethernet service offerings have been captured through previous experience. New study groups and standards bodies have been formed to address these problems. This feature issue aims at reviewing and updating the new developments and R&D efforts of high-speed Ethernet in recent years, especially those related to the field of optical networking. Scope of Submission The scope of the papers includes, but is not limited to, the following: Ethernet PHY development 10-Gbit Ethernet on multimode fiber Native Ethernet transport and Ethernet on legacy networks EPON Ethernet OAM Resilient packet ring (RPR) and Ethernet QoS definition and management on Ethernet Ethernet protection switching Circuit emulation services on Ethernet Transparent LAN service development Carrier VLAN and Ethernet Ethernet MAC frame expansion Ethernet switching High-speed Ethernet applications Economic models of high-speed Ethernet services Ethernet field deployment and standard activities To submit to this special issue, follow the normal procedure for submission to JON, indicating "Optical Ethernet feature" in the "Comments" field of the online submission form. For all other questions relating to this feature issue, please send an e-mail to jon@osa.org, subject line "Optical Ethernet." Additional information can be found on the JON website: http://www.osa-jon.org/submission/

Efficient Low-Lift Cooling with Radiant Distribution, Thermal Storage and Variable-Speed Chiller Controls Part I: Component and Subsystem Models

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

Armstrong, Peter; Jiang, Wei; Winiarski, David W.

2009-03-31

this paper develops component and subsystem models used to evaluat4e the performance of a low-lift cooling system with an air-colled chiller optimized for variable-speed and low-pressure-ratio operation, a hydronic radient distribution system, variable-speed transport miotor controls, and peak-shifting controls.

Host-Based Systemic Network Obfuscation System for Windows

DTIC Science & Technology

2011-06-01

speed, CPU speed, and memory size. These additional parameters are control variables and do not change throughout the experiment. The applications...physical median that passes the network traffic, such as a wireless signal or Ethernet cable and does not need obfuscation. The colored layers in Figure...Gul09] Ron Gula, “ Enchanced Operating System Identification with Nessus.” [Online]. Available: http://blog.tenablesecurity.com/2009/02

A Systems Approach to Scalable Transportation Network Modeling

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

Perumalla, Kalyan S

2006-01-01

Emerging needs in transportation network modeling and simulation are raising new challenges with respect to scal-ability of network size and vehicular traffic intensity, speed of simulation for simulation-based optimization, and fidel-ity of vehicular behavior for accurate capture of event phe-nomena. Parallel execution is warranted to sustain the re-quired detail, size and speed. However, few parallel simulators exist for such applications, partly due to the challenges underlying their development. Moreover, many simulators are based on time-stepped models, which can be computationally inefficient for the purposes of modeling evacuation traffic. Here an approach is presented to de-signing a simulator with memory andmore » speed efficiency as the goals from the outset, and, specifically, scalability via parallel execution. The design makes use of discrete event modeling techniques as well as parallel simulation meth-ods. Our simulator, called SCATTER, is being developed, incorporating such design considerations. Preliminary per-formance results are presented on benchmark road net-works, showing scalability to one million vehicles simu-lated on one processor.« less

Internet Basics. ERIC Digest.

ERIC Educational Resources Information Center

Tennant, Roy

The Internet is a worldwide network of computer networks. In the United States, the National Science Foundation Network (NSFNet) serves as the Internet "backbone" (a very high speed network that connects key regions across the country). The NSFNet will likely evolve into the National Research and Education Network (NREN) as defined in…

A Novel Approach to Constrain Near-Surface Seismic Wave Speed Based on Polarization Analysis

NASA Astrophysics Data System (ADS)

Park, S.; Ishii, M.

2016-12-01

Understanding the seismic responses of cities around the world is essential for the risk assessment of earthquake hazards. One of the important parameters is the elastic structure of the sites, in particular, near-surface seismic wave speed, that influences the level of ground shaking. Many methods have been developed to constrain the elastic structure of the populated sites or urban basins, and here, we introduce a new technique based on analyzing the polarization content or the three-dimensional particle motion of seismic phases arriving at the sites. Polarization analysis of three-component seismic data was widely used up to about two decades ago, to detect signals and identify different types of seismic arrivals. Today, we have good understanding of the expected polarization direction and ray parameter for seismic wave arrivals that are calculated based on a reference seismic model. The polarization of a given phase is also strongly sensitive to the elastic wave speed immediately beneath the station. This allows us to compare the observed and predicted polarization directions of incoming body waves and infer the near-surface wave speed. This approach is applied to High-Sensitivity Seismograph Network in Japan, where we benchmark the results against the well-log data that are available at most stations. There is a good agreement between our estimates of seismic wave speeds and those from well logs, confirming the efficacy of the new method. In most urban environments, where well logging is not a practical option for measuring the seismic wave speeds, this method can provide a reliable, non-invasive, and computationally inexpensive estimate of near-surface elastic properties.

A complex network-based importance measure for mechatronics systems

NASA Astrophysics Data System (ADS)

Wang, Yanhui; Bi, Lifeng; Lin, Shuai; Li, Man; Shi, Hao

2017-01-01

In view of the negative impact of functional dependency, this paper attempts to provide an alternative importance measure called Improved-PageRank (IPR) for measuring the importance of components in mechatronics systems. IPR is a meaningful extension of the centrality measures in complex network, which considers usage reliability of components and functional dependency between components to increase importance measures usefulness. Our work makes two important contributions. First, this paper integrates the literature of mechatronic architecture and complex networks theory to define component network. Second, based on the notion of component network, a meaningful IPR is brought into the identifying of important components. In addition, the IPR component importance measures, and an algorithm to perform stochastic ordering of components due to the time-varying nature of usage reliability of components and functional dependency between components, are illustrated with a component network of bogie system that consists of 27 components.

Non-equilibrium physics of neural networks for leaning, memory and decision making: landscape and flux perspectives

NASA Astrophysics Data System (ADS)

Wang, Jin

Cognitive behaviors are determined by underlying neural networks. Many brain functions, such as learning and memory, can be described by attractor dynamics. We developed a theoretical framework for global dynamics by quantifying the landscape associated with the steady state probability distributions and steady state curl flux, measuring the degree of non-equilibrium through detailed balance breaking. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. Both landscape and flux determine the kinetic paths and speed of decision making. The kinetics and global stability of decision making are explored by quantifying the landscape topography through the barrier heights and the mean first passage time. The theoretical predictions are in agreement with experimental observations: more errors occur under time pressure. We quantitatively explored two mechanisms of the speed-accuracy tradeoff with speed emphasis and further uncovered the tradeoffs among speed, accuracy, and energy cost. Our results show an optimal balance among speed, accuracy, and the energy cost in decision making. We uncovered possible mechanisms of changes of mind and how mind changes improve performance in decision processes. Our landscape approach can help facilitate an understanding of the underlying physical mechanisms of cognitive processes and identify the key elements in neural networks.

Short-term wind speed prediction based on the wavelet transformation and Adaboost neural network

NASA Astrophysics Data System (ADS)

Hai, Zhou; Xiang, Zhu; Haijian, Shao; Ji, Wu

2018-03-01

The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.

Research of x-ray nondestructive detector for high-speed running conveyor belt with steel wire ropes

NASA Astrophysics Data System (ADS)

Wang, Junfeng; Miao, Changyun; Wang, Wei; Lu, Xiaocui

2008-03-01

An X-ray nondestructive detector for high-speed running conveyor belt with steel wire ropes is researched in the paper. The principle of X-ray nondestructive testing (NDT) is analyzed, the general scheme of the X-ray nondestructive testing system is proposed, and the nondestructive detector for high-speed running conveyor belt with steel wire ropes is developed. The hardware of system is designed with Xilinx's VIRTEX-4 FPGA that embeds PowerPC and MAC IP core, and its network communication software based on TCP/IP protocol is programmed by loading LwIP to PowerPC. The nondestructive testing of high-speed conveyor belt with steel wire ropes and network transfer function are implemented. It is a strong real-time system with rapid scanning speed, high reliability and remotely nondestructive testing function. The nondestructive detector can be applied to the detection of product line in industry.

System and method to determine thermophysical properties of a multi-component gas

DOEpatents

Morrow, Thomas B.; Behring, II, Kendricks A.

2003-08-05

A system and method to characterize natural gas hydrocarbons using a single inferential property, such as standard sound speed, when the concentrations of the diluent gases (e.g., carbon dioxide and nitrogen) are known. The system to determine a thermophysical property of a gas having a first plurality of components comprises a sound velocity measurement device, a concentration measurement device, and a processor to determine a thermophysical property as a function of a correlation between the thermophysical property, the speed of sound, and the concentration measurements, wherein the number of concentration measurements is less than the number of components in the gas. The method includes the steps of determining the speed of sound in the gas, determining a plurality of gas component concentrations in the gas, and determining the thermophysical property as a function of a correlation between the thermophysical property, the speed of sound, and the plurality of concentrations.

The high speed interconnect system architecture and operation

NASA Astrophysics Data System (ADS)

Anderson, Steven C.

The design and operation of a fiber-optic high-speed interconnect system (HSIS) being developed to meet the requirements of future avionics and flight-control hardware with distributed-system architectures are discussed. The HSIS is intended for 100-Mb/s operation of a local-area network with up to 256 stations. It comprises a bus transmission system (passive star couplers and linear media linked by active elements) and network interface units (NIUs). Each NIU is designed to perform the physical, data link, network, and transport functions defined by the ISO OSI Basic Reference Model (1982 and 1983) and incorporates a fiber-optic transceiver, a high-speed protocol based on the SAE AE-9B linear token-passing data bus (1986), and a specialized application interface unit. The operating modes and capabilities of HSIS are described in detail and illustrated with diagrams.

Traffic signal coordination and queue management in oversaturated intersection.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network : performance by reducing delay, increasing network throughput, reducing number of stops, or : increasing average speed in the network. The optimization can be...

Traffic signal coordination and queue management in oversaturated intersections.

DOT National Transportation Integrated Search

2011-03-18

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become...

Repeatable, accurate, and high speed multi-level programming of memristor 1T1R arrays for power efficient analog computing applications.

PubMed

Merced-Grafals, Emmanuelle J; Dávila, Noraica; Ge, Ning; Williams, R Stanley; Strachan, John Paul

2016-09-09

Beyond use as high density non-volatile memories, memristors have potential as synaptic components of neuromorphic systems. We investigated the suitability of tantalum oxide (TaOx) transistor-memristor (1T1R) arrays for such applications, particularly the ability to accurately, repeatedly, and rapidly reach arbitrary conductance states. Programming is performed by applying an adaptive pulsed algorithm that utilizes the transistor gate voltage to control the SET switching operation and increase programming speed of the 1T1R cells. We show the capability of programming 64 conductance levels with <0.5% average accuracy using 100 ns pulses and studied the trade-offs between programming speed and programming error. The algorithm is also utilized to program 16 conductance levels on a population of cells in the 1T1R array showing robustness to cell-to-cell variability. In general, the proposed algorithm results in approximately 10× improvement in programming speed over standard algorithms that do not use the transistor gate to control memristor switching. In addition, after only two programming pulses (an initialization pulse followed by a programming pulse), the resulting conductance values are within 12% of the target values in all cases. Finally, endurance of more than 10(6) cycles is shown through open-loop (single pulses) programming across multiple conductance levels using the optimized gate voltage of the transistor. These results are relevant for applications that require high speed, accurate, and repeatable programming of the cells such as in neural networks and analog data processing.

Best facilitated cortical activation during different stepping, treadmill, and robot-assisted walking training paradigms and speeds: A functional near-infrared spectroscopy neuroimaging study.

PubMed

Kim, Ha Yeon; Yang, Sung Phil; Park, Gyu Lee; Kim, Eun Joo; You, Joshua Sung Hyun

2016-01-01

Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during different gait training modes and speeds. The present optical imaging study compared cortical activities during conventional stepping walking (SW), treadmill walking (TW), and robot-assisted walking (RW) at different speeds. Fourteen healthy subjects (6 women, mean age 30.06, years ± 4.53) completed three walking training modes (SW, TW, and RW) at various speeds (self-selected, 1.5, 2.0, 2.5, and 3.0  km/h). A functional near-infrared spectroscopy (fNIRS) system determined cerebral hemodynamic changes associated with cortical locomotor network areas in the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC). There was increased cortical activation in the SMC, PMC, and SMA during different walking training modes. More global locomotor network activation was observed during RW than TW or SW. As walking speed increased, multiple locomotor network activations were observed, and increased activation power spectrum. This is the first empirical evidence highlighting the neural substrates mediating dynamic locomotion for different gait training modes and speeds. Fast, robot-assisted gait training best facilitated cortical activation associated with locomotor control.

From Romance to Rocket Science: Speed Dating in Higher Education

ERIC Educational Resources Information Center

Muurlink, Olav; Poyatos Matas, Cristina

2011-01-01

This article is the first comprehensive review of speed dating in the tertiary sector. While speed dating has its origins as a networking technique to connect singles, it has only more recently made its way into the academy. Since 2005 universities world-wide have begun to adopt speed dating protocols as a tool for building research culture. An…

Developing seamless connections in the urban transit network : a look toward high-speed rail interconnectivity.

DOT National Transportation Integrated Search

2014-07-01

In the past, U.S. studies on high-speed rail (HSR) have focused primarily on the economic implications of high-speed rail development. Recently, however, studies have begun evaluating multimodal connectivity of HSR stations. The ways in which differe...

Advanced Gas Turbine (AGT) power-train system development

NASA Technical Reports Server (NTRS)

Helms, H. E.; Johnson, R. A.; Gibson, R. K.

1982-01-01

Technical work on the design and component testing of a 74.5 kW (100 hp) advanced automotive gas turbine is described. Selected component ceramic component design, and procurement were tested. Compressor tests of a modified rotor showed high speed performance improvement over previous rotor designs; efficiency improved by 2.5%, corrected flow by 4.6%, and pressure ratio by 11.6% at 100% speed. The aerodynamic design is completed for both the gasifier and power turbines. Ceramic (silicon carbide) gasifier rotors were spin tested to failure. Improving strengths is indicated by burst speeds and the group of five rotors failed at speeds between 104% and 116% of engine rated speed. The emission results from combustor testing showed NOx levels to be nearly one order of magnitude lower than with previous designs. A one piece ceramic exhaust duct/regenerator seal platform is designed with acceptable low stress levels.

Optical datacenter network employing slotted (TDMA) operation for dynamic resource allocation

NASA Astrophysics Data System (ADS)

Bakopoulos, P.; Tokas, K.; Spatharakis, C.; Patronas, I.; Landi, G.; Christodoulopoulos, K.; Capitani, M.; Kyriakos, A.; Aziz, M.; Reisis, D.; Varvarigos, E.; Zahavi, E.; Avramopoulos, H.

2018-02-01

The soaring traffic demands in datacenter networks (DCNs) are outpacing progresses in CMOS technology, challenging the bandwidth and energy scalability of currently established technologies. Optical switching is gaining traction as a promising path for sustaining the explosive growth of DCNs; however, its practical deployment necessitates extensive modifications to the network architecture and operation, tailored to the technological particularities of optical switches (i.e. no buffering, limitations in radix size and speed). European project NEPHELE is developing an optical network infrastructure that leverages optical switching within a software-defined networking (SDN) framework to overcome the bandwidth and energy scaling challenges of datacenter networks. An experimental validation of the NEPHELE data plane is reported based on commercial off-the-shelf optical components controlled by FPGA boards. To facilitate dynamic allocation of the network resources and perform collision-free routing in a lossless network environment, slotted operation is employed (i.e. using time-division multiple-access - TDMA). Error-free operation of the NEPHELE data plane is verified for 200 μs slots in various scenarios that involve communication between Ethernet hosts connected to custom-designed top-of-rack (ToR) switches, located in the same or in different datacenter pods. Control of the slotted data plane is obtained through an SDN framework comprising an OpenDaylight controller with appropriate add-ons. Communication between servers in the optical-ToR is demonstrated with various routing scenarios, concerning communication between hosts located in the same rack or in different racks, within the same or different datacenter pods. Error-free operation is confirmed for all evaluated scenarios, underpinning the feasibility of the NEPHELE architecture.

Judged effectiveness of threat and coping appraisal anti-speeding messages.

PubMed

Cathcart, Rachel L; Glendon, A Ian

2016-11-01

Using a young driver sample, this experimental study sought to identify which combinations of threat-appraisal (TA) and coping-appraisal (CA) messages derived from protection motivation theory (PMT) participants would judge as most effective for themselves, and for other drivers. The criterion variable was reported intention to drive within a signed speed limit. All possible TA/CA combinations of 18 previously highly-rated anti-speeding messages were presented both simultaneously and sequentially. These represented PMT's three TA components: severity, vulnerability, and rewards, and three CA components: self-efficacy, response efficacy, and response costs. Eighty-eight young drivers (34 males) each rated 54 messages for perceived effectiveness for self and other drivers. Messages derived from the TA severity component were judged the most effective. Response cost messages were most effective for females. Reverse third-person effects were found for both females and males, which suggested that combining TA and CA components may increase the perceived relevance of anti-speeding messages for males. The findings have potential value for creating effective roadside anti-speeding messages, meriting further investigation in field studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Highly survivable bed pressure mat remote patient monitoring system for mHealth.

PubMed

Joshi, Vilas; Holtzman, Megan; Arcelus, Amaya; Goubran, Rafik; Knoefel, Frank

2012-01-01

The high speed mobile networks like 4G and beyond are making a ubiquitous remote patient monitoring (RPM) system using multiple sensors and wireless sensor networks a realistic possibility. The high speed wireless RPM system will be an integral part of the mobile health (mHealth) paradigm reducing cost and providing better service to the patients. While the high speed wireless RPM system will allow clinicians to monitor various chronic and acute medical conditions, the reliability of such system will depend on the network Quality of Service (QoS). The RPM system needs to be resilient to temporary reduced network QoS. This paper presents a highly survivable bed pressure mat RPM system design using an adaptive information content management methodology for the monitored sensor data. The proposed design improves the resiliency of the RPM system under adverse network conditions like congestion and/or temporary loss of connectivity. It also shows how the proposed RPM system can reduce the information rate and correspondingly reduce the data transfer rate by a factor of 5.5 and 144 to address temporary network congestion. The RPM system data rate reduction results in a lower specificity and sensitivity for the features being monitored but increases the survivability of the system from 1 second to 2.4 minutes making it highly robust.

Distributed processing method for arbitrary view generation in camera sensor network

NASA Astrophysics Data System (ADS)

Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

2003-05-01

Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

Performance and component frontal areas of a hypothetical two-spool turbojet engine for three modes of operation

NASA Technical Reports Server (NTRS)

Dugan, James F , Jr

1955-01-01

Engine performance is better for constant outer-spool mechanical-speed operation than for constant inner-spool mechanical-speed operation over most of the flight range considered. Combustor and afterburner frontal areas are about the same for the two modes. Engine performance for a mode characterized by a constant outer-spool equivalent speed over part of the flight range and a constant outer-spool mechanical speed over the rest of the flight range is better that that for constant outer-spool mechanical speed operation. The former mode requires larger outer-spool centrifugal stresses and larger component frontal areas.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

PubMed

Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

High speed all-optical networks

NASA Technical Reports Server (NTRS)

Chlamtac, Imrich

1993-01-01

An inherent problem of conventional point-to-point WAN architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. This report presents the first solution to WDM based WAN networks that overcomes this limitation. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs.

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Code 672 observational science branch computer networks

NASA Technical Reports Server (NTRS)

Hancock, D. W.; Shirk, H. G.

1988-01-01

In general, networking increases productivity due to the speed of transmission, easy access to remote computers, ability to share files, and increased availability of peripherals. Two different networks within the Observational Science Branch are described in detail.

Fast packet switching algorithms for dynamic resource control over ATM networks

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

Tsang, R.P.; Keattihananant, P.; Chang, T.

1996-12-01

Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less

Actor and partner effects of perceived HIV stigma on social network components among people living with HIV/AIDS and their caregivers

PubMed Central

Hao, Chun; Liu, Hongjie

2014-01-01

Background Few studies have investigated the relationship between HIV stigma and social network components at the dyadic level. The objective of this study was to examine the actor and partner effects of perceived HIV stigma by people living with HIV/AIDS (PLWHAs) and their caregivers on social network variables at the dyadic level. Method An egocentric social network study was conducted among 147 dyads consisting of one PLWHA and one caregiver (294 participants) in Nanning, China. The actor-partner interdependence model (APIM) was used to analyze the relationships between perceived HIV stigma and social network components (network relations, network structures, and network functions) at the dyadic level. Results We found in this dyadic analysis that: (1) social network components were similar between PLWHAs and their caregivers; (2) HIV stigma perceived by PLWHAs influenced their own social network components, whereas this influence did not exist between caregivers' perceived HIV stigma and their own social network components; (3) a few significant partner effects were observed between HIV stigma and social network components among both PLWHAs and caregivers. Conclusion The interrelationships between HIV stigma and social network components were complex at the dyadic level. Future interventions programs targeting HIV stigma should focus on the interpersonal relationship at the dyadic level, beyond the intrapersonal factors. PMID:25085478

Actor and partner effects of perceived HIV stigma on social network components among people living with HIV/AIDS and their caregivers.

PubMed

Hao, Chun; Liu, Hongjie

2015-06-01

Few studies have investigated the relationship between HIV stigma and social network components at the dyadic level. The objective of this study was to examine the actor and partner effects of perceived HIV stigma by people living with HIV/AIDS (PLWHAs) and their caregivers on social network variables at the dyadic level. An egocentric social network study was conducted among 147 dyads consisting of one PLWHA and one caregiver (294 participants) in Nanning, China. The actor-partner interdependence model (APIM) was used to analyze the relationships between perceived HIV stigma and social network components (network relations, network structures, and network functions) at the dyadic level. We found in this dyadic analysis that: (1) social network components were similar between PLWHAs and their caregivers; (2) HIV stigma perceived by PLWHAs influenced their own social network components, whereas this influence did not exist between caregivers' perceived HIV stigma and their own social network components; (3) a few significant partner effects were observed between HIV stigma and social network components among both PLWHAs and caregivers. The interrelationships between HIV stigma and social network components were complex at the dyadic level. Future interventions programs targeting HIV stigma should focus on the interpersonal relationship at the dyadic level, beyond the intrapersonal factors. © The Author(s) 2014.

High-performance reconfigurable hardware architecture for restricted Boltzmann machines.

PubMed

Ly, Daniel Le; Chow, Paul

2010-11-01

Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications has been limited. A primary cause for this lack of adoption is that neural networks are usually implemented as software running on general-purpose processors. Hence, a hardware implementation that can exploit the inherent parallelism in neural networks is desired. This paper investigates how the restricted Boltzmann machine (RBM), which is a popular type of neural network, can be mapped to a high-performance hardware architecture on field-programmable gate array (FPGA) platforms. The proposed modular framework is designed to reduce the time complexity of the computations through heavily customized hardware engines. A method to partition large RBMs into smaller congruent components is also presented, allowing the distribution of one RBM across multiple FPGA resources. The framework is tested on a platform of four Xilinx Virtex II-Pro XC2VP70 FPGAs running at 100 MHz through a variety of different configurations. The maximum performance was obtained by instantiating an RBM of 256 × 256 nodes distributed across four FPGAs, which resulted in a computational speed of 3.13 billion connection-updates-per-second and a speedup of 145-fold over an optimized C program running on a 2.8-GHz Intel processor.

Queueing models for token and slotted ring networks. Thesis

NASA Technical Reports Server (NTRS)

Peden, Jeffery H.

1990-01-01

Currently the end-to-end delay characteristics of very high speed local area networks are not well understood. The transmission speed of computer networks is increasing, and local area networks especially are finding increasing use in real time systems. Ring networks operation is generally well understood for both token rings and slotted rings. There is, however, a severe lack of queueing models for high layer operation. There are several factors which contribute to the processing delay of a packet, as opposed to the transmission delay, e.g., packet priority, its length, the user load, the processor load, the use of priority preemption, the use of preemption at packet reception, the number of processors, the number of protocol processing layers, the speed of each processor, and queue length limitations. Currently existing medium access queueing models are extended by adding modeling techniques which will handle exhaustive limited service both with and without priority traffic, and modeling capabilities are extended into the upper layers of the OSI model. Some of the model are parameterized solution methods, since it is shown that certain models do not exist as parameterized solutions, but rather as solution methods.

Emergent Network Defense

ERIC Educational Resources Information Center

Crane, Earl Newell

2013-01-01

The research problem that inspired this effort is the challenge of managing the security of systems in large-scale heterogeneous networked environments. Human intervention is slow and limited: humans operate at much slower speeds than networked computer communications and there are few humans associated with each network. Enabling each node in the…

The South African Astronomical Observatory instrumentation software architecture and the SHOC instruments

NASA Astrophysics Data System (ADS)

van Gend, Carel; Lombaard, Briehan; Sickafoose, Amanda; Whittal, Hamish

2016-07-01

Until recently, software for instruments on the smaller telescopes at the South African Astronomical Observatory (SAAO) has not been designed for remote accessibility and frequently has not been developed using modern software best-practice. We describe a software architecture we have implemented for use with new and upgraded instruments at the SAAO. The architecture was designed to allow for multiple components and to be fast, reliable, remotely- operable, support different user interfaces, employ as much non-proprietary software as possible, and to take future-proofing into consideration. Individual component drivers exist as standalone processes, communicating over a network. A controller layer coordinates the various components, and allows a variety of user interfaces to be used. The Sutherland High-speed Optical Cameras (SHOC) instruments incorporate an Andor electron-multiplying CCD camera, a GPS unit for accurate timing and a pair of filter wheels. We have applied the new architecture to the SHOC instruments, with the camera driver developed using Andor's software development kit. We have used this to develop an innovative web-based user-interface to the instrument.

Processing speed in recurrent visual networks correlates with general intelligence.

PubMed

Jolij, Jacob; Huisman, Danielle; Scholte, Steven; Hamel, Ronald; Kemner, Chantal; Lamme, Victor A F

2007-01-08

Studies on the neural basis of general fluid intelligence strongly suggest that a smarter brain processes information faster. Different brain areas, however, are interconnected by both feedforward and feedback projections. Whether both types of connections or only one of the two types are faster in smarter brains remains unclear. Here we show, by measuring visual evoked potentials during a texture discrimination task, that general fluid intelligence shows a strong correlation with processing speed in recurrent visual networks, while there is no correlation with speed of feedforward connections. The hypothesis that a smarter brain runs faster may need to be refined: a smarter brain's feedback connections run faster.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

PubMed Central

Erdakov, Ivan Nikolaevich; Taha, Mohamed~Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-01-01

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth–Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness (Ra) prediction of one component in computer numerical control (CNC) turning over minimal machining time (Tm) and at prime machining costs (C). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra, Tm, and C, in relation to cutting speed, vc, depth of cut, ap, and feed per revolution, fr. For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values vc, ap, and fr. The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, Tm = 0.358 min/cm3, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed vc = 250 m/min, cutting depth ap = 1.0 mm, and feed per revolution fr = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness. PMID:29772670

Optimal Self-Tuning PID Controller Based on Low Power Consumption for a Server Fan Cooling System.

PubMed

Lee, Chengming; Chen, Rongshun

2015-05-20

Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server's fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption.

LAVIA--an evaluation of the potential safety benefits of the French intelligent speed adaptation project.

PubMed

Driscoll, R; Page, Y; Lassarre, S; Ehrlich, J

2007-01-01

This paper presents the potential safety benefits of the experimental French LAVIA Intelligent Speed Adaptation system, according to road network and system mode, based on observed driving speeds, distributions of crash severity and crash injury risk. Results are given for car frontal and side impacts that together, represent 80% of all serious and fatal injuries in France. Of the three system modes tested (advisory, driver select, mandatory), our results suggest that driver select would most significantly reduce serious injuries and death. We estimate this 100% utilization of cars equipped with this type of speed adaptation system would decrease injury rates by 6% to 16% over existing conditions depending on the type of crash (frontal or side) and road environment considered. Some limitations associated with the analysis are also identified. LAVIA is the acronym for Limiteur s'Adaptant à la VItesse Autorisée, a French Intelligent Speed Adaptation (ISA) project that was set up towards the end of 1999. At the time, 1998 French national road safety statistics recorded 8437 road related deaths, a figure which had shown virtually no positive evolution since 1994. Detailed analysis of the contributory factors involved in fatal road crashes highlighted the time-honoured crash and injury causation mechanisms - alcohol, speed and seatbelts. Of the three, excessive speed (over and above the posted speed limit) was a contributory factor in half of all fatal crashes Inappropriate behaviour such as excessive speeding can be dealt with either by legislative or driver-incentive programmes. The first of these two solutions involves the introduction of new legislation and/or the enforcement of existing laws. This is the domain of Public Authorities and will not be discussed in detail here. Alternatively, incentive schemes can involve the implementation of speed related driver assistance systems, categorised according to their voluntary or mandatory character and the degree of autonomy proposed to or imposed on the driver. The LAVIA project set out to address several possible combinations of these two factors. The generic term Intelligent Speed Adaptation (ISA) encompasses a wide range of different technologies aimed at improving road safety by reducing traffic speed and homogenising traffic flow, within the limit of posted speed limits. "Fixed speed limit" systems inform the vehicle of the posted speed limit whereas "variable speed limit" systems take into account certain locations on the road network where a speed below the posted limit is desirable, such as sharp curves, pedestrian crossings or crash black spots. Taken one step further, speed limit systems may also take into account weather and traffic flow conditions. These systems are known as "dynamic speed limit" systems and benefit from real time updates for a specific location. The different ISA systems are generally characterised by the degree of freedom of choice given to the driver in moderating his or her speed. Speed limit technologies may be advisory (informing drivers of the current speed limit and speed limit changes), voluntary (allowing the driver to decide whether or not to implement speed limitation) or mandatory (imposing the current speed limit). The information supplied may be provided by way of the road infrastructure (and associated equipment), may be acquired autonomously by the vehicle or may be based on an interaction between the infrastructure and the vehicle. Even the most basic of these systems should be considered as a very useful driver aid, helping the driver to stay within the posted speed limit, avoiding "unnecessary" speeding fines through inattention, modelling driver behaviour through the long term reduction of speeds and reducing driver workload by limiting visual speedometer controls. Vehicle-based ISA systems should not be confused with internal systems. These latter systems rely upon the driver entering the desired travel speed, which is then maintained by cruise control or set as a maximum value by automatic speed regulators. Although these systems will not be discussed in detail here, it should be noted that the engine management technologies that they employ are a vital component of ISA systems.

Geometrical and Kinematic Parameters of the Jet of the Blazar S5 0716+71 in a Helical-Jet Model

NASA Astrophysics Data System (ADS)

Butuzova, M. S.

2018-02-01

Periodic variations of the position angle of the inner jet of the blazar S5 0716+71 suggest a helical structure for the jet. The geometrical parameters of a model helical jet are determined. It is shown that, when the trajectories of the jet components are non-ballistic, the angle between their velocity vectors and the line of sight lies in a broader interval than is the case for ballistic motions of the components, in agreement with available estimates. The contradictory results for the apparent speeds of components in the inner and outer jet at epochs 2004 and 2008-2010 can be explained in such a model. The ratio of the apparent speeds in the inner and outer jet are used to derive a lower limit for the physical speed of the components ( β > 0.999) and to determine the pitch angle of the helical jet ( p = 5.5°). The derived parameters can give rise to the conditions required to observe high speeds (right to 37 c) for individual jet components.

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods

NASA Astrophysics Data System (ADS)

Kong, Changduk; Lim, Semyeong

2011-12-01

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang

2016-08-01

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments

NASA Technical Reports Server (NTRS)

Leftwich, Matt; Hull, Tony; Leary, Michael; Leftwich, Marcus

2013-01-01

Future NASA destinations will be challenging to get to, have extreme environmental conditions, and may present difficulty in retrieving a spacecraft or its data. Space Photonics is developing a radiation-tolerant (rad-tolerant), high-speed, multi-channel fiber-optic transceiver, associated reconfigurable intelligent node communications architecture, and supporting hardware for intravehicular and ground-based optical networking applications. Data rates approaching 3.2 Gbps per channel will be achieved.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

PubMed Central

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms. PMID:22408487

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

PubMed

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Neural network based control of Doubly Fed Induction Generator in wind power generation

NASA Astrophysics Data System (ADS)

Barbade, Swati A.; Kasliwal, Prabha

2012-07-01

To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.

Design and performance evaluation of an OpenFlow-based control plane for software-defined elastic optical networks with direct-detection optical OFDM (DDO-OFDM) transmission.

PubMed

Liu, Lei; Peng, Wei-Ren; Casellas, Ramon; Tsuritani, Takehiro; Morita, Itsuro; Martínez, Ricardo; Muñoz, Raül; Yoo, S J B

2014-01-13

Optical Orthogonal Frequency Division Multiplexing (O-OFDM), which transmits high speed optical signals using multiple spectrally overlapped lower-speed subcarriers, is a promising candidate for supporting future elastic optical networks. In contrast to previous works which focus on Coherent Optical OFDM (CO-OFDM), in this paper, we consider the direct-detection optical OFDM (DDO-OFDM) as the transport technique, which leads to simpler hardware and software realizations, potentially offering a low-cost solution for elastic optical networks, especially in metro networks, and short or medium distance core networks. Based on this network scenario, we design and deploy a software-defined networking (SDN) control plane enabled by extending OpenFlow, detailing the network architecture, the routing and spectrum assignment algorithm, OpenFlow protocol extensions and the experimental validation. To the best of our knowledge, it is the first time that an OpenFlow-based control plane is reported and its performance is quantitatively measured in an elastic optical network with DDO-OFDM transmission.

Research and development of a NYNEX switched multi-megabit data service prototype system

NASA Astrophysics Data System (ADS)

Maman, K. H.; Haines, Robert; Chatterjee, Samir

1991-02-01

Switched Multi-megabit Data Service (SMDS) is a proposed high-speed packet-switched service which will support broadband applications such as Local Area Network (LAN) interconnections across a metropolitan area and beyond. This service is designed to take advantage of evolving Metropolitan Area Network (MAN) standards and technology which will provide customers with 45-mbps and 1 . 5-mbps access to high-speed public data communications networks. This paper will briefly discuss SMDS and review its architecture including the Subscriber Network Interface (SNI) and the SMDS Interface Protocol (SIP). It will review the fundamental features of SMDS such as address screening addressing scheme and access classes. Then it will describe the SMDS prototype system developed in-house by NYNEX Science Technology.

Cascade exciton-pumping engines with manipulated speed and efficiency in light-harvesting porous π-network films

PubMed Central

Gu, Cheng; Huang, Ning; Xu, Fei; Gao, Jia; Jiang, Donglin

2015-01-01

Light-harvesting antennae are the machinery for exciton pumping in natural photosynthesis, whereas cascade energy transfer through chlorophyll is key to long-distance, efficient energy transduction. Numerous artificial antennae have been developed. However, they are limited in their cascade energy-transfer abilities because of a lack of control over complex chromophore aggregation processes, which has impeded their advancement. Here we report a viable approach for addressing this issue by using a light-harvesting porous polymer film in which a three-dimensional π-network serves as the antenna and micropores segregate multiple dyes to prevent aggregation. Cascade energy-transfer engines are integrated into the films; the rate and efficiency of the energy-funneling engines are precisely manipulated by tailoring the dye components and contents. The nanofilms allow accurate and versatile luminescence engineering, resulting in the production of thirty emission hues, including blue, green, red and white. This advance may open new pathways for realising photosynthesis and photoenergy conversion. PMID:25746459

Investigating molecular crowding within nuclear pores using polarization-PALM

PubMed Central

Fu, Guo; Tu, Li-Chun; Zilman, Anton

2017-01-01

The key component of the nuclear pore complex (NPC) controlling permeability, selectivity, and the speed of nucleocytoplasmic transport is an assembly of natively unfolded polypeptides, which contain phenylalanine-glycine (FG) binding sites for nuclear transport receptors. The architecture and dynamics of the FG-network have been refractory to characterization due to the paucity of experimental methods able to probe the mobility and density of the FG-polypeptides and embedded macromolecules within intact NPCs. Combining fluorescence polarization, super-resolution microscopy, and mathematical analyses, we examined the rotational mobility of fluorescent probes at various locations within the FG-network under different conditions. We demonstrate that polarization PALM (p-PALM) provides a rich source of information about low rotational mobilities that are inaccessible with bulk fluorescence anisotropy approaches, and anticipate that p-PALM is well-suited to explore numerous crowded cellular environments. In total, our findings indicate that the NPC’s internal organization consists of multiple dynamic environments with different local properties. PMID:28949296

Graphical processors for HEP trigger systems

NASA Astrophysics Data System (ADS)

Ammendola, R.; Biagioni, A.; Chiozzi, S.; Cotta Ramusino, A.; Di Lorenzo, S.; Fantechi, R.; Fiorini, M.; Frezza, O.; Lamanna, G.; Lo Cicero, F.; Lonardo, A.; Martinelli, M.; Neri, I.; Paolucci, P. S.; Pastorelli, E.; Piandani, R.; Pontisso, L.; Rossetti, D.; Simula, F.; Sozzi, M.; Vicini, P.

2017-02-01

General-purpose computing on GPUs is emerging as a new paradigm in several fields of science, although so far applications have been tailored to employ GPUs as accelerators in offline computations. With the steady decrease of GPU latencies and the increase in link and memory throughputs, time is ripe for real-time applications using GPUs in high-energy physics data acquisition and trigger systems. We will discuss the use of online parallel computing on GPUs for synchronous low level trigger systems, focusing on tests performed on the trigger of the CERN NA62 experiment. Latencies of all components need analysing, networking being the most critical. To keep it under control, we envisioned NaNet, an FPGA-based PCIe Network Interface Card (NIC) enabling GPUDirect connection. Moreover, we discuss how specific trigger algorithms can be parallelised and thus benefit from a GPU implementation, in terms of increased execution speed. Such improvements are particularly relevant for the foreseen LHC luminosity upgrade where highly selective algorithms will be crucial to maintain sustainable trigger rates with very high pileup.

Application of the ANNA neural network chip to high-speed character recognition.

PubMed

Sackinger, E; Boser, B E; Bromley, J; Lecun, Y; Jackel, L D

1992-01-01

A neural network with 136000 connections for recognition of handwritten digits has been implemented using a mixed analog/digital neural network chip. The neural network chip is capable of processing 1000 characters/s. The recognition system has essentially the same rate (5%) as a simulation of the network with 32-b floating-point precision.

Weaves as an Interconnection Fabric for ASIM's and Nanosatellites

NASA Technical Reports Server (NTRS)

Gorlick, Michael M.

1995-01-01

Many of the micromachines under consideration require computer support, indeed, one of the appeals of this technology is the ability to intermix mechanical, optical, analog, and digital devices on the same substrate. The amount of computer power is rarely an issue, the sticking point is the complexity of the software required to make effective use of these devices. Micromachines are the nano-technologist's equivalent of 'golden screws'. In other words, they will be piece parts in larger assemblages. For example, a nano-satellite may be composed of stacked silicon wafers where each wafer contains hundreds to thousands of micromachines, digital controllers, general purpose computers, memories, and high-speed bus interconnects. Comparatively few of these devices will be custom designed, most will be stock parts selected from libraries and catalogs. The novelty will lie in the interconnections. For example, a digital accelerometer may be a component part in an adaptive suspension, a monitoring element embedded in the wrapper of a package, or a portion of the smart skin of a launch vehicle. In each case, this device must inter-operate with other devices and probes for the purposes of command, control, and communication. We propose a software technology called 'weaves' that will permit large collections of micromachines and their attendant computers to freely intercommunicate while preserving modularity, transparency, and flexibility. Weaves are composed of networks of communicating software components. The network, and the components comprising it, may be changed even while the software, and the devices it controls, are executing. This unusual degree of software plasticity permits micromachines to dynamically adapt the software to changing conditions and allows system engineers to rapidly and inexpensively develop special purpose software by assembling stock software components in custom configurations.

Potential assessment of a neural network model with PCA/RBF approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong.

PubMed

Lu, Wei-Zhen; Wang, Wen-Jian; Wang, Xie-Kang; Yan, Sui-Hang; Lam, Joseph C

2004-09-01

The forecasting of air pollutant trends has received much attention in recent years. It is an important and popular topic in environmental science, as concerns have been raised about the health impacts caused by unacceptable ambient air pollutant levels. Of greatest concern are metropolitan cities like Hong Kong. In Hong Kong, respirable suspended particulates (RSP), nitrogen oxides (NOx), and nitrogen dioxide (NO2) are major air pollutants due to the dominant usage of diesel fuel by commercial vehicles and buses. Hence, the study of the influence and the trends relating to these pollutants is extremely significant to the public health and the image of the city. The use of neural network techniques to predict trends relating to air pollutants is regarded as a reliable and cost-effective method for the task of prediction. The works reported here involve developing an improved neural network model that combines both the principal component analysis technique and the radial basis function network and forecasts pollutant tendencies based on a recorded database. Compared with general neural network models, the proposed model features a more simple network architecture, a faster training speed, and a more satisfactory prediction performance. The improved model was evaluated with hourly time series of RSP, NOx and NO2 concentrations monitored at the Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000 and proved to be effective. The model developed is a potential tool for forecasting air quality parameters and is superior to traditional neural network methods.

Effect of Wind Speed on Aerosol Optical Depth over Remote Oceans, Based on Data from the Maritime Aerosol Network

NASA Technical Reports Server (NTRS)

Smirnov, A.; Sayer, A. M.; Holben, B. N.; Hsu, N. C.; Sakerin, S. M.; Macke, A.; Nelson, N. B.; Courcoux, Y.; Smyth, T. J.; Croot, P.;

A hybrid wavelet transform based short-term wind speed forecasting approach.

PubMed

Wang, Jujie

2014-01-01

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network

NASA Astrophysics Data System (ADS)

Smirnov, A.; Sayer, A. M.; Holben, B. N.; Hsu, N. C.; Sakerin, S. M.; Macke, A.; Nelson, N. B.; Courcoux, Y.; Smyth, T. J.; Croot, P.; Quinn, P. K.; Sciare, J.; Gulev, S. K.; Piketh, S.; Losno, R.; Kinne, S.; Radionov, V. F.

2011-12-01

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (∼0.004-0.005), even for strong winds over 10 m s-1. The relationships show significant scatter (correlation coefficients typically in the range 0.3-0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.

Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network

NASA Astrophysics Data System (ADS)

Smirnov, A.; Sayer, A. M.; Holben, B. N.; Hsu, N. C.; Sakerin, S. M.; Macke, A.; Nelson, N. B.; Courcoux, Y.; Smyth, T. J.; Croot, P.; Quinn, P. K.; Sciare, J.; Gulev, S. K.; Piketh, S.; Losno, R.; Kinne, S.; Radionov, V. F.

2012-02-01

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (~0.004-0.005), even for strong winds over 10 m s-1. The relationships show significant scatter (correlation coefficients typically in the range 0.3-0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.

A Hybrid Wavelet Transform Based Short-Term Wind Speed Forecasting Approach

PubMed Central

Wang, Jujie

2014-01-01

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy. PMID:25136699

GUI Type Fault Diagnostic Program for a Turboshaft Engine Using Fuzzy and Neural Networks

NASA Astrophysics Data System (ADS)

Kong, Changduk; Koo, Youngju

2011-04-01

The helicopter to be operated in a severe flight environmental condition must have a very reliable propulsion system. On-line condition monitoring and fault detection of the engine can promote reliability and availability of the helicopter propulsion system. A hybrid health monitoring program using Fuzzy Logic and Neural Network Algorithms can be proposed. In this hybrid method, the Fuzzy Logic identifies easily the faulted components from engine measuring parameter changes, and the Neural Networks can quantify accurately its identified faults. In order to use effectively the fault diagnostic system, a GUI (Graphical User Interface) type program is newly proposed. This program is composed of the real time monitoring part, the engine condition monitoring part and the fault diagnostic part. The real time monitoring part can display measuring parameters of the study turboshaft engine such as power turbine inlet temperature, exhaust gas temperature, fuel flow, torque and gas generator speed. The engine condition monitoring part can evaluate the engine condition through comparison between monitoring performance parameters the base performance parameters analyzed by the base performance analysis program using look-up tables. The fault diagnostic part can identify and quantify the single faults the multiple faults from the monitoring parameters using hybrid method.

Local-Area-Network Simulator

NASA Technical Reports Server (NTRS)

Gibson, Jim; Jordan, Joe; Grant, Terry

1990-01-01

Local Area Network Extensible Simulator (LANES) computer program provides method for simulating performance of high-speed local-area-network (LAN) technology. Developed as design and analysis software tool for networking computers on board proposed Space Station. Load, network, link, and physical layers of layered network architecture all modeled. Mathematically models according to different lower-layer protocols: Fiber Distributed Data Interface (FDDI) and Star*Bus. Written in FORTRAN 77.

Cylinder pressure reconstruction based on complex radial basis function networks from vibration and speed signals

NASA Astrophysics Data System (ADS)

Johnsson, Roger

2006-11-01

Methods to measure and monitor the cylinder pressure in internal combustion engines can contribute to reduced fuel consumption, noise and exhaust emissions. As direct measurements of the cylinder pressure are expensive and not suitable for measurements in vehicles on the road indirect methods which measure cylinder pressure have great potential value. In this paper, a non-linear model based on complex radial basis function (RBF) networks is proposed for the reconstruction of in-cylinder pressure pulse waveforms. Input to the network is the Fourier transforms of both engine structure vibration and crankshaft speed fluctuation. The primary reason for the use of Fourier transforms is that different frequency regions of the signals are used for the reconstruction process. This approach also makes it easier to reduce the amount of information that is used as input to the RBF network. The complex RBF network was applied to measurements from a 6-cylinder ethanol powered diesel engine over a wide range of running conditions. Prediction accuracy was validated by comparing a number of parameters between the measured and predicted cylinder pressure waveform such as maximum pressure, maximum rate of pressure rise and indicated mean effective pressure. The performance of the network was also evaluated for a number of untrained running conditions that differ both in speed and load from the trained ones. The results for the validation set were comparable to the trained conditions.

Distributing stand inventory data and maps over a wide area network

Treesearch

Thomas E. Burk

2000-01-01

High-speed networks connecting multiple levels of management are becoming commonplace among forest resources organizations. Such networks can be used to deliver timely spatial and aspatial data relevant to the management of stands to field personnel. A network infrastructure allows maintenance of cost-effective, centralized databases with the potential for updating by...

Mississippi Library Commission Data Network Specifications.

ERIC Educational Resources Information Center

Evans Associates, Thiensville, WI.

This document provides a detailed design for the data portion of the Mississippi Library Commission (MLC) public library network. The data network is based on Frame Relay technology, and would provide more functionality at a higher speed than a previously considered dial-in network could. The document is divided into 16 sections: (1) Introduction;…

Location accuracy evaluation of lightning location systems using natural lightning flashes recorded by a network of high-speed cameras

NASA Astrophysics Data System (ADS)

Alves, J.; Saraiva, A. C. V.; Campos, L. Z. D. S.; Pinto, O., Jr.; Antunes, L.

2014-12-01

This work presents a method for the evaluation of location accuracy of all Lightning Location System (LLS) in operation in southeastern Brazil, using natural cloud-to-ground (CG) lightning flashes. This can be done through a multiple high-speed cameras network (RAMMER network) installed in the Paraiba Valley region - SP - Brazil. The RAMMER network (Automated Multi-camera Network for Monitoring and Study of Lightning) is composed by four high-speed cameras operating at 2,500 frames per second. Three stationary black-and-white (B&W) cameras were situated in the cities of São José dos Campos and Caçapava. A fourth color camera was mobile (installed in a car), but operated in a fixed location during the observation period, within the city of São José dos Campos. The average distance among cameras was 13 kilometers. Each RAMMER sensor position was determined so that the network can observe the same lightning flash from different angles and all recorded videos were GPS (Global Position System) time stamped, allowing comparisons of events between cameras and the LLS. The RAMMER sensor is basically composed by a computer, a Phantom high-speed camera version 9.1 and a GPS unit. The lightning cases analyzed in the present work were observed by at least two cameras, their position was visually triangulated and the results compared with BrasilDAT network, during the summer seasons of 2011/2012 and 2012/2013. The visual triangulation method is presented in details. The calibration procedure showed an accuracy of 9 meters between the accurate GPS position of the object triangulated and the result from the visual triangulation method. Lightning return stroke positions, estimated with the visual triangulation method, were compared with LLS locations. Differences between solutions were not greater than 1.8 km.

Data Handling and Communication

NASA Astrophysics Data System (ADS)

Hemmer, FréDéRic Giorgio Innocenti, Pier

The following sections are included: * Introduction * Computing Clusters and Data Storage: The New Factory and Warehouse * Local Area Networks: Organizing Interconnection * High-Speed Worldwide Networking: Accelerating Protocols * Detector Simulation: Events Before the Event * Data Analysis and Programming Environment: Distilling Information * World Wide Web: Global Networking * References

Instrument for analysis of electric motors based on slip-poles component

DOEpatents

Haynes, Howard D.; Ayers, Curtis W.; Casada, Donald A.

1996-01-01

A new instrument for monitoring the condition and speed of an operating electric motor from a remote location. The slip-poles component is derived from a motor current signal. The magnitude of the slip-poles component provides the basis for a motor condition monitor, while the frequency of the slip-poles component provides the basis for a motor speed monitor. The result is a simple-to-understand motor health monitor in an easy-to-use package. Straightforward indications of motor speed, motor running current, motor condition (e.g., rotor bar condition) and synthesized motor sound (audible indication of motor condition) are provided. With the device, a relatively untrained worker can diagnose electric motors in the field without requiring the presence of a trained engineer or technician.

Instrument for analysis of electric motors based on slip-poles component

DOEpatents

Haynes, H.D.; Ayers, C.W.; Casada, D.A.

1996-11-26

A new instrument is described for monitoring the condition and speed of an operating electric motor from a remote location. The slip-poles component is derived from a motor current signal. The magnitude of the slip-poles component provides the basis for a motor condition monitor, while the frequency of the slip-poles component provides the basis for a motor speed monitor. The result is a simple-to-understand motor health monitor in an easy-to-use package. Straightforward indications of motor speed, motor running current, motor condition (e.g., rotor bar condition) and synthesized motor sound (audible indication of motor condition) are provided. With the device, a relatively untrained worker can diagnose electric motors in the field without requiring the presence of a trained engineer or technician. 4 figs.

Deep learning with coherent nanophotonic circuits

NASA Astrophysics Data System (ADS)

Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin

2017-07-01

Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.

Development of programmable artificial neural networks

NASA Technical Reports Server (NTRS)

Meade, Andrew J.

1993-01-01

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

System, apparatus and methods to implement high-speed network analyzers

DOEpatents

Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

2015-11-10

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

T-cell movement on the reticular network.

PubMed

Donovan, Graham M; Lythe, Grant

2012-02-21

The idea that the apparently random motion of T cells in lymph nodes is a result of movement on a reticular network (RN) has received support from dynamic imaging experiments and theoretical studies. We present a mathematical representation of the RN consisting of edges connecting vertices that are randomly distributed in three-dimensional space, and models of lymphocyte movement on such networks including constant speed motion along edges and Brownian motion, not in three-dimensions, but only along edges. The simplest model, in which a cell moves with a constant speed along edges, is consistent with mean-squared displacement proportional to time over intervals long enough to include several changes of direction. A non-random distribution of turning angles is one consequence of motion on a preformed network. Confining cell movement to a network does not, in itself, increase the frequency of cell-cell encounters. Copyright © 2011 Elsevier Ltd. All rights reserved.

Brain networks governing the golf swing in professional golfers.

PubMed

Kim, Jin Hyun; Han, Joung Kyue; Kim, Bung-Nyun; Han, Doug Hyun

2015-01-01

Golf, as with most complex motor skills, requires multiple different brain functions, including attention, motor planning, coordination, calculation of timing, and emotional control. In this study we assessed the correlation between swing components and brain connectivity from the cerebellum to the cerebrum. Ten female golf players and 10 age-matched female controls were recruited. In order to determine swing consistency among participants, the standard deviation (SD) of the mean swing speed time and the SD of the mean swing angle were assessed over 30 swings. Functional brain connectivity was assessed by resting state functional MRI. Pro-golfers showed greater positive left cerebellum connectivity to the occipital lobe, temporal lobe, parietal lobe and both frontal lobes compared to controls. The SD of play scores was positively correlated with the SD of the impact angle. Constant swing speed and back swing angle in professional golfers were associated with functional connectivity (FC) between the cerebellum and parietal and frontal lobes. In addition, the constant impact angle in professional golfers was associated with improved golf scores and additional FC of the thalamus.

Mapping near-surface air temperature, pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution

NASA Astrophysics Data System (ADS)

Li, Tao; Zheng, Xiaogu; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Zhang, Shupeng; Wu, Guocan; Wang, Zhonglei; Huang, Chengcheng; Shen, Yan; Liao, Rongwei

2014-09-01

As part of a joint effort to construct an atmospheric forcing dataset for mainland China with high spatiotemporal resolution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km×1 km. The approach comprises two steps: (1) fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; (2) apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over mainland China. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.

Electron acoustic-Langmuir solitons in a two-component electron plasma

NASA Astrophysics Data System (ADS)

McKenzie, J. F.

2003-04-01

We investigate the conditions under which ‘high-frequency’ electron acoustic Langmuir solitons can be constructed in a plasma consisting of protons and two electron populations: one ‘cold’ and the other ‘hot’. Conservation of total momentum can be cast as a structure equation either for the ‘cold’ or ‘hot’ electron flow speed in a stationary wave using the Bernoulli energy equations for each species. The linearized version of the governing equations gives the dispersion equation for the stationary waves of the system, from which follows the necessary but not sufficient conditions for the existence of soliton structures; namely that the wave speed must be less than the acoustic speed of the ‘hot’ electron component and greater than the low-frequency compound acoustic speed of the two electron populations. In this wave speed regime linear waves are ‘evanescent’, giving rise to the exponential growth or decay, which readily can give rise to non-linear effects that may balance dispersion and allow soliton formation. In general the ‘hot’ component must be more abundant than the ‘cold’ one and the wave is characterized by a compression of the ‘cold’ component and an expansion in the ‘hot’ component necessitating a potential dip. Both components are driven towards their sonic points; the ‘cold’ from above and the ‘hot’ from below. It is this transonic feature which limits the amplitude of the soliton. If the ‘hot’ component is not sufficiently abundant the window for soliton formation shrinks to a narrow speed regime which is quasi-transonic relative to the ‘hot’ electron acoustic speed, and it is shown that smooth solitons cannot be constructed. In the special case of a very cold electron population (i.e. ‘highly supersonic’) and the other population being very hot (i.e. ‘highly subsonic’) with adiabatic index 2, the structure equation simplifies and can be integrated in terms of elementary transcendental functions that provide the fully non-linear counterpart to the weakly non-linear sech(2) -type solitons. In this case the limiting soliton is comprised of an infinite compression in the cold component, a weak rarefaction in the ‘hot’ electrons and a modest potential dip.

Design and flight test results of high speed optical bidirectional link between stratospheric platforms for aerospace applications

NASA Astrophysics Data System (ADS)

Briatore, S.; Akhtyamov, R.; Golkar, A.

2017-08-01

As small and nanosatellites become increasingly relevant in the aerospace industry1, 2, the need of efficient, lightweight and cost-effective networking solutions drives the need for the development of lightweight and low cost networking and communication terminals. In this paper we propose the design and prototype results of a hybrid optical and radio communication architecture developed to fit the coarse pointing capabilities of nanosatellites, tested through a proxy flight experiment on stratospheric balloons. This system takes advantage of the higher data-rate offered by optical communication channels while relying on the more mature and stable technology of conventional radio systems for link negotiation and low-speed data exchange. Such architecture allows the user to overcome the licensing requirements and scarce availability of high data-rate radio frequency channels in the commonly used bands. Outlined are the architecture, development and test of the mentioned terminal, with focus on the communication part and supporting technologies, including the navigation algorithm, the developed fail-safe approach, and the evolution of the pointing system continuing previous work done in 3. The system has been built with commercial-off-the-shelf components and demonstrated on a stratospheric balloon launch campaign. The paper outlines the results of an in-flight demonstration, where the two platforms successfully established an optical link at stratospheric altitudes. The results are then analyzed and contextualized in plans of future work for nanosatellite implementations.

Seismic Noise Characterization in the Northern Mississippi Embayment

NASA Astrophysics Data System (ADS)

Wiley, S.; Deshon, H. R.; Boyd, O. S.

2009-12-01

We present a study of seismic noise sources present within the northern Mississippi embayment near the New Madrid Seismic Zone (NMSZ). The northern embayment contains up to 1 km of unconsolidated coastal plain sediments overlying bedrock, making it an inherently noisy environment for seismic stations. The area is known to display high levels of cultural noise caused by agricultural activity, passing cars, trains, etc. We characterize continuous broadband seismic noise data recorded for the months of March through June 2009 at six stations operated by the Cooperative New Madrid Seismic Network. We looked at a single horizontal component of data during nighttime hours, defined as 6:15PM to 5:45AM Central Standard Time, which we determined to be the lowest amplitude period of noise for the region. Hourly median amplitudes were compared to daily average wind speeds downloaded from the National Oceanic and Atmospheric Administration. We find a correlation between time periods of increased noise and days with high wind speeds, suggesting that wind is likely a prevalent source of seismic noise in the area. The effects of wind on seismic recordings may result from wind induced tree root movement which causes ground motion to be recorded at the vaults located ~3m below ground. Automated studies utilizing the local network or the EarthScope Transportable Array, scheduled to arrive in the area in 2010-11, should expect to encounter wind induced noise fluctuations and must account for this in their analysis.

A New Measure for Neural Compensation Is Positively Correlated With Working Memory and Gait Speed.

PubMed

Ji, Lanxin; Pearlson, Godfrey D; Hawkins, Keith A; Steffens, David C; Guo, Hua; Wang, Lihong

2018-01-01

Neuroimaging studies suggest that older adults may compensate for declines in brain function and cognition through reorganization of neural resources. A limitation of prior research is reliance on between-group comparisons of neural activation (e.g., younger vs. older), which cannot be used to assess compensatory ability quantitatively. It is also unclear about the relationship between compensatory ability with cognitive function or how other factors such as physical exercise modulates compensatory ability. Here, we proposed a data-driven method to semi-quantitatively measure neural compensation under a challenging cognitive task, and we then explored connections between neural compensation to cognitive engagement and cognitive reserve (CR). Functional and structural magnetic resonance imaging scans were acquired for 26 healthy older adults during a face-name memory task. Spatial independent component analysis (ICA) identified visual, attentional and left executive as core networks. Results show that the smaller the volumes of the gray matter (GM) structures within core networks, the more networks were needed to conduct the task ( r = -0.408, p = 0.035). Therefore, the number of task-activated networks controlling for the GM volume within core networks was defined as a measure of neural compensatory ability. We found that compensatory ability correlated with working memory performance ( r = 0.528, p = 0.035). Among subjects with good memory task performance, those with higher CR used fewer networks than subjects with lower CR. Among poor-performance subjects, those using more networks had higher CR. Our results indicated that using a high cognitive-demanding task to measure the number of activated neural networks could be a useful and sensitive measure of neural compensation in older adults.

Portable emergency telemedicine system over wireless broadband and 3G networks.

PubMed

Hong, SungHye; Kim, SangYong; Kim, JungChae; Lim, DongKyu; Jung, SeokMyung; Kim, DongKeun; Yoo, Sun K

2009-01-01

The telemedicine system aims at monitoring patients remotely without limit in time and space. However the existing telemedicine systems exchange medical information simply in a specified location. Due to increasing speed in processing data and expanding bandwidth of wireless networks, it is possible to perform telemedicine services on personal digital assistants (PDA). In this paper, a telemedicine system on PDA was developed using wideband mobile networks such as Wi-Fi, HSDPA, and WiBro for high speed bandwidths. This system enables to utilize and exchange variety and reliable patient information of video, biosignals, chatting messages, and triage data. By measuring bandwidths of individual data of the system over wireless networks, and evaluating the performance of this system using PDA, we demonstrated the feasibility of the designed portable emergency telemedicine system.

A network analysis of the Chinese medicine Lianhua-Qingwen formula to identify its main effective components.

PubMed

Wang, Chun-Hua; Zhong, Yi; Zhang, Yan; Liu, Jin-Ping; Wang, Yue-Fei; Jia, Wei-Na; Wang, Guo-Cai; Li, Zheng; Zhu, Yan; Gao, Xiu-Mei

2016-02-01

Chinese medicine is known to treat complex diseases with multiple components and multiple targets. However, the main effective components and their related key targets and functions remain to be identified. Herein, a network analysis method was developed to identify the main effective components and key targets of a Chinese medicine, Lianhua-Qingwen Formula (LQF). The LQF is commonly used for the prevention and treatment of viral influenza in China. It is composed of 11 herbs, gypsum and menthol with 61 compounds being identified in our previous work. In this paper, these 61 candidate compounds were used to find their related targets and construct the predicted-target (PT) network. An influenza-related protein-protein interaction (PPI) network was constructed and integrated with the PT network. Then the compound-effective target (CET) network and compound-ineffective target network (CIT) were extracted, respectively. A novel approach was developed to identify effective components by comparing CET and CIT networks. As a result, 15 main effective components were identified along with 61 corresponding targets. 7 of these main effective components were further experimentally validated to have antivirus efficacy in vitro. The main effective component-target (MECT) network was further constructed with main effective components and their key targets. Gene Ontology (GO) analysis of the MECT network predicted key functions such as NO production being modulated by the LQF. Interestingly, five effective components were experimentally tested and exhibited inhibitory effects on NO production in the LPS induced RAW 264.7 cell. In summary, we have developed a novel approach to identify the main effective components in a Chinese medicine LQF and experimentally validated some of the predictions.

P- and S-Wave Speeds of the Very Upper Crust Estimated by a New Technique Based Upon Body-Wave Polarization

NASA Astrophysics Data System (ADS)

Park, S.; Ishii, M.

2017-12-01

Various seismic imaging methods have been developed, such as traveltime, waveform, and noise tomography, improving our knowledge of the subsurface structure and evolution. Near-surface structure, in particular, is crucial in understanding earthquake and volcano hazards. Seismic speed is directly related to the level of ground shaking, and monitoring its temporal change is valuable in volcanic hazard assessment. Here, we introduce a novel technique to constrain seismic wave speed of the very upper crust based upon the polarization measurements of teleseismic body-wave arrivals. The technique relates the orientation of recorded body waves to the wave speed immediately beneath a seismic instrument. We develop a counter-intuitive relationship that the P-wave polarization direction is only sensitive to subsurface shear wave speed but not to compressional wave speed, while the S-wave polarization direction is sensitive to both wave speeds. This approach is applied to the High-Sensitivity Seismograph Network in Japan, where the results are benchmarked against the borehole well data available at most stations. There is a good agreement between polarization-based estimates and the well measurements at as shallow as 100 m, confirming the efficacy of the new method in resolving the shallow structure. The lateral variation of wave speeds shows that sedimentary basins and mountainous regions are characterized by low and high wave speeds, respectively. It also correlates with volcano locations and geological units of different ages. Moreover, the analysis is expanded into 3D by examining the frequency dependence, where some preliminary results using broadband data are presented. These 2D and 3D wave speed estimates can be used to identify zones of high seismic risk by comparison with population distribution. This technique requires minimal computation resources and can be applied to any single three-component seismograph. It opens a new path to a reliable, non-invasive, and inexpensive earthquake hazard assessment in any environment where a drilling or a field experiment using vibro-trucks or explosives is not a practical option for measuring the near-surface seismic wave speeds. It can also provide means of monitoring changes that occur within the very upper crust such as from volcanic or hydrological phenomena.

Coordinated platooning with multiple speeds

DOE PAGES

Luo, Fengqiao; Larson, Jeffrey; Munson, Todd

2018-03-22

In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on themore » time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.« less

Coordinated platooning with multiple speeds

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

Luo, Fengqiao; Larson, Jeffrey; Munson, Todd

In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on themore » time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.« less

Design study of wind turbines 50 kW to 3000 kW for electric utility applications. Volume 2: Analysis and design

NASA Technical Reports Server (NTRS)

1976-01-01

All possible overall system configurations, operating modes, and subsystem concepts for a wind turbine configuration for cost effective generation of electrical power were evaluated for both technical feasibility and compatibility with utility networks, as well as for economic attractiveness. A design optimization computer code was developed to determine the cost sensitivity of the various design features, and thus establish the configuration and design conditions that would minimize the generated energy costs. The preliminary designs of both a 500 kW unit and a 1500 kW unit operating in a 12 mph and 18 mph median wind speed respectively, were developed. The various design features and components evaluated are described, and the rationale employed to select the final design configuration is given. All pertinent technical performance data and component cost data is included. The costs of all major subassemblies are estimated and the resultant energy costs for both the 500 kW and 1500 kW units are calculated.

Low power pulsed MPD thruster system analysis and applications

NASA Astrophysics Data System (ADS)

Myers, Roger M.; Domonkos, Matthew; Gilland, James H.

1993-06-01

Pulsed MPD thruster systems were analyzed for application to solar-electric orbit transfer vehicles at power levels ranging from 10 to 40 kW. Potential system level benefits of pulsed propulsion technology include ease of power scaling without thruster performance changes, improved transportability from low power flight experiments to operational systems, and reduced ground qualification costs. Required pulsed propulsion system components include a pulsed applied-field MPD thruster, a pulse-forming network, a charge control unit, a cathode heater supply, and high speed valves. Mass estimates were obtained for each propulsion subsystem and spacecraft component. Results indicate that for payloads of 1000 and 2000 kg, pulsed MPD thrusters can reduce launch mass by between 1000 and 2500 kg relative to hydrogen arcjets, reducing launch vehicle class and launch cost. While the achievable mass savings depends on the trip time allowed for the mission, cases are shown in which the launch vehicle required for a mission is decreased from an Atlas IIAS to an Atlas I or Delta 7920.

Low cost Ku-band earth terminals for voice/data/facsimile

NASA Technical Reports Server (NTRS)

Kelley, R. L.

1977-01-01

A Ku-band satellite earth terminal capable of providing two way voice/facsimile teleconferencing, 128 Kbps data, telephone, and high-speed imagery services is proposed. Optimized terminal cost and configuration are presented as a function of FDMA and TDMA approaches to multiple access. The entire terminal from the antenna to microphones, speakers and facsimile equipment is considered. Component cost versus performance has been projected as a function of size of the procurement and predicted hardware innovations and production techniques through 1985. The lowest cost combinations of components has been determined in a computer optimization algorithm. The system requirements including terminal EIRP and G/T, satellite size, power per spacecraft transponder, satellite antenna characteristics, and link propagation outage were selected using a computerized system cost/performance optimization algorithm. System cost and terminal cost and performance requirements are presented as a function of the size of a nationwide U.S. network. Service costs are compared with typical conference travel costs to show the viability of the proposed terminal.

A High Speed Mobile Courier Data Access System That Processes Database Queries in Real-Time

NASA Astrophysics Data System (ADS)

Gatsheni, Barnabas Ndlovu; Mabizela, Zwelakhe

A secure high-speed query processing mobile courier data access (MCDA) system for a Courier Company has been developed. This system uses the wireless networks in combination with wired networks for updating a live database at the courier centre in real-time by an offsite worker (the Courier). The system is protected by VPN based on IPsec. There is no system that we know of to date that performs the task for the courier as proposed in this paper.

Ad-Hoc Sensor Networks for Maritime Interdiction Operations and Regional Security

DTIC Science & Technology

2012-09-01

as resistant to rough sea conditions as the SHARC, since its maximum operation limit is sea state 3. Its maximum speed approaches three knots and...which renders it corrosion resistant and lightweight. Its length is 3.2 meters with a rotor diameter at 3.3 meters. It flies at speeds of 50 knots...NMIOTC main building and to a moored training ship (see Figure 50), (2) GSM/GPRS was networked with swimmers , (3) security patrol and target vessels

Report on dynamic speed harmonization and queue warning algorithm design.

DOT National Transportation Integrated Search

2014-02-01

This report provides a detailed description of the algorithms that will be used to generate harmonized recommended speeds and queue warning information in the proposed Intelligent Network Flow Optimization (INFLO) prototype. This document describes t...

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 23: Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Barclay, Rebecca O.; Bishop, Ann P.; Kennedy, John M.

1992-01-01

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowled reproduction, transfer, and use as equally important components of the process of knowledge diffusion. It is argued that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of the members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Cognitive and neuropathologic correlates of Stroop Color-Word Test performance in Alzheimer's disease.

PubMed

Bondi, Mark W; Serody, Adam B; Chan, Agnes S; Eberson-Shumate, Sonja C; Delis, Dean C; Hansen, Lawrence A; Salmon, David P

2002-07-01

The Stroop Color-Word Test (SCWT; C. Golden, 1978) was examined in 59 patients with probable Alzheimer's disease (AD) and in 51 demographically comparable normal control (NC) participants. AD patients produced significantly larger Stroop interference effects than NC participants, and level of dementia severity significantly influenced SCWT performance. Principal-components analyses demonstrated a dissociation in the factor structure of the Stroop trials between NC participants and AD patients, suggesting that disruption of semantic knowledge and speeded verbal processing in AD may be a major contributor to impairment on the incongruent trial. Results of clinicopathologic correlations in an autopsy-confirmed AD subgroup further suggest the invocation of a broad network of integrated cortical regions and executive and language processes underlying successful SCWT performance.

Building intelligent communication systems for handicapped aphasiacs.

PubMed

Fu, Yu-Fen; Ho, Cheng-Seen

2010-01-01

This paper presents an intelligent system allowing handicapped aphasiacs to perform basic communication tasks. It has the following three key features: (1) A 6-sensor data glove measures the finger gestures of a patient in terms of the bending degrees of his fingers. (2) A finger language recognition subsystem recognizes language components from the finger gestures. It employs multiple regression analysis to automatically extract proper finger features so that the recognition model can be fast and correctly constructed by a radial basis function neural network. (3) A coordinate-indexed virtual keyboard allows the users to directly access the letters on the keyboard at a practical speed. The system serves as a viable tool for natural and affordable communication for handicapped aphasiacs through continuous finger language input.

NASA/DoD Aerospace Knowledge Diffusion Research Project. XXIII - Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

NASA Technical Reports Server (NTRS)

Pinelli, Thomas E.; Barclay, Rebecca O.; Bishop, Ann P.; Kennedy, John M.

1992-01-01

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowledge production, transfer, and use as equally important components of the process of knowledge diffusion. This article argues that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid

PubMed Central

Li, Yuancheng; Jing, Sitong

2018-01-01

Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can’t satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy. PMID:29485990

High-Speed Optical Wide-Area Data-Communication Network

NASA Technical Reports Server (NTRS)

Monacos, Steve P.

1994-01-01

Proposed fiber-optic wide-area network (WAN) for digital communication balances input and output flows of data with its internal capacity by routing traffic via dynamically interconnected routing planes. Data transmitted optically through network by wavelength-division multiplexing in synchronous or asynchronous packets. WAN implemented with currently available technology. Network is multiple-ring cyclic shuffle exchange network ensuring traffic reaches its destination with minimum number of hops.

Composition and Realization of Source-to-Sink High-Performance Flows: File Systems, Storage, Hosts, LAN and WAN

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

Wu, Chase Qishi

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. To support such capabilities, significant progress has been made in various components including the deployment of 100 Gbps networks with future 1 Tbps bandwidth, increases in end-host capabilities with multiple cores and buses, capacity improvements in large disk arrays, and deployment of parallel file systems such as Lustre and GPFS. High-performance source-to-sink datamore » flows must be composed of these component systems, which requires significant optimizations of the storage-to-host data and execution paths to match the edge and long-haul network connections. In particular, end systems are currently supported by 10-40 Gbps Network Interface Cards (NIC) and 8-32 Gbps storage Host Channel Adapters (HCAs), which carry the individual flows that collectively must reach network speeds of 100 Gbps and higher. Indeed, such data flows must be synthesized using multicore, multibus hosts connected to high-performance storage systems on one side and to the network on the other side. Current experimental results show that the constituent flows must be optimally composed and preserved from storage systems, across the hosts and the networks with minimal interference. Furthermore, such a capability must be made available transparently to the science users without placing undue demands on them to account for the details of underlying systems and networks. And, this task is expected to become even more complex in the future due to the increasing sophistication of hosts, storage systems, and networks that constitute the high-performance flows. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align and transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections. These solutions will be tested using (1) 100 Gbps connection(s) between Oak Ridge National Laboratory (ORNL) and Argonne National Laboratory (ANL) with storage systems supported by Lustre and GPFS file systems with an asymmetric connection to University of Memphis (UM); (2) ORNL testbed with multicore and multibus hosts, switches with OpenFlow capabilities, and network emulators; and (3) 100 Gbps connections from ESnet and their Openflow testbed, and other experimental connections. This proposal brings together the expertise and facilities of the two national laboratories, ORNL and ANL, and UM. It also represents a collaboration between DOE and the Department of Defense (DOD) projects at ORNL by sharing technical expertise and personnel costs, and leveraging the existing DOD Extreme Scale Systems Center (ESSC) facilities at ORNL.« less

An Experimental Investigation into the Optimal Processing Conditions for the CO2 Laser Cladding of 20 MnCr5 Steel Using Taguchi Method and ANN

NASA Astrophysics Data System (ADS)

Mondal, Subrata; Bandyopadhyay, Asish.; Pal, Pradip Kumar

2010-10-01

This paper presents the prediction and evaluation of laser clad profile formed by means of CO2 laser applying Taguchi method and the artificial neural network (ANN). Laser cladding is one of the surface modifying technologies in which the desired surface characteristics of any component can be achieved such as good corrosion resistance, wear resistance and hardness etc. Laser is used as a heat source to melt the anti-corrosive powder of Inconel-625 (Super Alloy) to give a coating on 20 MnCr5 substrate. The parametric study of this technique is also attempted here. The data obtained from experiments have been used to develop the linear regression equation and then to develop the neural network model. Moreover, the data obtained from regression equations have also been used as supporting data to train the neural network. The artificial neural network (ANN) is used to establish the relationship between the input/output parameters of the process. The established ANN model is then indirectly integrated with the optimization technique. It has been seen that the developed neural network model shows a good degree of approximation with experimental data. In order to obtain the combination of process parameters such as laser power, scan speed and powder feed rate for which the output parameters become optimum, the experimental data have been used to develop the response surfaces.

An oilspill trajectory analysis model with a variable wind deflection angle

USGS Publications Warehouse

Samuels, W.B.; Huang, N.E.; Amstutz, D.E.

1982-01-01

The oilspill trajectory movement algorithm consists of a vector sum of the surface drift component due to wind and the surface current component. In the U.S. Geological Survey oilspill trajectory analysis model, the surface drift component is assumed to be 3.5% of the wind speed and is rotated 20 degrees clockwise to account for Coriolis effects in the Northern Hemisphere. Field and laboratory data suggest, however, that the deflection angle of the surface drift current can be highly variable. An empirical formula, based on field observations and theoretical arguments relating wind speed to deflection angle, was used to calculate a new deflection angle at each time step in the model. Comparisons of oilspill contact probabilities to coastal areas calculated for constant and variable deflection angles showed that the model is insensitive to this changing angle at low wind speeds. At high wind speeds, some statistically significant differences in contact probabilities did appear. ?? 1982.

Functional subdivision of group-ICA results of fMRI data collected during cinema viewing.

PubMed

Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

2012-01-01

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film ("At land" by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service.

PubMed

Main, M L; Foltz, D; Firstenberg, M S; Bobinsky, E; Bailey, D; Frantz, B; Pleva, D; Baldizzi, M; Meyers, D P; Jones, K; Spence, M C; Freeman, K; Morehead, A; Thomas, J D

2000-08-01

With high-resolution network transmission required for telemedicine, education, and guided-image acquisition, the impact of errors and transmission rates on image quality needs evaluation. We transmitted clinical echocardiograms from 2 National Aeronautics and Space Administration (NASA) research centers with the use of Motion Picture Expert Group-2 (MPEG-2) encoding and asynchronous transmission mode (ATM) network protocol over the NASA Research and Education Network. Data rates and network quality (cell losses [CLR], errors [CER], and delay variability [CVD]) were altered and image quality was judged. At speeds of 3 to 5 megabits per second (Mbps), digital images were superior to those on videotape; at 2 Mbps, images were equivalent. Increasing CLR caused occasional, brief pauses. Extreme CER and CDV increases still yielded high-quality images. Real-time echocardiographic acquisition, guidance, and transmission is feasible with the use of MPEG-2 and ATM with broadcast quality seen above 3 Mbps, even with severe network quality degradation. These techniques can be applied to telemedicine and used for planned echocardiography aboard the International Space Station.

Real-time transmission of full-motion echocardiography over a high-speed data network: impact of data rate and network quality of service

NASA Technical Reports Server (NTRS)

Main, M. L.; Foltz, D.; Firstenberg, M. S.; Bobinsky, E.; Bailey, D.; Frantz, B.; Pleva, D.; Baldizzi, M.; Meyers, D. P.; Jones, K.;

High speed all optical networks

NASA Technical Reports Server (NTRS)

Chlamtac, Imrich; Ganz, Aura

1990-01-01

An inherent problem of conventional point-to-point wide area network (WAN) architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. The first solution to wavelength division multiplexing (WDM) based WAN networks that overcomes this limitation is presented. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs. The principle of the Lightnet architecture is the construction and use of virtual topology networks, embedded in the original network in the wavelength domain. For this construction Lightnets utilize the new concept of lightpaths which constitute the links of the virtual topology. Lightpaths are all-optical, multihop, paths in the network that allow data to be switched through intermediate nodes using high throughput passive optical switches. The use of the virtual topologies and the associated switching design introduce a number of new ideas, which are discussed in detail.

Flank wears Simulation by using back propagation neural network when cutting hardened H-13 steel in CNC End Milling

NASA Astrophysics Data System (ADS)

Hazza, Muataz Hazza F. Al; Adesta, Erry Y. T.; Riza, Muhammad

2013-12-01

High speed milling has many advantages such as higher removal rate and high productivity. However, higher cutting speed increase the flank wear rate and thus reducing the cutting tool life. Therefore estimating and predicting the flank wear length in early stages reduces the risk of unaccepted tooling cost. This research presents a neural network model for predicting and simulating the flank wear in the CNC end milling process. A set of sparse experimental data for finish end milling on AISI H13 at hardness of 48 HRC have been conducted to measure the flank wear length. Then the measured data have been used to train the developed neural network model. Artificial neural network (ANN) was applied to predict the flank wear length. The neural network contains twenty hidden layer with feed forward back propagation hierarchical. The neural network has been designed with MATLAB Neural Network Toolbox. The results show a high correlation between the predicted and the observed flank wear which indicates the validity of the models.

The prediction of speed and incline in outdoor running in humans using accelerometry.

PubMed

Herren, R; Sparti, A; Aminian, K; Schutz, Y

1999-07-01

To explore whether triaxial accelerometric measurements can be utilized to accurately assess speed and incline of running in free-living conditions. Body accelerations during running were recorded at the lower back and at the heel by a portable data logger in 20 human subjects, 10 men, and 10 women. After parameterizing body accelerations, two neural networks were designed to recognize each running pattern and calculate speed and incline. Each subject ran 18 times on outdoor roads at various speeds and inclines; 12 runs were used to calibrate the neural networks whereas the 6 other runs were used to validate the model. A small difference between the estimated and the actual values was observed: the square root of the mean square error (RMSE) was 0.12 m x s(-1) for speed and 0.014 radiant (rad) (or 1.4% in absolute value) for incline. Multiple regression analysis allowed accurate prediction of speed (RMSE = 0.14 m x s(-1)) but not of incline (RMSE = 0.026 rad or 2.6% slope). Triaxial accelerometric measurements allows an accurate estimation of speed of running and incline of terrain (the latter with more uncertainty). This will permit the validation of the energetic results generated on the treadmill as applied to more physiological unconstrained running conditions.

Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm

PubMed Central

Tra, Viet; Kim, Jaeyoung; Kim, Jong-Myon

2017-01-01

This paper presents a novel method for diagnosing incipient bearing defects under variable operating speeds using convolutional neural networks (CNNs) trained via the stochastic diagonal Levenberg-Marquardt (S-DLM) algorithm. The CNNs utilize the spectral energy maps (SEMs) of the acoustic emission (AE) signals as inputs and automatically learn the optimal features, which yield the best discriminative models for diagnosing incipient bearing defects under variable operating speeds. The SEMs are two-dimensional maps that show the distribution of energy across different bands of the AE spectrum. It is hypothesized that the variation of a bearing’s speed would not alter the overall shape of the AE spectrum rather, it may only scale and translate it. Thus, at different speeds, the same defect would yield SEMs that are scaled and shifted versions of each other. This hypothesis is confirmed by the experimental results, where CNNs trained using the S-DLM algorithm yield significantly better diagnostic performance under variable operating speeds compared to existing methods. In this work, the performance of different training algorithms is also evaluated to select the best training algorithm for the CNNs. The proposed method is used to diagnose both single and compound defects at six different operating speeds. PMID:29211025

The complex genetics of gait speed: genome-wide meta-analysis approach

PubMed Central

Lunetta, Kathryn L.; Smith, Jennifer A.; Eicher, John D.; Vered, Rotem; Deelen, Joris; Arnold, Alice M.; Buchman, Aron S.; Tanaka, Toshiko; Faul, Jessica D.; Nethander, Maria; Fornage, Myriam; Adams, Hieab H.; Matteini, Amy M.; Callisaya, Michele L.; Smith, Albert V.; Yu, Lei; De Jager, Philip L.; Evans, Denis A.; Gudnason, Vilmundur; Hofman, Albert; Pattie, Alison; Corley, Janie; Launer, Lenore J.; Knopman, Davis S.; Parimi, Neeta; Turner, Stephen T.; Bandinelli, Stefania; Beekman, Marian; Gutman, Danielle; Sharvit, Lital; Mooijaart, Simon P.; Liewald, David C.; Houwing-Duistermaat, Jeanine J.; Ohlsson, Claes; Moed, Matthijs; Verlinden, Vincent J.; Mellström, Dan; van der Geest, Jos N.; Karlsson, Magnus; Hernandez, Dena; McWhirter, Rebekah; Liu, Yongmei; Thomson, Russell; Tranah, Gregory J.; Uitterlinden, Andre G.; Weir, David R.; Zhao, Wei; Starr, John M.; Johnson, Andrew D.; Ikram, M. Arfan; Bennett, David A.; Cummings, Steven R.; Deary, Ian J.; Harris, Tamara B.; Kardia, Sharon L. R.; Mosley, Thomas H.; Srikanth, Velandai K.; Windham, Beverly G.; Newman, Ann B.; Walston, Jeremy D.; Davies, Gail; Evans, Daniel S.; Slagboom, Eline P.; Ferrucci, Luigi; Kiel, Douglas P.; Murabito, Joanne M.; Atzmon, Gil

2017-01-01

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging. PMID:28077804

Shocks in fragile matter

NASA Astrophysics Data System (ADS)

Vitelli, Vincenzo

2012-02-01

Non-linear sound is an extreme phenomenon typically observed in solids after violent explosions. But granular media are different. Right when they unjam, these fragile and disordered solids exhibit vanishing elastic moduli and sound speed, so that even tiny mechanical perturbations form supersonic shocks. Here, we perform simulations in which two-dimensional jammed granular packings are continuously compressed, and demonstrate that the resulting excitations are strongly nonlinear shocks, rather than linear waves. We capture the full dependence of the shock speed on pressure and compression speed by a surprisingly simple analytical model. We also treat shear shocks within a simplified viscoelastic model of nearly-isostatic random networks comprised of harmonic springs. In this case, anharmonicity does not originate locally from nonlinear interactions between particles, as in granular media; instead, it emerges from the global architecture of the network. As a result, the diverging width of the shear shocks bears a nonlinear signature of the diverging isostatic length associated with the loss of rigidity in these floppy networks.

Seeing the forest for the trees: Networked workstations as a parallel processing computer

NASA Technical Reports Server (NTRS)

Breen, J. O.; Meleedy, D. M.

1992-01-01

Unlike traditional 'serial' processing computers in which one central processing unit performs one instruction at a time, parallel processing computers contain several processing units, thereby, performing several instructions at once. Many of today's fastest supercomputers achieve their speed by employing thousands of processing elements working in parallel. Few institutions can afford these state-of-the-art parallel processors, but many already have the makings of a modest parallel processing system. Workstations on existing high-speed networks can be harnessed as nodes in a parallel processing environment, bringing the benefits of parallel processing to many. While such a system can not rival the industry's latest machines, many common tasks can be accelerated greatly by spreading the processing burden and exploiting idle network resources. We study several aspects of this approach, from algorithms to select nodes to speed gains in specific tasks. With ever-increasing volumes of astronomical data, it becomes all the more necessary to utilize our computing resources fully.

Coarse cluster enhancing collaborative recommendation for social network systems

NASA Astrophysics Data System (ADS)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Characteristic electron variations across simple high-speed solar wind streams

NASA Technical Reports Server (NTRS)

Feldman, W. C.; Asbridge, J. R.; Bame, S. J.; Gosling, J. T.; Lemons, D. S.

1978-01-01

The paper deals with electron variations across simple high-speed streams. Comprehensive scans of the shapes of electron distributions measured at the highest bulk speeds confirm the results of Rosenbauer et al. (1976, 1977) and show that the electron velocity distributions can be broken down into a low-energy or core component and a high-energy strongly beamed component. The low-energy component displays many characteristics expected from a fluid: the internal particle coupling necessary to maintain this state must result from both binary Coulomb collisions and wave-particle interactions. The high-energy or halo component displays many characteristics expected to develop in the absence of collisions beyond a certain base radius. These electrons appear to evolve under the primary influence of static interplanetary magnetic and electric fields and, therefore, develop very anisotropic velocity distributions.

A three-sided rearrangeable switching network for a binary fat tree

NASA Astrophysics Data System (ADS)

Yen, Mao-Hsu; Yu, Chu; Shin, Haw-Yun; Chen, Sao-Jie

2011-06-01

A binary fat tree needs an internal node to interconnect the left-children, right-children and parent terminals to each other. In this article, we first propose a three-stage, 3-sided rearrangeable switching network for the implementation of a binary fat tree. The main component of this 3-sided switching network (3SSN) consists of a polygonal switch block (PSB) interconnected by crossbars. With the same size and the same number of switches as our 3SSN, a three-stage, 3-sided clique-based switching network is shown to be not rearrangeable. Also, the effects of the rearrangeable structure and the number of terminals on the network switch-efficiency are explored and a proper set of parameters has been determined to minimise the number of switches. We derive that a rearrangeable 3-sided switching network with switches proportional to N 3/2 is most suitable to interconnect N terminals. Moreover, we propose a new Polygonal Field Programmable Gate Array (PFPGA) that consists of logic blocks interconnected by our 3SSN, such that the logic blocks in this PFPGA can be grouped into clusters to implement different logic functions. Since the programmable switches usually have high resistance and capacitance and occupy a large area, we have to consider the effect of the 3SSN structure and the granularity of its cluster logic blocks on the switch efficiency of PFPGA. Experiments on benchmark circuits show that the switch and speed performances are significantly improved. Based on the experimental results, we can determine the parameters of PFPGA for the VLSI implementation.

Videoconferencing Comes of Age.

ERIC Educational Resources Information Center

Bosak, Steve

2000-01-01

Hundreds of districts are using high-speed videoconferencing for distance learning and resource sharing, inservice training, and districtwide meetings. Speed matters. Districts will need either Ethernet or ATM (asynchronous transfer mode) forms of wide-area networks to connect schools and offices. (MLH)

Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics.

PubMed

Maurer, Christian; Federolf, Peter; von Tscharner, Vinzenz; Stirling, Lisa; Nigg, Benno M

2012-05-01

Changes in gait kinematics have often been analyzed using pattern recognition methods such as principal component analysis (PCA). It is usually just the first few principal components that are analyzed, because they describe the main variability within a dataset and thus represent the main movement patterns. However, while subtle changes in gait pattern (for instance, due to different footwear) may not change main movement patterns, they may affect movements represented by higher principal components. This study was designed to test two hypotheses: (1) speed and gender differences can be observed in the first principal components, and (2) small interventions such as changing footwear change the gait characteristics of higher principal components. Kinematic changes due to different running conditions (speed - 3.1m/s and 4.9 m/s, gender, and footwear - control shoe and adidas MicroBounce shoe) were investigated by applying PCA and support vector machine (SVM) to a full-body reflective marker setup. Differences in speed changed the basic movement pattern, as was reflected by a change in the time-dependent coefficient derived from the first principal. Gender was differentiated by using the time-dependent coefficient derived from intermediate principal components. (Intermediate principal components are characterized by limb rotations of the thigh and shank.) Different shoe conditions were identified in higher principal components. This study showed that different interventions can be analyzed using a full-body kinematic approach. Within the well-defined vector space spanned by the data of all subjects, higher principal components should also be considered because these components show the differences that result from small interventions such as footwear changes. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

S3: School Zone Safety System Based on Wireless Sensor Network

PubMed Central

Yoo, Seong-eun; Chong, Poh Kit; Kim, Daeyoung

2009-01-01

School zones are areas near schools that have lower speed limits and where illegally parked vehicles pose a threat to school children by obstructing them from the view of drivers. However, these laws are regularly flouted. Thus, we propose a novel wireless sensor network application called School zone Safety System (S3) to help regulate the speed limit and to prevent illegal parking in school zones. S3 detects illegally parked vehicles, and warns the driver and records the license plate number. To reduce the traveling speed of vehicles in a school zone, S3 measures the speed of vehicles and displays the speed to the driver via an LED display, and also captures the image of the speeding vehicle with a speed camera. We developed a state machine based vehicle detection algorithm for S3. From extensive experiments in our testbeds and data from a real school zone, it is shown that the system can detect all kinds of vehicles, and has an accuracy of over 95% for speed measurement. We modeled the battery life time of a sensor node and validated the model with a downscaled measurement; we estimate the battery life time to be over 2 years. We have deployed S3 in 15 school zones in 2007, and we have demonstrated the robustness of S3 by operating them for over 1 year. PMID:22454567

Calculation of Sensitivity Derivatives in an MDAO Framework

NASA Technical Reports Server (NTRS)

Moore, Kenneth T.

2012-01-01

During gradient-based optimization of a system, it is necessary to generate the derivatives of each objective and constraint with respect to each design parameter. If the system is multidisciplinary, it may consist of a set of smaller "components" with some arbitrary data interconnection and process work ow. Analytical derivatives in these components can be used to improve the speed and accuracy of the derivative calculation over a purely numerical calculation; however, a multidisciplinary system may include both components for which derivatives are available and components for which they are not. Three methods to calculate the sensitivity of a mixed multidisciplinary system are presented: the finite difference method, where the derivatives are calculated numerically; the chain rule method, where the derivatives are successively cascaded along the system's network graph; and the analytic method, where the derivatives come from the solution of a linear system of equations. Some improvements to these methods, to accommodate mixed multidisciplinary systems, are also presented; in particular, a new method is introduced to allow existing derivatives to be used inside of finite difference. All three methods are implemented and demonstrated in the open-source MDAO framework OpenMDAO. It was found that there are advantages to each of them depending on the system being solved.

[Construction of DICOM-WWW gateway by open source, and application to PDAs using the high-speed mobile communications network].

PubMed

Yokohama, Noriya

2003-09-01

The author constructed a medical image network system using open source software that took security into consideration. This system was enabled for search and browse with a WWW browser, and images were stored in a DICOM server. In order to realize this function, software was developed to fill in the gap between the DICOM protocol and HTTP using PHP language. The transmission speed was evaluated by the difference in protocols between DICOM and HTTP. Furthermore, an attempt was made to evaluate the convenience of medical image access with a personal information terminal via the Internet through the high-speed mobile communication terminal. Results suggested the feasibility of remote diagnosis and application to emergency care.

High speed photodiodes in standard nanometer scale CMOS technology: a comparative study.

PubMed

Nakhkoob, Behrooz; Ray, Sagar; Hella, Mona M

2012-05-07

This paper compares various techniques for improving the frequency response of silicon photodiodes fabricated in mainstream CMOS technology for fully integrated optical receivers. The three presented photodiodes, Spatially Modulated Light detectors, Double, and Interrupted P-Finger photodiodes, aim at reducing the low speed diffusive component of the photo generated current. For the first photodiode, Spatially Modulated Light (SML) detectors, the low speed current component is canceled out by converting it to a common mode current driving a differential transimpedance amplifier. The Double Photodiode (DP) uses two depletion regions to increase the fast drift component, while the Interrupted-P Finger Photodiode (IPFPD) redirects the low speed component towards a different contact from the main fast terminal of the photodiode. Extensive device simulations using 130 nm CMOS technology-parameters are presented to compare their performance using the same technological platform. Finally a new type of photodiode that uses triple well CMOS technology is introduced that can achieve a bandwidth of roughly 10 GHz without any process modification or high reverse bias voltages that would jeopardize the photodetector and subsequent transimpedance amplifier reliability.

Stability of a giant connected component in a complex network

NASA Astrophysics Data System (ADS)

Kitsak, Maksim; Ganin, Alexander A.; Eisenberg, Daniel A.; Krapivsky, Pavel L.; Krioukov, Dmitri; Alderson, David L.; Linkov, Igor

2018-01-01

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

VPIsystems industry training program on computer-aided design of fiber optic communication systems

NASA Astrophysics Data System (ADS)

Richter, Andre; Chan, David K. C.

2002-05-01

In industry today, professional Photonic Design Automation (PDA) tools are a necessity to enable fast development cycles for the design of optical components, systems and networks. The training of industrial personnel is of great importance in facilitating the full usability of PDA tools tailored to meet these demands. As the market leader of design and planning tools for system integrators and manufacturers of optical transmission systems and components, VPIsystems offers a set of two-day training courses. Attendees are taught on the design of metro WDM networks, high speed DWDM and ultra long-haul WDM systems, analogue and digital cable access systems, EDFA and Raman amplifiers, as well as active devices and circuits. The course work compromises of: (1) lectures on physical and modeling background topics; (2) creation of typical simulation scenarios and; (3) the analysis of results. This course work is facilitated by guided, hands-on lab exercises using VPIsystems software for a variety of practical design situations. In classes of up to 15, each attendee is allocated a computer, thereby allowing for a thorough and speedy training for the individual in all of the covered topics as well as for any extra-curriculum topics to be covered. Since 1999, more than 750 people have graduated from over 60 training courses. In this paper, details of VPIsystems Industry training program will be presented.

Fiber-channel audio video standard for military and commercial aircraft product lines

NASA Astrophysics Data System (ADS)

Keller, Jack E.

2002-08-01

Fibre channel is an emerging high-speed digital network technology that combines to make inroads into the avionics arena. The suitability of fibre channel for such applications is largely due to its flexibility in these key areas: Network topologies can be configured in point-to-point, arbitrated loop or switched fabric connections. The physical layer supports either copper or fiber optic implementations with a Bit Error Rate of less than 10-12. Multiple Classes of Service are available. Multiple Upper Level Protocols are supported. Multiple high speed data rates offer open ended growth paths providing speed negotiation within a single network. Current speeds supported by commercially available hardware are 1 and 2 Gbps providing effective data rates of 100 and 200 MBps respectively. Such networks lend themselves well to the transport of digital video and audio data. This paper summarizes an ANSI standard currently in the final approval cycle of the InterNational Committee for Information Technology Standardization (INCITS). This standard defines a flexible mechanism whereby digital video, audio and ancillary data are systematically packaged for transport over a fibre channel network. The basic mechanism, called a container, houses audio and video content functionally grouped as elements of the container called objects. Featured in this paper is a specific container mapping called Simple Parametric Digital Video (SPDV) developed particularly to address digital video in avionics systems. SPDV provides pixel-based video with associated ancillary data typically sourced by various sensors to be processed and/or distributed in the cockpit for presentation via high-resolution displays. Also highlighted in this paper is a streamlined Upper Level Protocol (ULP) called Frame Header Control Procedure (FHCP) targeted for avionics systems where the functionality of a more complex ULP is not required.

Hardware Neural Network for a Visual Inspection System

NASA Astrophysics Data System (ADS)

Chun, Seungwoo; Hayakawa, Yoshihiro; Nakajima, Koji

The visual inspection of defects in products is heavily dependent on human experience and instinct. In this situation, it is difficult to reduce the production costs and to shorten the inspection time and hence the total process time. Consequently people involved in this area desire an automatic inspection system. In this paper, we propose a hardware neural network, which is expected to provide high-speed operation for automatic inspection of products. Since neural networks can learn, this is a suitable method for self-adjustment of criteria for classification. To achieve high-speed operation, we use parallel and pipelining techniques. Furthermore, we use a piecewise linear function instead of a conventional activation function in order to save hardware resources. Consequently, our proposed hardware neural network achieved 6GCPS and 2GCUPS, which in our test sample proved to be sufficiently fast.

Design and implementation of novel nonlinear processes in bulk and waveguide periodic structures

NASA Astrophysics Data System (ADS)

Kajal, Meenu

The telecommunication networks are facing increasing demand to implement all-optical network infrastructure for enabling the wide deployment of new triple play high-speed services (e.g. IPTV, Video On Demand, Voice over IP). One of the challenges with such video broadcasting applications is that these are much more distributed and multi-point in nature unlike the traditional point-to-point communication networks. Currently deployed high-speed electronic components in the optical networks are incapable of handling the unprecedented bandwidth demand for real-time multimedia based broadcasting. The solution essentially lies in increasing the transparency of networks i.e. by replacing high speed signal processing electronics with all-optical signal processors capable of performing signal manipulations such as wavelength switching, time and wavelength division multiplexing, optical pulse compression etc. all in optical domain. This thesis aims at providing an all-optical solution for broadband wavelength conversion and tunable broadcasting, a crucial optical network component, based on quasi-phase-matched wave mixing in nonlinear materials. The quasi phase matching (QPM) technique allows phase matching in long crystal lengths by employing domain-inverted gratings to periodically reverse the sign of nonlinearity, known as periodic poling. This results into new frequency components with high conversion efficiency and has been successfully implemented towards various processes such as second harmonic generation (SHG), sum- and difference- frequency generation (SFG and DFG). Conventionally, the optical networks has an operation window of ˜35 nm centered at 1.55 mum, known as C-band. The wavelength conversion of a signal channel in C-band to an output channel also in the C-band has been demonstrated in periodically poled lithium niobate (PPLN) waveguides via the process of difference frequency mixing, cascaded SHG/DFG and cascaded SFG/DFG. While a DFG process utilized a pump wavelength in 775nm regime, it suffered from low efficiency due to mode mismatch between the pump and the signal wavelengths; whereas the technique based on cSHG/DFG or cSFG/DFG eliminated the mode mismatch problem with pump(s) lying in the 1.55 mum wavelength regime. In this thesis, for the first time a flattened bandwidth of cSFG/DFG have been experimentally realized by slight detuning of the pump wavelengths from their phase matching condition. Moreover, employing two closely spaced pumps in a cSFG/DFG process in a PPLN waveguide, a signal has been broadcast to three idlers in C-band. Although a uniform period PPLN grating increases efficiency by the use of highest nonlinearity tensor coefficient via QPM, it suffers from the limitation of a narrow bandwidth of frequency doubling. The narrow bandwidth restricts the choice of pump wavelengths in a cascaded conversion process and consequently the converted signal wavelength is also fixed for a given signal wavelength. Enhancing the frequency doubling bandwidth is necessary for mainly two reasons: firstly, to achieve the tunability of wavelength conversion of a signal to any channel in the communication band; and secondly, to broadcast a signal to several channels simultaneously by employing multiple pump lasers within its broad bandwidth. The first engineered PPLN device proposed and demonstrated in this thesis for broadband wavelength conversion has an aperiodic domain in the center of an otherwise periodic grating. This phase-shifted or aperiodic (a-) PPLN has a dual-peak SH response with an increase in bandwidth compared to a uniform PPLN. It has also been shown that using temperature tuning, the phase matching conditions of the aPPLN can be varied and its SH bandwidth can be further enhanced. The triple-idler broadcasting is shown and for the first time, the idlers are tuned across 40 channels in C-band with flexible location and mutual spacing in the WDM grid assisted with pump detuning and temperature tuning. Although the temperature-tuning scheme solves the problem of narrow SH bandwidth and tunability of conversion, the slow speed of temperature change makes it inadequate for ultra-fast WDM applications. Therefore, a temperature-independent broadband device has been demonstrated for the first time in this dissertation, using a step-chirped grating (SCG), which has an inherent 30-nm SH bandwidth overlapping the C-band. This device obviates the need of temperature tuning and leads to tunable wavelength conversion and flexible broadcasting. Employing a single tuned pump wavelength in the SC-PPLN, conversion of a signal in C-band to tunable dual idlers via cSHG/DFG process is demonstrated for the first time. Also by taking advantage of the broad SH-SF bandwidth, for the first time, agile broadcasting of a signal to seven idlers spanning across C-band with variable position in the grid is realized based on cSHG/DFG and cSFG/DFG processes. By tuning the two pump wavelengths over less than 6 nm, broadcasting is achieved across ˜70 WDM channels within the 50 GHz spacing WDM grid. (Abstract shortened by UMI.).

Wireless Local Area Networks: The Next Evolutionary Step.

ERIC Educational Resources Information Center

Wodarz, Nan

2001-01-01

The Institute of Electrical and Electronics Engineers recently approved a high-speed wireless standard that enables devices from different manufacturers to communicate through a common backbone, making wireless local area networks more feasible in schools. Schools can now use wireless access points and network cards to provide flexible…

Teaching Heat Exchanger Network Synthesis Using Interactive Microcomputer Graphics.

ERIC Educational Resources Information Center

Dixon, Anthony G.

1987-01-01

Describes the Heat Exchanger Network Synthesis (HENS) program used at Worcester Polytechnic Institute (Massachusetts) as an aid to teaching the energy integration step in process design. Focuses on the benefits of the computer graphics used in the program to increase the speed of generating and changing networks. (TW)

Spoken Word Recognition and Serial Recall of Words from Components in the Phonological Network

ERIC Educational Resources Information Center

Siew, Cynthia S. Q.; Vitevitch, Michael S.

2016-01-01

Network science uses mathematical techniques to study complex systems such as the phonological lexicon (Vitevitch, 2008). The phonological network consists of a "giant component" (the largest connected component of the network) and "lexical islands" (smaller groups of words that are connected to each other, but not to the giant…

A virus spreading model for cognitive radio networks

NASA Astrophysics Data System (ADS)

Hou, L.; Yeung, K. H.; Wong, K. Y.

2012-12-01

Since cognitive radio (CR) networks could solve the spectrum scarcity problem, they have drawn much research in recent years. Artificial intelligence(AI) is introduced into CRs to learn from and adapt to their environment. Nonetheless, AI brings in a new kind of attacks specific to CR networks. The most powerful one is a self-propagating AI virus. And no spreading properties specific to this virus have been reported in the literature. To fill this research gap, we propose a virus spreading model of an AI virus by considering the characteristics of CR networks and the behavior of CR users. Several important observations are made from the simulation results based on the model. Firstly, the time taken to infect the whole network increases exponentially with the network size. Based on this result, CR network designers could calculate the optimal network size to slow down AI virus propagation rate. Secondly, the anti-virus performance of static networks to an AI virus is better than dynamic networks. Thirdly, if the CR devices with the highest degree are initially infected, the AI virus propagation rate will be increased substantially. Finally, it is also found that in the area with abundant spectrum resource, the AI virus propagation speed increases notably but the variability of the spectrum does not affect the propagation speed much.

Optical burst switching based satellite backbone network

NASA Astrophysics Data System (ADS)

Li, Tingting; Guo, Hongxiang; Wang, Cen; Wu, Jian

2018-02-01

We propose a novel time slot based optical burst switching (OBS) architecture for GEO/LEO based satellite backbone network. This architecture can provide high speed data transmission rate and high switching capacity . Furthermore, we design the control plane of this optical satellite backbone network. The software defined network (SDN) and network slice (NS) technologies are introduced. Under the properly designed control mechanism, this backbone network is flexible to support various services with diverse transmission requirements. Additionally, the LEO access and handoff management in this network is also discussed.

ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs.

PubMed

Abbas, Adel Taha; Pimenov, Danil Yurievich; Erdakov, Ivan Nikolaevich; Taha, Mohamed Adel; Soliman, Mahmoud Sayed; El Rayes, Magdy Mostafa

2018-05-16

Magnesium alloys are widely used in aerospace vehicles and modern cars, due to their rapid machinability at high cutting speeds. A novel Edgeworth⁻Pareto optimization of an artificial neural network (ANN) is presented in this paper for surface roughness ( Ra ) prediction of one component in computer numerical control (CNC) turning over minimal machining time ( T m ) and at prime machining costs ( C ). An ANN is built in the Matlab programming environment, based on a 4-12-3 multi-layer perceptron (MLP), to predict Ra , T m , and C , in relation to cutting speed, v c , depth of cut, a p , and feed per revolution, f r . For the first time, a profile of an AZ61 alloy workpiece after finish turning is constructed using an ANN for the range of experimental values v c , a p , and f r . The global minimum length of a three-dimensional estimation vector was defined with the following coordinates: Ra = 0.087 μm, T m = 0.358 min/cm³, C = $8.2973. Likewise, the corresponding finish-turning parameters were also estimated: cutting speed v c = 250 m/min, cutting depth a p = 1.0 mm, and feed per revolution f r = 0.08 mm/rev. The ANN model achieved a reliable prediction accuracy of ±1.35% for surface roughness.

Reorganization of large-scale cognitive networks during automation of imagination of a complex sequential movement.

PubMed

Sauvage, C; De Greef, N; Manto, M; Jissendi, P; Nioche, C; Habas, C

2015-04-01

We investigated the functional reconfiguration of the cerebral networks involved in imagination of sequential movements of the left foot, both performed at regular and fast speed after mental imagery training. Thirty-five volunteers were scanned with a 3T MRI while they imagined a sequence of ankle movements (dorsiflexion, plantar flexion, varus and valgus) before and after mental practice. Subjects were distributed in two groups: the first group executed regular movements whereas the second group made fast movements. We applied the general linear model (GLM) and model-free, exploratory tensorial independent component analytic (TICA) approaches to identify plastic post-training effects on brain activation. GLM showed that post-training imagination of movement was accompanied by a dual effect: a specific recruitment of a medial prefronto-cingulo-parietal circuit reminiscent of the default-mode network, with the left putamen, and a decreased activity of a lateral fronto-parietal network. Training-related subcortical changes only consisted in an increased activity in the left striatum. Unexpectedly, no difference was observed in the cerebellum. TICA also revealed involvement of the left executive network, and of the dorsal control executive network but no significant differences were found between pre- and post-training phases. Therefore, repetitive motor mental imagery induced specific putamen (motor rehearsal) recruitment that one previously observed during learning of overt movements, and, simultaneously, a specific shift of activity from the dorsolateral prefrontal cortex (attention, working memory) to the medial posterior parietal and cingulate cortices (mental imagery and memory rehearsal). Our data complement and confirm the notion that differential and coupled recruitment of cognitive networks can constitute a neural marker of training effects. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Designed a web crawler which oriented network public opinion data acquisition

NASA Astrophysics Data System (ADS)

Lu, Shan; Ma, Hui; Gao, Ying

2015-12-01

The paper describes the meaning of network public opinion and the network public opinion research of data acquisition technique. Designed and implemented a web crawler which oriented network public opinion data acquisition. Insufficient analysis of the generic web crawler, using asynchronous Socket, DNS cache, and queue downloads to improve its bottom story frame, increase the speed of collecting.

Estimating workforce development needs for high-speed rail in California : [research brief].

DOT National Transportation Integrated Search

2012-03-01

It is critical to understand the emergent workforce characteristics for the California High-Speed Rail (HSR) network. Knowledge about the size and characteristics of this workforce, including its training and education needs, is required to guide the...

Estimating workforce development needs for high-speed rail in California.

DOT National Transportation Integrated Search

2012-03-01

This study provides an assessment of the job creation and attendant education and training needs associated with the creation of the California High-Speed Rail (CHSR) network, scheduled to begin construction in September 2012. Given the high profile ...

Quantifying a cellular automata simulation of electric vehicles

NASA Astrophysics Data System (ADS)

Hill, Graeme; Bell, Margaret; Blythe, Phil

2014-12-01

Within this work the Nagel-Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.

Using a CLIPS expert system to automatically manage TCP/IP networks and their components

NASA Technical Reports Server (NTRS)

Faul, Ben M.

1991-01-01

A expert system that can directly manage networks components on a Transmission Control Protocol/Internet Protocol (TCP/IP) network is described. Previous expert systems for managing networks have focused on managing network faults after they occur. However, this proactive expert system can monitor and control network components in near real time. The ability to directly manage network elements from the C Language Integrated Production System (CLIPS) is accomplished by the integration of the Simple Network Management Protocol (SNMP) and a Abstract Syntax Notation (ASN) parser into the CLIPS artificial intelligence language.

Deterministic-random separation in nonstationary regime

NASA Astrophysics Data System (ADS)

Abboud, D.; Antoni, J.; Sieg-Zieba, S.; Eltabach, M.

2016-02-01

In rotating machinery vibration analysis, the synchronous average is perhaps the most widely used technique for extracting periodic components. Periodic components are typically related to gear vibrations, misalignments, unbalances, blade rotations, reciprocating forces, etc. Their separation from other random components is essential in vibration-based diagnosis in order to discriminate useful information from masking noise. However, synchronous averaging theoretically requires the machine to operate under stationary regime (i.e. the related vibration signals are cyclostationary) and is otherwise jeopardized by the presence of amplitude and phase modulations. A first object of this paper is to investigate the nature of the nonstationarity induced by the response of a linear time-invariant system subjected to speed varying excitation. For this purpose, the concept of a cyclo-non-stationary signal is introduced, which extends the class of cyclostationary signals to speed-varying regimes. Next, a "generalized synchronous average'' is designed to extract the deterministic part of a cyclo-non-stationary vibration signal-i.e. the analog of the periodic part of a cyclostationary signal. Two estimators of the GSA have been proposed. The first one returns the synchronous average of the signal at predefined discrete operating speeds. A brief statistical study of it is performed, aiming to provide the user with confidence intervals that reflect the "quality" of the estimator according to the SNR and the estimated speed. The second estimator returns a smoothed version of the former by enforcing continuity over the speed axis. It helps to reconstruct the deterministic component by tracking a specific trajectory dictated by the speed profile (assumed to be known a priori).The proposed method is validated first on synthetic signals and then on actual industrial signals. The usefulness of the approach is demonstrated on envelope-based diagnosis of bearings in variable-speed operation.

Merlot Design

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

Ahern, S D

2003-06-10

We describe Merlot, a system for delivery of digital imagery over high speed networks. We describe various use cases, the client/server interaction, and the image and network codecs. We also describe some possible applications using Merlot and future work.

Functional Subdivision of Group-ICA Results of fMRI Data Collected during Cinema Viewing

PubMed Central

Pamilo, Siina; Malinen, Sanna; Hlushchuk, Yevhen; Seppä, Mika; Tikka, Pia; Hari, Riitta

2012-01-01

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film (“At land” by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative. PMID:22860044

Design Tools for Evaluating Multiprocessor Programs

DTIC Science & Technology

1976-07-01

than large uniprocessing machines, and 2. economies of scale in manufacturing. Perhaps the most compelling reason (possibly a consequence of the...speed, redundancy, (inefficiency, resource utilization, and economies of the components. [Browne 73, Lehman 66] 6. How can the system be scheduled...mejsures are interesting about the computation? Somn may be: speed, redundancy, (inefficiency, resource utilization, and economies of the components

Frequency-domain ultrasound waveform tomography breast attenuation imaging

NASA Astrophysics Data System (ADS)

Sandhu, Gursharan Yash Singh; Li, Cuiping; Roy, Olivier; West, Erik; Montgomery, Katelyn; Boone, Michael; Duric, Neb

2016-04-01

Ultrasound waveform tomography techniques have shown promising results for the visualization and characterization of breast disease. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, we have previously reconstructed the sound speed distributions of breasts of varying densities with different types of breast disease including benign and malignant lesions. By allowing the sound speed to have an imaginary component, we can model the intrinsic attenuation of a medium. We can similarly recover the imaginary component of the velocity and thus the attenuation. In this paper, we will briefly review ultrasound waveform tomography techniques, discuss attenuation and its relations to the imaginary component of the sound speed, and provide both numerical and ex vivo examples of waveform tomography attenuation reconstructions.

Low Temperature Performance of High-Speed Neural Network Circuits

NASA Technical Reports Server (NTRS)

Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

1995-01-01

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

Evaluation of barriers for very high speed roadways.

DOT National Transportation Integrated Search

2010-03-01

As TxDOT plans for future expansion of the states highway network, interest in higher design : speeds has been expressed as a means of promoting faster and more efficient travel and movement of goods : within the state. TxDOT funded project 0-6071...

Numerical solution of differential equations by artificial neural networks

NASA Technical Reports Server (NTRS)

Meade, Andrew J., Jr.

1995-01-01

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks (ANN's) are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed by the author to mate the adaptability of the ANN with the speed and precision of the digital computer. This method has been successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Mid- to high-frequency noise from high-speed boats and its potential impacts on humpback dolphins.

PubMed

Li, Songhai; Wu, Haiping; Xu, Youhou; Peng, Chongwei; Fang, Liang; Lin, Mingli; Xing, Luru; Zhang, Peijun

2015-08-01

The impact of noise made by vessels on marine animals has come under increased concern. However, most measurements on noise from vessels have only taken into account the low-frequency components. For cetaceans operating in the mid- and high-frequencies, such as the Indo-Pacific humpback dolphin (Sousa chinensis), mid- to high-frequency noise components may be of more concern, in terms of their potential impacts. In this study, noise made by a small high-speed boat was recorded using a broadband recording system in a dolphin watching area focusing on the effects on humpback dolphins in Sanniang Bay, China. The high-speed boat produced substantial mid- to high-frequency noise components with frequencies to >100 kHz, measured at three speeds: ∼40, 30, and 15 km/h. The noise from the boat raised the ambient noise levels from ∼5 to 47 decibels (dB) root-mean-square (rms) across frequency bands ranging from 1 to 125 kHz at a distance of 20 to 85 m, with louder levels recorded at higher speeds and at closer distances. To conclude, the noise produced by the small high-speed boat could be heard by Sousa chinensis and therefore potentially had adverse effects on the dolphins.

Structural integrity of power generating speed bumps made of concrete foam composite

NASA Astrophysics Data System (ADS)

Syam, B.; Muttaqin, M.; Hastrino, D.; Sebayang, A.; Basuki, W. S.; Sabri, M.; Abda, S.

2018-02-01

In this paper concrete foam composite speed bumps were designed to generate electrical power by utilizing the movements of commuting vehicles on highways, streets, parking gates, and drive-thru station of fast food restaurants. The speed bumps were subjected to loadings generated by vehicles pass over the power generating mechanical system. In this paper, we mainly focus our discussion on the structural integrity of the speed bumps and discuss the electrical power generating speed bumps in another paper. One aspect of structural integrity is its ability to support designed loads without breaking and includes the study of past structural failures in order to prevent failures in future designs. The concrete foam composites were used for the speed bumps; the reinforcement materials are selected from empty fruit bunch of oil palm. In this study, the speed bump materials and structure were subjected to various tests to obtain its physical and mechanical properties. To analyze the structure stability of the speed bumps some models were produced and tested in our speed bump test station. We also conduct a FEM-based computer simulation to analyze stress responses of the speed bump structures. It was found that speed bump type 1 significantly reduced the radial voltage. In addition, the speed bump is equipped with a steel casing is also suitable for use as a component component in generating electrical energy.

Improving the Efficiency and Effectiveness of Community Detection via Prior-Induced Equivalent Super-Network.

PubMed

Yang, Liang; Jin, Di; He, Dongxiao; Fu, Huazhu; Cao, Xiaochun; Fogelman-Soulie, Francoise

2017-03-29

Due to the importance of community structure in understanding network and a surge of interest aroused on community detectability, how to improve the community identification performance with pairwise prior information becomes a hot topic. However, most existing semi-supervised community detection algorithms only focus on improving the accuracy but ignore the impacts of priors on speeding detection. Besides, they always require to tune additional parameters and cannot guarantee pairwise constraints. To address these drawbacks, we propose a general, high-speed, effective and parameter-free semi-supervised community detection framework. By constructing the indivisible super-nodes according to the connected subgraph of the must-link constraints and by forming the weighted super-edge based on network topology and cannot-link constraints, our new framework transforms the original network into an equivalent but much smaller Super-Network. Super-Network perfectly ensures the must-link constraints and effectively encodes cannot-link constraints. Furthermore, the time complexity of super-network construction process is linear in the original network size, which makes it efficient. Meanwhile, since the constructed super-network is much smaller than the original one, any existing community detection algorithm is much faster when using our framework. Besides, the overall process will not introduce any additional parameters, making it more practical.

Experimental high-speed network

NASA Astrophysics Data System (ADS)

McNeill, Kevin M.; Klein, William P.; Vercillo, Richard; Alsafadi, Yasser H.; Parra, Miguel V.; Dallas, William J.

1993-09-01

Many existing local area networking protocols currently applied in medical imaging were originally designed for relatively low-speed, low-volume networking. These protocols utilize small packet sizes appropriate for text based communication. Local area networks of this type typically provide raw bandwidth under 125 MHz. These older network technologies are not optimized for the low delay, high data traffic environment of a totally digital radiology department. Some current implementations use point-to-point links when greater bandwidth is required. However, the use of point-to-point communications for a total digital radiology department network presents many disadvantages. This paper describes work on an experimental multi-access local area network called XFT. The work includes the protocol specification, and the design and implementation of network interface hardware and software. The protocol specifies the Physical and Data Link layers (OSI layers 1 & 2) for a fiber-optic based token ring providing a raw bandwidth of 500 MHz. The protocol design and implementation of the XFT interface hardware includes many features to optimize image transfer and provide flexibility for additional future enhancements which include: a modular hardware design supporting easy portability to a variety of host system buses, a versatile message buffer design providing 16 MB of memory, and the capability to extend the raw bandwidth of the network to 3.0 GHz.

Coverage-maximization in networks under resource constraints.

PubMed

Nandi, Subrata; Brusch, Lutz; Deutsch, Andreas; Ganguly, Niloy

2010-06-01

Efficient coverage algorithms are essential for information search or dispersal in all kinds of networks. We define an extended coverage problem which accounts for constrained resources of consumed bandwidth B and time T . Our solution to the network challenge is here studied for regular grids only. Using methods from statistical mechanics, we develop a coverage algorithm with proliferating message packets and temporally modulated proliferation rate. The algorithm performs as efficiently as a single random walker but O(B(d-2)/d) times faster, resulting in significant service speed-up on a regular grid of dimension d . The algorithm is numerically compared to a class of generalized proliferating random walk strategies and on regular grids shown to perform best in terms of the product metric of speed and efficiency.

Network-Based Professional Development: A Comparison of Statewide Initiatives.

ERIC Educational Resources Information Center

Shotsberger, Paul G.; Stammen, Ronald; Vetter, Ronald; Blue, Gloria; Greer, Edrie

This paper addresses opportunities and issues related to the use of the World Wide Web and high-speed networks as a delivery vehicle for training educators who are geographically dispersed. The benefits and potential pitfalls of using networks as educational platforms are explored from the perspective of various systems specifically being…

The Glenview Model: Community Networking via Broadband Cable.

ERIC Educational Resources Information Center

Mundt, John P.

This paper describes the installation of a data network in the community of Glenview, Illinois, which uses broadband cable equipment to connect schools, libraries, and governmental agencies to each other and to the Internet via a high speed Ethernet network. The history of the project is outlined followed by a discussion of the implementation of…

High Speed Computing, LANs, and WAMs

NASA Technical Reports Server (NTRS)

Bergman, Larry A.; Monacos, Steve

1994-01-01

Optical fiber networks may one day offer potential capacities exceeding 10 terabits/sec. This paper describes present gigabit network techniques for distributed computing as illustrated by the CASA gigabit testbed, and then explores future all-optic network architectures that offer increased capacity, more optimized level of service for a given application, high fault tolerance, and dynamic reconfigurability.

Network Design: Best Practices for Alberta School Jurisdictions.

ERIC Educational Resources Information Center

Schienbein, Ralph

This report examines subsections of the computer network topology that relate to end-to-end performance and capacity planning in schools. Active star topology, Category 5 wiring, Ethernet, and intelligent devices are assumed. The report describes a model that can be used to project WAN (wide area network) connection speeds based on user traffic,…

Receiver-Assisted Congestion Control to Achieve High Throughput in Lossy Wireless Networks

NASA Astrophysics Data System (ADS)

Shi, Kai; Shu, Yantai; Yang, Oliver; Luo, Jiarong

2010-04-01

Many applications would require fast data transfer in high-speed wireless networks nowadays. However, due to its conservative congestion control algorithm, Transmission Control Protocol (TCP) cannot effectively utilize the network capacity in lossy wireless networks. In this paper, we propose a receiver-assisted congestion control mechanism (RACC) in which the sender performs loss-based control, while the receiver is performing delay-based control. The receiver measures the network bandwidth based on the packet interarrival interval and uses it to compute a congestion window size deemed appropriate for the sender. After receiving the advertised value feedback from the receiver, the sender then uses the additive increase and multiplicative decrease (AIMD) mechanism to compute the correct congestion window size to be used. By integrating the loss-based and the delay-based congestion controls, our mechanism can mitigate the effect of wireless losses, alleviate the timeout effect, and therefore make better use of network bandwidth. Simulation and experiment results in various scenarios show that our mechanism can outperform conventional TCP in high-speed and lossy wireless environments.

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA.

PubMed

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints.

Neuromodulation and Synaptic Plasticity for the Control of Fast Periodic Movement: Energy Efficiency in Coupled Compliant Joints via PCA

PubMed Central

Stratmann, Philipp; Lakatos, Dominic; Albu-Schäffer, Alin

2016-01-01

There are multiple indications that the nervous system of animals tunes muscle output to exploit natural dynamics of the elastic locomotor system and the environment. This is an advantageous strategy especially in fast periodic movements, since the elastic elements store energy and increase energy efficiency and movement speed. Experimental evidence suggests that coordination among joints involves proprioceptive input and neuromodulatory influence originating in the brain stem. However, the neural strategies underlying the coordination of fast periodic movements remain poorly understood. Based on robotics control theory, we suggest that the nervous system implements a mechanism to accomplish coordination between joints by a linear coordinate transformation from the multi-dimensional space representing proprioceptive input at the joint level into a one-dimensional controller space. In this one-dimensional subspace, the movements of a whole limb can be driven by a single oscillating unit as simple as a reflex interneuron. The output of the oscillating unit is transformed back to joint space via the same transformation. The transformation weights correspond to the dominant principal component of the movement. In this study, we propose a biologically plausible neural network to exemplify that the central nervous system (CNS) may encode our controller design. Using theoretical considerations and computer simulations, we demonstrate that spike-timing-dependent plasticity (STDP) for the input mapping and serotonergic neuromodulation for the output mapping can extract the dominant principal component of sensory signals. Our simulations show that our network can reliably control mechanical systems of different complexity and increase the energy efficiency of ongoing cyclic movements. The proposed network is simple and consistent with previous biologic experiments. Thus, our controller could serve as a candidate to describe the neural control of fast, energy-efficient, periodic movements involving multiple coupled joints. PMID:27014051

(abstract) A High Throughput 3-D Inner Product Processor

NASA Technical Reports Server (NTRS)

Daud, Tuan

1996-01-01

A particularily challenging image processing application is the real time scene acquisition and object discrimination. It requires spatio-temporal recognition of point and resolved objects at high speeds with parallel processing algorithms. Neural network paradigms provide fine grain parallism and, when implemented in hardware, offer orders of magnitude speed up. However, neural networks implemented on a VLSI chip are planer architectures capable of efficient processing of linear vector signals rather than 2-D images. Therefore, for processing of images, a 3-D stack of neural-net ICs receiving planar inputs and consuming minimal power are required. Details of the circuits with chip architectures will be described with need to develop ultralow-power electronics. Further, use of the architecture in a system for high-speed processing will be illustrated.

Old Buildings Broadband Home Networks: Technologies and Services Overview

NASA Astrophysics Data System (ADS)

Fantacci, Romano; Pecorella, Tommaso; Micciullo, Luigia; Viti, Roberto; Pasquini, Vincenzo; Calì, Marco

2014-05-01

Internet broadband access is becoming a reality in many countries. To fully exploit the benefits from high-speed connection, both suitable home network connectivity and advanced services support have to be made available to the user. In this article, issues relative to the upgrade of existing home networks, particularly in old buildings, together with networking and security requirements are addressed, and possible solutions are proposed.

Low Loss Graded Index Polymer Optical Fiber for Local Networking

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

Claus, Richard Otto

The objective of this Department of Energy SBIR program has been to develop technology for the advancement of advanced computing systems. NanoSonic worked with two subcontractors, the Polymicro Division of Molex, a U.S.-based manufacturer of specialized optical fiber and fiber components, and Virginia Tech, a research university involved through the Global Environment for Network Innovations (GENI) program in high-speed computer networking research. NanoSonic developed a patented molecular-level self-assembly process to manufacture polymer-based optical fibers in a way similar to the modified chemical vapor deposition (MCVD) approach typically used to make glass optical fibers. Although polymer fiber has a higher attenuationmore » per unit length than glass fiber, short connectorized polymer fiber jumpers offer significant cost savings over their glass counterparts, particularly due to the potential use of low-cost plastic fiber connectors. As part of the SBIR commercialization process, NanoSonic exclusively licensed this technology to a large ($100B+ market cap) U.S.-based manufacturing conglomerate near the end of the first year of the Phase II program. With this base technology developed and licensed, NanoSonic then worked with Polymicro to address secondary program goals of using related but not conflicting production methods to enhance the performance of other specialty optical fiber products and components, and Virginia Tech continued its evaluation of developed polymer fibers in its network infrastructure system on the university campus. We also report our current understanding of the observation during the Phase I program of quantum conductance and partial quantum conductance in metal-insulator-metal (MIM) devices. Such conductance behavior may be modeled as singlemode behavior in one-dimensional electrically conducting waveguides, similar in principle to singlemode optical propagation in dielectric fiber waveguides. Although NanoSonic has not licensed any of the additional technology developed during the second year of the program, several proprietary discussions with major materials companies are underway as of the conclusion of Phase II.« less

Parallel network simulations with NEURON.

PubMed

Migliore, M; Cannia, C; Lytton, W W; Markram, Henry; Hines, M L

2006-10-01

The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2,000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored.

Parallel Network Simulations with NEURON

PubMed Central

Migliore, M.; Cannia, C.; Lytton, W.W; Markram, Henry; Hines, M. L.

2009-01-01

The NEURON simulation environment has been extended to support parallel network simulations. Each processor integrates the equations for its subnet over an interval equal to the minimum (interprocessor) presynaptic spike generation to postsynaptic spike delivery connection delay. The performance of three published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters and demonstrates that spike communication overhead is often less than the benefit of an increased fraction of the entire problem fitting into high speed cache. On the EPFL IBM Blue Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from 500 to 40,000 realistic cells exhibited almost linear speedup on 2000 processors, with an integration time of 9.8 seconds and communication time of 1.3 seconds. The potential for speed-ups of several orders of magnitude makes practical the running of large network simulations that could otherwise not be explored. PMID:16732488

A Software Suite for Testing SpaceWire Devices and Networks

NASA Astrophysics Data System (ADS)

Mills, Stuart; Parkes, Steve

2015-09-01

SpaceWire is a data-handling network for use on-board spacecraft, which connects together instruments, mass-memory, processors, downlink telemetry, and other on-board sub-systems. SpaceWire is simple to implement and has some specific characteristics that help it support data-handling applications in space: high-speed, low-power, simplicity, relatively low implementation cost, and architectural flexibility making it ideal for many space missions. SpaceWire provides high-speed (2 Mbits/s to 200 Mbits/s), bi-directional, full-duplex data-links, which connect together SpaceWire enabled equipment. Data-handling networks can be built to suit particular applications using point-to-point data-links and routing switches. STAR-Dundee’s STAR-System software stack has been designed to meet the needs of engineers designing and developing SpaceWire networks and devices. This paper describes the aims of the software and how those needs were met.

Variable speed limit strategies analysis with mesoscopic traffic flow model based on complex networks

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Cao, Dan-Ni; Dang, Wen-Xiu; Zhang, Lin

As a new cross-discipline, the complexity science has penetrated into every field of economy and society. With the arrival of big data, the research of the complexity science has reached its summit again. In recent years, it offers a new perspective for traffic control by using complex networks theory. The interaction course of various kinds of information in traffic system forms a huge complex system. A new mesoscopic traffic flow model is improved with variable speed limit (VSL), and the simulation process is designed, which is based on the complex networks theory combined with the proposed model. This paper studies effect of VSL on the dynamic traffic flow, and then analyzes the optimal control strategy of VSL in different network topologies. The conclusion of this research is meaningful to put forward some reasonable transportation plan and develop effective traffic management and control measures to help the department of traffic management.

Exact coupling threshold for structural transition reveals diversified behaviors in interconnected networks.

PubMed

Darabi Sahneh, Faryad; Scoglio, Caterina; Van Mieghem, Piet

2015-10-01

An interconnected network features a structural transition between two regimes [F. Radicchi and A. Arenas, Nat. Phys. 9, 717 (2013)]: one where the network components are structurally distinguishable and one where the interconnected network functions as a whole. Our exact solution for the coupling threshold uncovers network topologies with unexpected behaviors. Specifically, we show conditions that superdiffusion, introduced by Gómez et al. [Phys. Rev. Lett. 110, 028701 (2013)], can occur despite the network components functioning distinctly. Moreover, we find that components of certain interconnected network topologies are indistinguishable despite very weak coupling between them.

Gossip algorithms in quantum networks

NASA Astrophysics Data System (ADS)

Siomau, Michael

2017-01-01

Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up - in the best case exponentially - the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication.

Stochastic simulation of enzyme-catalyzed reactions with disparate timescales.

PubMed

Barik, Debashis; Paul, Mark R; Baumann, William T; Cao, Yang; Tyson, John J

2008-10-01

Many physiological characteristics of living cells are regulated by protein interaction networks. Because the total numbers of these protein species can be small, molecular noise can have significant effects on the dynamical properties of a regulatory network. Computing these stochastic effects is made difficult by the large timescale separations typical of protein interactions (e.g., complex formation may occur in fractions of a second, whereas catalytic conversions may take minutes). Exact stochastic simulation may be very inefficient under these circumstances, and methods for speeding up the simulation without sacrificing accuracy have been widely studied. We show that the "total quasi-steady-state approximation" for enzyme-catalyzed reactions provides a useful framework for efficient and accurate stochastic simulations. The method is applied to three examples: a simple enzyme-catalyzed reaction where enzyme and substrate have comparable abundances, a Goldbeter-Koshland switch, where a kinase and phosphatase regulate the phosphorylation state of a common substrate, and coupled Goldbeter-Koshland switches that exhibit bistability. Simulations based on the total quasi-steady-state approximation accurately capture the steady-state probability distributions of all components of these reaction networks. In many respects, the approximation also faithfully reproduces time-dependent aspects of the fluctuations. The method is accurate even under conditions of poor timescale separation.

Applying a cloud computing approach to storage architectures for spacecraft

NASA Astrophysics Data System (ADS)

Baldor, Sue A.; Quiroz, Carlos; Wood, Paul

As sensor technologies, processor speeds, and memory densities increase, spacecraft command, control, processing, and data storage systems have grown in complexity to take advantage of these improvements and expand the possible missions of spacecraft. Spacecraft systems engineers are increasingly looking for novel ways to address this growth in complexity and mitigate associated risks. Looking to conventional computing, many solutions have been executed to solve both the problem of complexity and heterogeneity in systems. In particular, the cloud-based paradigm provides a solution for distributing applications and storage capabilities across multiple platforms. In this paper, we propose utilizing a cloud-like architecture to provide a scalable mechanism for providing mass storage in spacecraft networks that can be reused on multiple spacecraft systems. By presenting a consistent interface to applications and devices that request data to be stored, complex systems designed by multiple organizations may be more readily integrated. Behind the abstraction, the cloud storage capability would manage wear-leveling, power consumption, and other attributes related to the physical memory devices, critical components in any mass storage solution for spacecraft. Our approach employs SpaceWire networks and SpaceWire-capable devices, although the concept could easily be extended to non-heterogeneous networks consisting of multiple spacecraft and potentially the ground segment.

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

Remote Observing with the Keck Telescope Using the ACTS Satellite

NASA Technical Reports Server (NTRS)

Cohen, Judy; Shopbell, Patrick; Bergman, Larry

1998-01-01

As a technical demonstration project for the NASA Advanced Communications Technology Satellite (ACTS), we have implemented remote observing on the 10-meter Keck II telescope on Mauna Kea in Hawaii from the California Institute of Technology campus in Pasadena. The data connection consists of optical fiber networks in Hawaii and California, connecting the end-points to high data rate (HDR) ACTS satellite antennae at JPL in Pasadena and at the Tripler Army Medical Center in Honolulu. The terrestrial fiber networks run the asynchronous transfer mode (ATM) protocol at DS-3 (45 Mbit/sec) speeds, providing ample bandwidth to enable remote observing with a software environment identical to that used for on-site observing in Hawaii. This experiment has explored the data requirements of remote observing with a modern research telescope and large-format detector arrays. While the maximum burst data rates are lower than those required for many other applications (e.g., HDTV), the network reliability and data integrity requirements are critical. As we show in this report, the former issue particularly may be the greatest challenge for satellite networks for this class of application. We have also experimented with the portability of standard TCP/IP applications to satellite networks, demonstrating the need for alternative TCP congestion algorithms and minimization of bit error rates (BER). Reliability issues aside, we have demonstrated that true remote observing over high-speed networks provides several important advantages over standard observing paradigms. Technical advantages of the high-speed network access include more rapid download of data to a user's home institution and the opportunity for alternative communication facilities between members of an observing team, such as audio- and videoconferencing.

Hip fracture in the elderly: a re-analysis of the EPIDOS study with causal Bayesian networks.

PubMed

Caillet, Pascal; Klemm, Sarah; Ducher, Michel; Aussem, Alexandre; Schott, Anne-Marie

2015-01-01

Hip fractures commonly result in permanent disability, institutionalization or death in elderly. Existing hip-fracture predicting tools are underused in clinical practice, partly due to their lack of intuitive interpretation. By use of a graphical layer, Bayesian network models could increase the attractiveness of fracture prediction tools. Our aim was to study the potential contribution of a causal Bayesian network in this clinical setting. A logistic regression was performed as a standard control approach to check the robustness of the causal Bayesian network approach. EPIDOS is a multicenter study, conducted in an ambulatory care setting in five French cities between 1992 and 1996 and updated in 2010. The study included 7598 women aged 75 years or older, in which fractures were assessed quarterly during 4 years. A causal Bayesian network and a logistic regression were performed on EPIDOS data to describe major variables involved in hip fractures occurrences. Both models had similar association estimations and predictive performances. They detected gait speed and mineral bone density as variables the most involved in the fracture process. The causal Bayesian network showed that gait speed and bone mineral density were directly connected to fracture and seem to mediate the influence of all the other variables included in our model. The logistic regression approach detected multiple interactions involving psychotropic drug use, age and bone mineral density. Both approaches retrieved similar variables as predictors of hip fractures. However, Bayesian network highlighted the whole web of relation between the variables involved in the analysis, suggesting a possible mechanism leading to hip fracture. According to the latter results, intervention focusing concomitantly on gait speed and bone mineral density may be necessary for an optimal prevention of hip fracture occurrence in elderly people.

Determination of combustion parameters using engine crankshaft speed

NASA Astrophysics Data System (ADS)

Taglialatela, F.; Lavorgna, M.; Mancaruso, E.; Vaglieco, B. M.

2013-07-01

Electronic engine controls based on real time diagnosis of combustion process can significantly help in complying with the stricter and stricter regulations on pollutants emissions and fuel consumption. The most important parameter for the evaluation of combustion quality in internal combustion engines is the in-cylinder pressure, but its direct measurement is very expensive and involves an intrusive approach to the cylinder. Previous researches demonstrated the direct relationship existing between in-cylinder pressure and engine crankshaft speed and several authors tried to reconstruct the pressure cycle on the basis of the engine speed signal. In this paper we propose the use of a Multi-Layer Perceptron neural network to model the relationship between the engine crankshaft speed and some parameters derived from the in-cylinder pressure cycle. This allows to have a non-intrusive estimation of cylinder pressure and a real time evaluation of combustion quality. The structure of the model and the training procedure is outlined in the paper. A possible combustion controller using the information extracted from the crankshaft speed information is also proposed. The application of the neural network model is demonstrated on a single-cylinder spark ignition engine tested in a wide range of speeds and loads. Results confirm that a good estimation of some combustion pressure parameters can be obtained by means of a suitable processing of crankshaft speed signal.

Revealing the microstructure of the giant component in random graph ensembles

NASA Astrophysics Data System (ADS)

Tishby, Ido; Biham, Ofer; Katzav, Eytan; Kühn, Reimer

2018-04-01

The microstructure of the giant component of the Erdős-Rényi network and other configuration model networks is analyzed using generating function methods. While configuration model networks are uncorrelated, the giant component exhibits a degree distribution which is different from the overall degree distribution of the network and includes degree-degree correlations of all orders. We present exact analytical results for the degree distributions as well as higher-order degree-degree correlations on the giant components of configuration model networks. We show that the degree-degree correlations are essential for the integrity of the giant component, in the sense that the degree distribution alone cannot guarantee that it will consist of a single connected component. To demonstrate the importance and broad applicability of these results, we apply them to the study of the distribution of shortest path lengths on the giant component, percolation on the giant component, and spectra of sparse matrices defined on the giant component. We show that by using the degree distribution on the giant component one obtains high quality results for these properties, which can be further improved by taking the degree-degree correlations into account. This suggests that many existing methods, currently used for the analysis of the whole network, can be adapted in a straightforward fashion to yield results conditioned on the giant component.

High-Speed Rail and Local Land Development : Case Studies in London and Las Vegas

DOT National Transportation Integrated Search

2017-11-01

The efficacy of a high-speed rail system depends, in part, upon locating rail stations close to urban centers and integrating them into broader transportation networks and the urban realm. In addition, through economies of agglomeration, successful h...

Solid-state switch increases switching speed

NASA Technical Reports Server (NTRS)

Mcgowan, G. F.

1966-01-01

Solid state switch for commutating capacitors in an RC commutated network increases switching speed and extends the filtering or commutating frequency spectrum well into the kilocycle region. The switch is equivalent to the standard double- pole double-throw /DPDT/ relay and is driven from digital micrologic circuits.

Joint Geodetic and Seismic Analysis of the effects of Englacial and Subglacial Hydraulics on Surface Crevassing near a Seasonal, Glacier-Dammed Lake on Gornergletscher, Switzerland

NASA Astrophysics Data System (ADS)

Garcia, L.; Luttrell, K. M.; Kilb, D. L.; Walter, F.

2017-12-01

Glacial outburst floods are difficult to predict and threaten human life and property near glaciated regions. These events are characterized by rapid draining of glacier-dammed lakes via the sub/englacial hydraulic network to the proglacial stream. The glacier-dammed lake on Gornergletscher in Switzerland, which fills and drains each summer, provides an opportunity to study this hazard. For three drainages (2004, 2006, and 2007), we track icequakes (IQ) and on-ice GPS movement. Our seasonal seismic networks had 8 - 24 three component stations and apertures of about 300 - 400 m on the glacier surface. The seasonal GPS arrays contained 4 - 8 GPS antennae on the glacier surface. Using Rayleigh wave coherence surface IQ location, we located 2924, 7822 and 3782 IQs, in 2004, 2006 and 2007, respectively. The GPS data were smoothed using a nonparametric protocol, with average station velocities of 10 - 90 mm/day. In 2006, strains were calculated using five stations within 500 m of the lake, co-located with the seismic network. IQ productivity increased substantially during lake drainage only in 2004, which was the only year when the lake drainage was rapid ( 6 days) and primarily subglacial. In 2006, there was no obvious increase in GPS speeds with slow ( 21 days), supraglacial lake drainage. However, when drainage was subglacial as in 2004 and 2007 (sub/englacial over 11 days), GPS speed increased up to 160%. This speed increase is evidence for basal sliding induced by subglacial drainage. In general, we find that when the strain increase on the principle extension axis aligns with the crevasse opening direction, IQ are more prolific. We also observe a diurnal signal in both IQ occurrence and surface strain, with peak strain occurring in the mid- to late-afternoon (15:00 - 19:00 local) across the study area in 2006. We interpret this time-shift in strain and spatiotemporal dependence of IQs to be caused by diurnal variations in melt-induced sliding. Our analysis sheds light on crevasse formation on short time scales where glacier flow is controlled by sliding variations in response to water input into the subglacial drainage system. Coupled seismic and GPS monitoring can thus make a key contribution to our understanding of brittle deformation and crevassing of glacier ice.

The prestimulus default mode network state predicts cognitive task performance levels on a mental rotation task.

PubMed

Kamp, Tabea; Sorger, Bettina; Benjamins, Caroline; Hausfeld, Lars; Goebel, Rainer

2018-06-22

Linking individual task performance to preceding, regional brain activation is an ongoing goal of neuroscientific research. Recently, it could be shown that the activation and connectivity within large-scale brain networks prior to task onset influence performance levels. More specifically, prestimulus default mode network (DMN) effects have been linked to performance levels in sensory near-threshold tasks, as well as cognitive tasks. However, it still remains uncertain how the DMN state preceding cognitive tasks affects performance levels when the period between task trials is long and flexible, allowing participants to engage in different cognitive states. We here investigated whether the prestimulus activation and within-network connectivity of the DMN are predictive of the correctness and speed of task performance levels on a cognitive (match-to-sample) mental rotation task, employing a sparse event-related functional magnetic resonance imaging (fMRI) design. We found that prestimulus activation in the DMN predicted the speed of correct trials, with a higher amplitude preceding correct fast response trials compared to correct slow response trials. Moreover, we found higher connectivity within the DMN before incorrect trials compared to correct trials. These results indicate that pre-existing activation and connectivity states within the DMN influence task performance on cognitive tasks, both effecting the correctness and speed of task execution. The findings support existing theories and empirical work on relating mind-wandering and cognitive task performance to the DMN and expand these by establishing a relationship between the prestimulus DMN state and the speed of cognitive task performance. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

a Linux PC Cluster for Lattice QCD with Exact Chiral Symmetry

NASA Astrophysics Data System (ADS)

Chiu, Ting-Wai; Hsieh, Tung-Han; Huang, Chao-Hsi; Huang, Tsung-Ren

A computational system for lattice QCD with overlap Dirac quarks is described. The platform is a home-made Linux PC cluster, built with off-the-shelf components. At present the system constitutes of 64 nodes, with each node consisting of one Pentium 4 processor (1.6/2.0/2.5 GHz), one Gbyte of PC800/1066 RDRAM, one 40/80/120 Gbyte hard disk, and a network card. The computationally intensive parts of our program are written in SSE2 codes. The speed of our system is estimated to be 70 Gflops, and its price/performance ratio is better than $1.0/Mflops for 64-bit (double precision) computations in quenched QCD. We discuss how to optimize its hardware and software for computing propagators of overlap Dirac quarks.

Ge-Photodetectors for Si-Based Optoelectronic Integration

PubMed Central

Wang, Jian; Lee, Sungjoo

2011-01-01

High speed photodetectors are a key building block, which allow a large wavelength range of detection from 850 nm to telecommunication standards at optical fiber band passes of 1.3–1.55 μm. Such devices are key components in several applications such as local area networks, board to board, chip to chip and intrachip interconnects. Recent technological achievements in growth of high quality SiGe/Ge films on Si wafers have opened up the possibility of low cost Ge-based photodetectors for near infrared communication bands and high resolution spectral imaging with high quantum efficiencies. In this review article, the recent progress in the development and integration of Ge-photodetectors on Si-based photonics will be comprehensively reviewed, along with remaining technological issues to be overcome and future research trends. PMID:22346598

Comparison of Communication Architectures and Network Topologies for Distributed Propulsion Controls (Preprint)

DTIC Science & Technology

2013-05-01

logic to perform control function computations and are connected to the full authority digital engine control ( FADEC ) via a high-speed data...Digital Engine Control ( FADEC ) via a high speed data communication bus. The short term distributed engine control configu- rations will be core...concen- trator; and high temperature electronics, high speed communication bus between the data concentrator and the control law processor master FADEC

A System And Method To Determine Thermophysical Properties Of A Multi-Component Gas At Arbitrary Temperature And Pressure

DOEpatents

Morrow, Thomas E.; Behring, II, Kendricks A.

2004-03-09

A method to determine thermodynamic properties of a natural gas hydrocarbon, when the speed of sound in the gas is known at an arbitrary temperature and pressure. Thus, the known parameters are the sound speed, temperature, pressure, and concentrations of any dilute components of the gas. The method uses a set of reference gases and their calculated density and speed of sound values to estimate the density of the subject gas. Additional calculations can be made to estimate the molecular weight of the subject gas, which can then be used as the basis for mass flow calculations, to determine the speed of sound at standard pressure and temperature, and to determine various thermophysical characteristics of the gas.

Device For Determining Therophysical Properties Of A Multi-Component Gas At Arbitrary Temperature And Pressure

DOEpatents

Morrow, Thomas B.; Behring, II, Kendricks A.

2005-02-01

A computer product for determining thermodynamic properties of a natural gas hydrocarbon, when the speed of sound in the gas is known at an arbitrary temperature and pressure. Thus, the known parameters are the sound speed, temperature, pressure, and concentrations of any dilute components of the gas. The method uses a set of reference gases and their calculated density and speed of sound values to estimate the density of the subject gas. Additional calculations can be made to estimate the molecular weight of the subject gas, which can then be used as the basis for mass flow calculations, to determine the speed of sound at standard pressure and temperature, and to determine various thermophysical characteristics of the gas.

LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

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

Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.

Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less

The spinal control of locomotion and step-to-step variability in left-right symmetry from slow to moderate speeds

PubMed Central

Dambreville, Charline; Labarre, Audrey; Thibaudier, Yann; Hurteau, Marie-France

2015-01-01

When speed changes during locomotion, both temporal and spatial parameters of the pattern must adjust. Moreover, at slow speeds the step-to-step pattern becomes increasingly variable. The objectives of the present study were to assess if the spinal locomotor network adjusts both temporal and spatial parameters from slow to moderate stepping speeds and to determine if it contributes to step-to-step variability in left-right symmetry observed at slow speeds. To determine the role of the spinal locomotor network, the spinal cord of 6 adult cats was transected (spinalized) at low thoracic levels and the cats were trained to recover hindlimb locomotion. Cats were implanted with electrodes to chronically record electromyography (EMG) in several hindlimb muscles. Experiments began once a stable hindlimb locomotor pattern emerged. During experiments, EMG and bilateral video recordings were made during treadmill locomotion from 0.1 to 0.4 m/s in 0.05 m/s increments. Cycle and stance durations significantly decreased with increasing speed, whereas swing duration remained unaffected. Extensor burst duration significantly decreased with increasing speed, whereas sartorius burst duration remained unchanged. Stride length, step length, and the relative distance of the paw at stance offset significantly increased with increasing speed, whereas the relative distance at stance onset and both the temporal and spatial phasing between hindlimbs were unaffected. Both temporal and spatial step-to-step left-right asymmetry decreased with increasing speed. Therefore, the spinal cord is capable of adjusting both temporal and spatial parameters during treadmill locomotion, and it is responsible, at least in part, for the step-to-step variability in left-right symmetry observed at slow speeds. PMID:26084910

Progress in neuromorphic photonics

NASA Astrophysics Data System (ADS)

Ferreira de Lima, Thomas; Shastri, Bhavin J.; Tait, Alexander N.; Nahmias, Mitchell A.; Prucnal, Paul R.

2017-03-01

As society's appetite for information continues to grow, so does our need to process this information with increasing speed and versatility. Many believe that the one-size-fits-all solution of digital electronics is becoming a limiting factor in certain areas such as data links, cognitive radio, and ultrafast control. Analog photonic devices have found relatively simple signal processing niches where electronics can no longer provide sufficient speed and reconfigurability. Recently, the landscape for commercially manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. By bridging the mathematical prowess of artificial neural networks to the underlying physics of optoelectronic devices, neuromorphic photonics could breach new domains of information processing demanding significant complexity, low cost, and unmatched speed. In this article, we review the progress in neuromorphic photonics, focusing on photonic integrated devices. The challenges and design rules for optoelectronic instantiation of artificial neurons are presented. The proposed photonic architecture revolves around the processing network node composed of two parts: a nonlinear element and a network interface. We then survey excitable lasers in the recent literature as candidates for the nonlinear node and microring-resonator weight banks as the network interface. Finally, we compare metrics between neuromorphic electronics and neuromorphic photonics and discuss potential applications.

Pavement Structural Evaluation at the Network Level [Tech Brief

DOT National Transportation Integrated Search

2016-03-01

This document is a technical summary of the Federal Highway Administration (FHWA) report, Pavement Structural Evaluation at the Network Level (FHWA-HRT-15-074). It addresses the use of traffic speed deflection devices for the structural evaluation of...

GLOBECOM '92 - IEEE Global Telecommunications Conference, Orlando, FL, Dec. 6-9, 1992, Conference Record. Vols. 1-3

NASA Astrophysics Data System (ADS)

Papers are presented on such topics as the wireless data network in PCS, advances in digital mobile networks, ATM switching experiments, broadband applications, network planning, and advances in SONET/SDH implementations. Consideration is also given to gigabit computer networks, techniques for modeling large high-speed networks, coding and modulation, the next-generation lightwave system, signaling systems for broadband ISDN, satellite technologies, and advances in standardization of low-rate signal processing.

Local network assessment

NASA Astrophysics Data System (ADS)

Glen, D. V.

1985-04-01

Local networks, related standards activities of the Institute of Electrical and Electronics Engineers the American National Standards Institute and other elements are presented. These elements include: (1) technology choices such as topology, transmission media, and access protocols; (2) descriptions of standards for the 802 local area networks (LAN's); high speed local networks (HSLN's) and military specification local networks; and (3) intra- and internetworking using bridges and gateways with protocols Interconnection (OSI) reference model. The convergence of LAN/PBX technology is also described.

Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants.

PubMed

Walters, D M; Stringer, S M

2010-07-01

A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

Statistical Mechanical Analysis of Online Learning with Weight Normalization in Single Layer Perceptron

NASA Astrophysics Data System (ADS)

Yoshida, Yuki; Karakida, Ryo; Okada, Masato; Amari, Shun-ichi

2017-04-01

Weight normalization, a newly proposed optimization method for neural networks by Salimans and Kingma (2016), decomposes the weight vector of a neural network into a radial length and a direction vector, and the decomposed parameters follow their steepest descent update. They reported that learning with the weight normalization achieves better converging speed in several tasks including image recognition and reinforcement learning than learning with the conventional parameterization. However, it remains theoretically uncovered how the weight normalization improves the converging speed. In this study, we applied a statistical mechanical technique to analyze on-line learning in single layer linear and nonlinear perceptrons with weight normalization. By deriving order parameters of the learning dynamics, we confirmed quantitatively that weight normalization realizes fast converging speed by automatically tuning the effective learning rate, regardless of the nonlinearity of the neural network. This property is realized when the initial value of the radial length is near the global minimum; therefore, our theory suggests that it is important to choose the initial value of the radial length appropriately when using weight normalization.

Arctic Boreal Vulnerability Experiment (ABoVE) Science Cloud

NASA Astrophysics Data System (ADS)

Duffy, D.; Schnase, J. L.; McInerney, M.; Webster, W. P.; Sinno, S.; Thompson, J. H.; Griffith, P. C.; Hoy, E.; Carroll, M.

2014-12-01

The effects of climate change are being revealed at alarming rates in the Arctic and Boreal regions of the planet. NASA's Terrestrial Ecology Program has launched a major field campaign to study these effects over the next 5 to 8 years. The Arctic Boreal Vulnerability Experiment (ABoVE) will challenge scientists to take measurements in the field, study remote observations, and even run models to better understand the impacts of a rapidly changing climate for areas of Alaska and western Canada. The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center (GSFC) has partnered with the Terrestrial Ecology Program to create a science cloud designed for this field campaign - the ABoVE Science Cloud. The cloud combines traditional high performance computing with emerging technologies to create an environment specifically designed for large-scale climate analytics. The ABoVE Science Cloud utilizes (1) virtualized high-speed InfiniBand networks, (2) a combination of high-performance file systems and object storage, and (3) virtual system environments tailored for data intensive, science applications. At the center of the architecture is a large object storage environment, much like a traditional high-performance file system, that supports data proximal processing using technologies like MapReduce on a Hadoop Distributed File System (HDFS). Surrounding the storage is a cloud of high performance compute resources with many processing cores and large memory coupled to the storage through an InfiniBand network. Virtual systems can be tailored to a specific scientist and provisioned on the compute resources with extremely high-speed network connectivity to the storage and to other virtual systems. In this talk, we will present the architectural components of the science cloud and examples of how it is being used to meet the needs of the ABoVE campaign. In our experience, the science cloud approach significantly lowers the barriers and risks to organizations that require high performance computing solutions and provides the NCCS with the agility required to meet our customers' rapidly increasing and evolving requirements.

Can anti-speeding messages based on protection motivation theory influence reported speeding intentions?

PubMed

Glendon, A Ian; Walker, Britta L

2013-08-01

The study investigated the effects of anti-speeding messages based on protection motivation theory (PMT) components: severity, vulnerability, rewards, self-efficacy, response efficacy, and response cost, on reported speeding intentions. Eighty-three participants aged 18-25 years holding a current Australian driver's license completed a questionnaire measuring their reported typical and recent speeding behaviors. Comparisons were made between 18 anti-speeding messages used on Australian roads and 18 new anti-speeding messages developed from the PMT model. Participants reported their reactions to the 36 messages on the perceived effectiveness of the message for themselves and for the general population of drivers, and also the likelihood of themselves and other drivers driving within the speed limit after viewing each message. Overall the PMT model-derived anti-speeding messages were better than jurisdiction-use anti-speeding messages in influencing participants' reported intention to drive within the speed limit. Severity and vulnerability were the most effective PMT components for developing anti-speeding messages. Male participants reported significantly lower intention to drive within the speed limit than did female participants. However, males reported significantly higher intention to drive within the speed limit for PMT-derived messages compared with jurisdiction-based messages. Third-person effects were that males reported anti-speeding messages to be more effective for the general driving population than for themselves. Females reported the opposite effect - that all messages would be more effective for themselves than for the general driving population. Findings provided support for using a sound conceptual basis as an effective foundation for anti-speeding message development as well as for evaluating proposed anti-speeding messages on the target driver population. Copyright © 2013 Elsevier Ltd. All rights reserved.

Eradicating catastrophic collapse in interdependent networks via reinforced nodes

PubMed Central

Yuan, Xin; Hu, Yanqing; Havlin, Shlomo

2017-01-01

In interdependent networks, it is usually assumed, based on percolation theory, that nodes become nonfunctional if they lose connection to the network giant component. However, in reality, some nodes, equipped with alternative resources, together with their connected neighbors can still be functioning after disconnected from the giant component. Here, we propose and study a generalized percolation model that introduces a fraction of reinforced nodes in the interdependent networks that can function and support their neighborhood. We analyze, both analytically and via simulations, the order parameter—the functioning component—comprising both the giant component and smaller components that include at least one reinforced node. Remarkably, it is found that, for interdependent networks, we need to reinforce only a small fraction of nodes to prevent abrupt catastrophic collapses. Moreover, we find that the universal upper bound of this fraction is 0.1756 for two interdependent Erdős–Rényi (ER) networks: regular random (RR) networks and scale-free (SF) networks with large average degrees. We also generalize our theory to interdependent networks of networks (NONs). These findings might yield insight for designing resilient interdependent infrastructure networks. PMID:28289204

Incorporating high speed passenger rail into a multimodal network model for improved regional transportation planning.

DOT National Transportation Integrated Search

2014-05-01

With increasing demand and rising fuel costs, both travel time and cost of intercity passenger : transportation are becoming increasingly significant. Around the world, high-speed rail (HSR) is seen as a : way to mitigate the risk of volatile petrole...

Independent verification and validation report of Washington state ferries' wireless high speed data project

DOT National Transportation Integrated Search

2008-06-30

The following Independent Verification and Validation (IV&V) report documents and presents the results of a study of the Washington State Ferries Prototype Wireless High Speed Data Network. The purpose of the study was to evaluate and determine if re...

Repressing the effects of variable speed harmonic orders in operational modal analysis

NASA Astrophysics Data System (ADS)

Randall, R. B.; Coats, M. D.; Smith, W. A.

2016-10-01

Discrete frequency components such as machine shaft orders can disrupt the operation of normal Operational Modal Analysis (OMA) algorithms. With constant speed machines, they have been removed using time synchronous averaging (TSA). This paper compares two approaches for varying speed machines. In one method, signals are transformed into the order domain, and after the removal of shaft speed related components by a cepstral notching method, are transformed back to the time domain to allow normal OMA. In the other simpler approach an exponential shortpass lifter is applied directly in the time domain cepstrum to enhance the modal information at the expense of other disturbances. For simulated gear signals with speed variations of both ±5% and ±15%, the simpler approach was found to give better results The TSA method is shown not to work in either case. The paper compares the results with those obtained using a stationary random excitation.

Does silent reading speed in normal adult readers depend on early visual processes? evidence from event-related brain potentials.

PubMed

Korinth, Sebastian Peter; Sommer, Werner; Breznitz, Zvia

2012-01-01

Little is known about the relationship of reading speed and early visual processes in normal readers. Here we examined the association of the early P1, N170 and late N1 component in visual event-related potentials (ERPs) with silent reading speed and a number of additional cognitive skills in a sample of 52 adult German readers utilizing a Lexical Decision Task (LDT) and a Face Decision Task (FDT). Amplitudes of the N170 component in the LDT but, interestingly, also in the FDT correlated with behavioral tests measuring silent reading speed. We suggest that reading speed performance can be at least partially accounted for by the extraction of essential structural information from visual stimuli, consisting of a domain-general and a domain-specific expertise-based portion. © 2011 Elsevier Inc. All rights reserved.

Wireless Local Area Network Performance Inside Aircraft Passenger Cabins

NASA Technical Reports Server (NTRS)

Whetten, Frank L.; Soroker, Andrew; Whetten, Dennis A.; Whetten, Frank L.; Beggs, John H.

2005-01-01

An examination of IEEE 802.11 wireless network performance within an aircraft fuselage is performed. This examination measured the propagated RF power along the length of the fuselage, and the associated network performance: the link speed, total throughput, and packet losses and errors. A total of four airplanes: one single-aisle and three twin-aisle airplanes were tested with 802.11a, 802.11b, and 802.11g networks.

Keypoint Density-Based Region Proposal for Fine-Grained Object Detection and Classification Using Regions with Convolutional Neural Network Features

DTIC Science & Technology

2015-12-15

Keypoint Density-based Region Proposal for Fine-Grained Object Detection and Classification using Regions with Convolutional Neural Network ... Convolutional Neural Networks (CNNs) enable them to outperform conventional techniques on standard object detection and classification tasks, their...detection accuracy and speed on the fine-grained Caltech UCSD bird dataset (Wah et al., 2011). Recently, Convolutional Neural Networks (CNNs), a deep

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

Application of Fuzzy-Logic Controller and Neural Networks Controller in Gas Turbine Speed Control and Overheating Control and Surge Control on Transient Performance

NASA Astrophysics Data System (ADS)

Torghabeh, A. A.; Tousi, A. M.

2007-08-01

This paper presents Fuzzy Logic and Neural Networks approach to Gas Turbine Fuel schedules. Modeling of non-linear system using feed forward artificial Neural Networks using data generated by a simulated gas turbine program is introduced. Two artificial Neural Networks are used , depicting the non-linear relationship between gas generator speed and fuel flow, and turbine inlet temperature and fuel flow respectively . Off-line fast simulations are used for engine controller design for turbojet engine based on repeated simulation. The Mamdani and Sugeno models are used to expression the Fuzzy system . The linguistic Fuzzy rules and membership functions are presents and a Fuzzy controller will be proposed to provide an Open-Loop control for the gas turbine engine during acceleration and deceleration . MATLAB Simulink was used to apply the Fuzzy Logic and Neural Networks analysis. Both systems were able to approximate functions characterizing the acceleration and deceleration schedules . Surge and Flame-out avoidance during acceleration and deceleration phases are then checked . Turbine Inlet Temperature also checked and controls by Neural Networks controller. This Fuzzy Logic and Neural Network Controllers output results are validated and evaluated by GSP software . The validation results are used to evaluate the generalization ability of these artificial Neural Networks and Fuzzy Logic controllers.

Mechanics of a two-fiber model with one nested fiber network, as applied to the collagen-fibrin system.

PubMed

Nedrelow, David S; Bankwala, Danesh; Hyypio, Jeffrey D; Lai, Victor K; Barocas, Victor H

2018-05-01

The mechanical behavior of collagen-fibrin (col-fib) co-gels is both scientifically interesting and clinically relevant. Collagen-fibrin networks are a staple of tissue engineering research, but the mechanical consequences of changes in co-gel composition have remained difficult to predict or even explain. We previously observed fundamental differences in failure behavior between collagen-rich and fibrin-rich co-gels, suggesting an essential change in how the two components interact as the co-gel's composition changes. In this work, we explored the hypothesis that the co-gel behavior is due to a lack of percolation by the dilute component. We generated a series of computational models based on interpenetrating fiber networks. In these models, the major network component percolated the model space but the minor component did not, instead occupying a small island embedded within the larger network. Each component was assigned properties based on a fit of single-component gel data. Island size was varied to match the relative concentrations of the two components. The model predicted that networks rich in collagen, the stiffer component, would roughly match pure-collagen gel behavior with little additional stress due to the fibrin, as seen experimentally. For fibrin-rich gels, however, the model predicted a smooth increase in the overall network strength with added collagen, as seen experimentally but not consistent with an additive parallel model. We thus conclude that incomplete percolation by the low-concentration component of a co-gel is a major determinant of its macroscopic properties, especially if the low-concentration component is the stiffer component. Models for the behavior of fibrous networks have useful applications in many different fields, including polymer science, textiles, and tissue engineering. In addition to being important structural components in soft tissues and blood clots, these protein networks can serve as scaffolds for bioartificial tissues. Thus, their mechanical behavior, especially in co-gels, is both interesting from a materials science standpoint and significant with regard to tissue engineering. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Program Helps Simulate Neural Networks

NASA Technical Reports Server (NTRS)

Villarreal, James; Mcintire, Gary

1993-01-01

Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

Modified neural networks for rapid recovery of tokamak plasma parameters for real time control

NASA Astrophysics Data System (ADS)

Sengupta, A.; Ranjan, P.

2002-07-01

Two modified neural network techniques are used for the identification of the equilibrium plasma parameters of the Superconducting Steady State Tokamak I from external magnetic measurements. This is expected to ultimately assist in a real time plasma control. As different from the conventional network structure where a single network with the optimum number of processing elements calculates the outputs, a multinetwork system connected in parallel does the calculations here in one of the methods. This network is called the double neural network. The accuracy of the recovered parameters is clearly more than the conventional network. The other type of neural network used here is based on the statistical function parametrization combined with a neural network. The principal component transformation removes linear dependences from the measurements and a dimensional reduction process reduces the dimensionality of the input space. This reduced and transformed input set, rather than the entire set, is fed into the neural network input. This is known as the principal component transformation-based neural network. The accuracy of the recovered parameters in the latter type of modified network is found to be a further improvement over the accuracy of the double neural network. This result differs from that obtained in an earlier work where the double neural network showed better performance. The conventional network and the function parametrization methods have also been used for comparison. The conventional network has been used for an optimization of the set of magnetic diagnostics. The effective set of sensors, as assessed by this network, are compared with the principal component based network. Fault tolerance of the neural networks has been tested. The double neural network showed the maximum resistance to faults in the diagnostics, while the principal component based network performed poorly. Finally the processing times of the methods have been compared. The double network and the principal component network involve the minimum computation time, although the conventional network also performs well enough to be used in real time.

Applications considerations in the system design of highly concurrent multiprocessors

NASA Technical Reports Server (NTRS)

Lundstrom, Stephen F.

1987-01-01

A flow model processor approach to parallel processing is described, using very-high-performance individual processors, high-speed circuit switched interconnection networks, and a high-speed synchronization capability to minimize the effect of the inherently serial portions of applications on performance. Design studies related to the determination of the number of processors, the memory organization, and the structure of the networks used to interconnect the processor and memory resources are discussed. Simulations indicate that applications centered on the large shared data memory should be able to sustain over 500 million floating point operations per second.

Real-Time Aircraft Engine-Life Monitoring

NASA Technical Reports Server (NTRS)

Klein, Richard

2014-01-01

This project developed an inservice life-monitoring system capable of predicting the remaining component and system life of aircraft engines. The embedded system provides real-time, inflight monitoring of the engine's thrust, exhaust gas temperature, efficiency, and the speed and time of operation. Based upon this data, the life-estimation algorithm calculates the remaining life of the engine components and uses this data to predict the remaining life of the engine. The calculations are based on the statistical life distribution of the engine components and their relationship to load, speed, temperature, and time.

High speed data transmission coaxial-cable in the space communication system

NASA Astrophysics Data System (ADS)

Su, Haohang; Huang, Jing

2018-01-01

An effective method is proved based on the scattering parameter of high speed 8-core coaxial-cable measured by vector network analyzer, and the semi-physical simulation is made to receive the eye diagram at different data transmission rate. The result can be apply to analysis decay and distortion of the signal through the coaxial-cable at high frequency, and can extensively design for electromagnetic compatibility of high-speed data transmission system.

Traveler oriented traffic performance metrics using real time traffic data from the Midtown-in-Motion (MIM) project in Manhattan, NY.

DOT National Transportation Integrated Search

2013-10-01

In a congested urban street network the average traffic speed is an inadequate metric for measuring : speed changes that drivers can perceive from changes in traffic control strategies. : A driver oriented metric is needed. Stop frequency distrib...

78 FR 18531 - Airworthiness Directives; Learjet Inc. Airplanes

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-27

... cause damage to various components, including the MLG squat switches, brake hydraulic tubes, wheel speed... airplanes. This proposed AD was prompted by a report of a high-speed rejected takeoff caused by all four... necessary; and, for certain airplanes; installing a new wheel speed detect box assembly, nutplates, and...

Network Dynamics Underlying Speed-Accuracy Trade-Offs in Response to Errors

PubMed Central

Agam, Yigal; Carey, Caitlin; Barton, Jason J. S.; Dyckman, Kara A.; Lee, Adrian K. C.; Vangel, Mark; Manoach, Dara S.

2013-01-01

The ability to dynamically and rapidly adjust task performance based on its outcome is fundamental to adaptive, flexible behavior. Over trials of a task, responses speed up until an error is committed and after the error responses slow down. These dynamic adjustments serve to optimize performance and are well-described by the speed-accuracy trade-off (SATO) function. We hypothesized that SATOs based on outcomes reflect reciprocal changes in the allocation of attention between the internal milieu and the task-at-hand, as indexed by reciprocal changes in activity between the default and dorsal attention brain networks. We tested this hypothesis using functional MRI to examine the pattern of network activation over a series of trials surrounding and including an error. We further hypothesized that these reciprocal changes in network activity are coordinated by the posterior cingulate cortex (PCC) and would rely on the structural integrity of its white matter connections. Using diffusion tensor imaging, we examined whether fractional anisotropy of the posterior cingulum bundle correlated with the magnitude of reciprocal changes in network activation around errors. As expected, reaction time (RT) in trials surrounding errors was consistent with predictions from the SATO function. Activation in the default network was: (i) inversely correlated with RT, (ii) greater on trials before than after an error and (iii) maximal at the error. In contrast, activation in the right intraparietal sulcus of the dorsal attention network was (i) positively correlated with RT and showed the opposite pattern: (ii) less activation before than after an error and (iii) the least activation on the error. Greater integrity of the posterior cingulum bundle was associated with greater reciprocity in network activation around errors. These findings suggest that dynamic changes in attention to the internal versus external milieu in response to errors underlie SATOs in RT and are mediated by the PCC. PMID:24069223

High-Speed Real-Time Resting-State fMRI Using Multi-Slab Echo-Volumar Imaging

PubMed Central

Posse, Stefan; Ackley, Elena; Mutihac, Radu; Zhang, Tongsheng; Hummatov, Ruslan; Akhtari, Massoud; Chohan, Muhammad; Fisch, Bruce; Yonas, Howard

2013-01-01

We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting-state networks (RSNs) compared to echo-planar imaging (Posse et al., 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arterio-venous malformations, and detection of abnormal resting-state connectivity in epilepsy. In patients with motor impairment, resting-state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arterio-venous malformations and a trend toward reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting-state connectivity and cerebro-vascular pulsatility for clinical and neuroscience research applications. PMID:23986677

FPGA implementation of a biological neural network based on the Hodgkin-Huxley neuron model.

PubMed

Yaghini Bonabi, Safa; Asgharian, Hassan; Safari, Saeed; Nili Ahmadabadi, Majid

2014-01-01

A set of techniques for efficient implementation of Hodgkin-Huxley-based (H-H) model of a neural network on FPGA (Field Programmable Gate Array) is presented. The central implementation challenge is H-H model complexity that puts limits on the network size and on the execution speed. However, basics of the original model cannot be compromised when effect of synaptic specifications on the network behavior is the subject of study. To solve the problem, we used computational techniques such as CORDIC (Coordinate Rotation Digital Computer) algorithm and step-by-step integration in the implementation of arithmetic circuits. In addition, we employed different techniques such as sharing resources to preserve the details of model as well as increasing the network size in addition to keeping the network execution speed close to real time while having high precision. Implementation of a two mini-columns network with 120/30 excitatory/inhibitory neurons is provided to investigate the characteristic of our method in practice. The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological mechanisms, like voltage-gated channels and synaptic activities, on the behavior of a neural network in an appropriate execution time. Additional to inherent properties of FPGA, like parallelism and re-configurability, our approach makes the FPGA-based system a proper candidate for study on neural control of cognitive robots and systems as well.

Identifying apple surface defects using principal components analysis and artifical neural networks

USDA-ARS?s Scientific Manuscript database

Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components derived from columns of pixels from images of apples acquired at two wavelengths (740 nm and 950 nm). I...

A weighted information criterion for multiple minor components and its adaptive extraction algorithms.

PubMed

Gao, Yingbin; Kong, Xiangyu; Zhang, Huihui; Hou, Li'an

2017-05-01

Minor component (MC) plays an important role in signal processing and data analysis, so it is a valuable work to develop MC extraction algorithms. Based on the concepts of weighted subspace and optimum theory, a weighted information criterion is proposed for searching the optimum solution of a linear neural network. This information criterion exhibits a unique global minimum attained if and only if the state matrix is composed of the desired MCs of an autocorrelation matrix of an input signal. By using gradient ascent method and recursive least square (RLS) method, two algorithms are developed for multiple MCs extraction. The global convergences of the proposed algorithms are also analyzed by the Lyapunov method. The proposed algorithms can extract the multiple MCs in parallel and has advantage in dealing with high dimension matrices. Since the weighted matrix does not require an accurate value, it facilitates the system design of the proposed algorithms for practical applications. The speed and computation advantages of the proposed algorithms are verified through simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural-net Processed Electronic Holography for Rotating Machines

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2003-01-01

This report presents the results of an R&D effort to apply neural-net processed electronic holography to NDE of rotors. Electronic holography was used to generate characteristic patterns or mode shapes of vibrating rotors and rotor components. Artificial neural networks were trained to identify damage-induced changes in the characteristic patterns. The development and optimization of a neural-net training method were the most significant contributions of this work, and the training method and its optimization are discussed in detail. A second positive result was the assembly and testing of a fiber-optic holocamera. A major disappointment was the inadequacy of the high-speed-holography hardware selected for this effort, but the use of scaled holograms to match the low effective resolution of an image intensifier was one interesting attempt to compensate. This report also discusses in some detail the physics and environmental requirements for rotor electronic holography. The major conclusions were that neural-net and electronic-holography inspections of stationary components in the laboratory and the field are quite practical and worthy of continuing development, but that electronic holography of moving rotors is still an expensive high-risk endeavor.

Low power pulsed MPD thruster system analysis and applications

NASA Astrophysics Data System (ADS)

Myers, Roger M.; Domonkos, Matthew; Gilland, James H.

1993-09-01

Pulsed magnetoplasmadynamic (MPD) thruster systems were analyzed for application to solar-electric orbit transfer vehicles at power levels ranging from 10 to 40 kW. Potential system level benefits of pulsed propulsion technology include ease of power scaling without thruster performance changes, improved transportability from low power flight experiments to operational systems, and reduced ground qualification costs. Required pulsed propulsion system components include a pulsed applied-field MPD thruster, a pulse-forming network, a charge control unit, a cathode heater supply, and high speed valves. Mass estimates were obtained for each propulsion subsystem and spacecraft component using off-the-shelf technology whenever possible. Results indicate that for payloads of 1000 and 2000 kg pulsed MPD thrusters can reduce launch mass by between 1000 and 2500 kg over those achievable with hydrogen arcjets, which can be used to reduce launch vehicle class and the associated launch cost. While the achievable mass savings depends on the trip time allowed for the mission, cases are shown in which the launch vehicle required for a mission is decreased from an Atlas IIAS to an Atlas I or Delta 7920.

Low power pulsed MPD thruster system analysis and applications

NASA Technical Reports Server (NTRS)

Myers, Roger M.; Domonkos, Matthew; Gilland, James H.

1993-01-01

Pulsed magnetoplasmadynamic (MPD) thruster systems were analyzed for application to solar-electric orbit transfer vehicles at power levels ranging from 10 to 40 kW. Potential system level benefits of pulsed propulsion technology include ease of power scaling without thruster performance changes, improved transportability from low power flight experiments to operational systems, and reduced ground qualification costs. Required pulsed propulsion system components include a pulsed applied-field MPD thruster, a pulse-forming network, a charge control unit, a cathode heater supply, and high speed valves. Mass estimates were obtained for each propulsion subsystem and spacecraft component using off-the-shelf technology whenever possible. Results indicate that for payloads of 1000 and 2000 kg pulsed MPD thrusters can reduce launch mass by between 1000 and 2500 kg over those achievable with hydrogen arcjets, which can be used to reduce launch vehicle class and the associated launch cost. While the achievable mass savings depends on the trip time allowed for the mission, cases are shown in which the launch vehicle required for a mission is decreased from an Atlas IIAS to an Atlas I or Delta 7920.

Evolving Requirements for Magnetic Tape Data Storage Systems

NASA Technical Reports Server (NTRS)

Gniewek, John J.

1996-01-01

Magnetic tape data storage systems have evolved in an environment where the major applications have been back-up/restore, disaster recovery, and long term archive. Coincident with the rapidly improving price-performance of disk storage systems, the prime requirements for tape storage systems have remained: (1) low cost per MB, (2) a data rate balanced to the remaining system components. Little emphasis was given to configuring the technology components to optimize retrieval of the stored data. Emerging new applications such as network attached high speed memory (HSM), and digital libraries, place additional emphasis and requirements on the retrieval of the stored data. It is therefore desirable to consider the system to be defined both by STorage And Retrieval System (STARS) requirements. It is possible to provide comparative performance analysis of different STARS by incorporating parameters related to (1) device characteristics, and (2) application characteristics in combination with queuing theory analysis. Results of these analyses are presented here in the form of response time as a function of system configuration for two different types of devices and for a variety of applications.

Working memory influences processing speed and reading fluency in ADHD.

PubMed

Jacobson, Lisa A; Ryan, Matthew; Martin, Rebecca B; Ewen, Joshua; Mostofsky, Stewart H; Denckla, Martha B; Mahone, E Mark

2011-01-01

Processing-speed deficits affect reading efficiency, even among individuals who recognize and decode words accurately. Children with ADHD who decode words accurately can still have inefficient reading fluency, leading to a bottleneck in other cognitive processes. This "slowing" in ADHD is associated with deficits in fundamental components of executive function underlying processing speed, including response selection. The purpose of the present study was to deconstruct processing speed in order to determine which components of executive control best explain the "processing" speed deficits related to reading fluency in ADHD. Participants (41 ADHD, 21 controls), ages 9-14 years, screened for language disorders, word reading deficits, and psychiatric disorders, were administered measures of copying speed, processing speed, reading fluency, working memory, reaction time, inhibition, and auditory attention span. Compared to controls, children with ADHD showed reduced oral and silent reading fluency and reduced processing speed-driven primarily by deficits on WISC-IV Coding. In contrast, groups did not differ on copying speed. After controlling for copying speed, sex, severity of ADHD-related symptomatology, and GAI, slowed "processing" speed (i.e., Coding) was significantly associated with verbal span and measures of working memory but not with measures of response control/inhibition, lexical retrieval speed, reaction time, or intrasubject variability. Further, "processing" speed (i.e., Coding, residualized for copying speed) and working memory were significant predictors of oral reading fluency. Abnormalities in working memory and response selection (which are frontally mediated and enter into the output side of processing speed) may play an important role in deficits in reading fluency in ADHD, potentially more than posteriorally mediated problems with orienting of attention or perceiving the stimulus.

The impact of social activities, social networks, social support and social relationships on the cognitive functioning of healthy older adults: a systematic review.

PubMed

Kelly, Michelle E; Duff, Hollie; Kelly, Sara; McHugh Power, Joanna E; Brennan, Sabina; Lawlor, Brian A; Loughrey, David G

2017-12-19

Social relationships, which are contingent on access to social networks, promote engagement in social activities and provide access to social support. These social factors have been shown to positively impact health outcomes. In the current systematic review, we offer a comprehensive overview of the impact of social activities, social networks and social support on the cognitive functioning of healthy older adults (50+) and examine the differential effects of aspects of social relationships on various cognitive domains. We followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, and collated data from randomised controlled trials (RCTs), genetic and observational studies. Independent variables of interest included subjective measures of social activities, social networks, and social support, and composite measures of social relationships (CMSR). The primary outcome of interest was cognitive function divided into domains of episodic memory, semantic memory, overall memory ability, working memory, verbal fluency, reasoning, attention, processing speed, visuospatial abilities, overall executive functioning and global cognition. Thirty-nine studies were included in the review; three RCTs, 34 observational studies, and two genetic studies. Evidence suggests a relationship between (1) social activity and global cognition and overall executive functioning, working memory, visuospatial abilities and processing speed but not episodic memory, verbal fluency, reasoning or attention; (2) social networks and global cognition but not episodic memory, attention or processing speed; (3) social support and global cognition and episodic memory but not attention or processing speed; and (4) CMSR and episodic memory and verbal fluency but not global cognition. The results support prior conclusions that there is an association between social relationships and cognitive function but the exact nature of this association remains unclear. Implications of the findings are discussed and suggestions for future research provided. PROSPERO 2012: CRD42012003248 .

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

NASA Technical Reports Server (NTRS)

Diallo, Ousmane H.

2012-01-01

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Transitions between Multiband Oscillatory Patterns Characterize Memory-Guided Perceptual Decisions in Prefrontal Circuits.

PubMed

Wimmer, Klaus; Ramon, Marc; Pasternak, Tatiana; Compte, Albert

2016-01-13

Neuronal activity in the lateral prefrontal cortex (LPFC) reflects the structure and cognitive demands of memory-guided sensory discrimination tasks. However, we still do not know how neuronal activity articulates in network states involved in perceiving, remembering, and comparing sensory information during such tasks. Oscillations in local field potentials (LFPs) provide fingerprints of such network dynamics. Here, we examined LFPs recorded from LPFC of macaques while they compared the directions or the speeds of two moving random-dot patterns, S1 and S2, separated by a delay. LFP activity in the theta, beta, and gamma bands tracked consecutive components of the task. In response to motion stimuli, LFP theta and gamma power increased, and beta power decreased, but showed only weak motion selectivity. In the delay, LFP beta power modulation anticipated the onset of S2 and encoded the task-relevant S1 feature, suggesting network dynamics associated with memory maintenance. After S2 onset the difference between the current stimulus S2 and the remembered S1 was strongly reflected in broadband LFP activity, with an early sensory-related component proportional to stimulus difference and a later choice-related component reflecting the behavioral decision buildup. Our results demonstrate that individual LFP bands reflect both sensory and cognitive processes engaged independently during different stages of the task. This activation pattern suggests that during elementary cognitive tasks, the prefrontal network transitions dynamically between states and that these transitions are characterized by the conjunction of LFP rhythms rather than by single LFP bands. Neurons in the brain communicate through electrical impulses and coordinate this activity in ensembles that pulsate rhythmically, very much like musical instruments in an orchestra. These rhythms change with "brain state," from sleep to waking, but also signal with different oscillation frequencies rapid changes between sensory and cognitive processing. Here, we studied rhythmic electrical activity in the monkey prefrontal cortex, an area implicated in working memory, decision making, and executive control. Monkeys had to identify and remember a visual motion pattern and compare it to a second pattern. We found orderly transitions between rhythmic activity where the same frequency channels were active in all ongoing prefrontal computations. This supports prefrontal circuit dynamics that transitions rapidly between complex rhythmic patterns during structured cognitive tasks. Copyright © 2016 the authors 0270-6474/16/360489-17$15.00/0.

Choosing a CD-ROM Network Solution.

ERIC Educational Resources Information Center

Doering, David

1996-01-01

Discusses issues to consider in selecting a CD-ROM network solution, including throughput (speed of data delivery), security, access, servers, key features, training, jukebox support, documentation, and licenses. Reviews software products offered by Novell, Around Technology, Micro Design, Smart Storage, Microtest, Meridian, CD-Connection,…

76 FR 31252 - Fixed and Mobile Services in the Mobile Satellite Service Bands at 1525-1559 MHz and 1626.5-1660...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-31

... also claims that MSS networks provide the only means to create a next generation air traffic management..., articulated their plans to offer high-speed data services, especially in connection with terrestrial networks... claimed that MSS networks provide the only means to create a next generation air traffic management (ATM...

Amphetamine primes motivation to gamble and gambling-related semantic networks in problem gamblers.

PubMed

Zack, Martin; Poulos, Constantine X

2004-01-01

Previous research suggests that gambling can induce effects that closely resemble a psychostimulant drug effect. Modest doses of addictive drugs can prime motivation for drugs with similar properties. Together, these findings imply that a dose of a psychostimulant drug could prime motivation to gamble in problem gamblers. This study assessed priming effects of oral D-amphetamine (AMPH) (30 mg) in a within-subject, counter-balanced, placebo-controlled design in problem gamblers (n=10), comorbid gamblerdrinkers (n=6), problem drinkers (n=8), and healthy controls (n=12). Modified visual analog scales assessed addictive motivation and subjective effects. A modified rapid reading task assessed pharmacological activation of words from motivationally relevant and irrelevant semantic domains (Gambling, Alcohol, Positive Affect, Negative Affect, Neutral). AMPH increased self-reported motivation for gambling in problem gamblers. Severity of problem gambling predicted positive subjective effects of AMPH and motivation to gamble under the drug. There was little evidence that AMPH directly primed motivation for alcohol in problem drinkers. On the reading task, AMPH produced undifferentiated improvement in reading speed to all word classes in Nongamblers. By contrast, in the two problem gambler groups, AMPH improved reading speed to Gambling words while profoundly slowing reading speed to motivationally irrelevant Neutral words. The latter finding was interpreted as directly congruent with models, which contend that priming of addictive motivation involves a linked suppression of motivationally irrelevant stimuli. This study provides experimental evidence that psychostimulant-like neurochemical activation is an important component of gambling addiction.

Noise can speed convergence in Markov chains.

PubMed

Franzke, Brandon; Kosko, Bart

2011-10-01

A new theorem shows that noise can speed convergence to equilibrium in discrete finite-state Markov chains. The noise applies to the state density and helps the Markov chain explore improbable regions of the state space. The theorem ensures that a stochastic-resonance noise benefit exists for states that obey a vector-norm inequality. Such noise leads to faster convergence because the noise reduces the norm components. A corollary shows that a noise benefit still occurs if the system states obey an alternate norm inequality. This leads to a noise-benefit algorithm that requires knowledge of the steady state. An alternative blind algorithm uses only past state information to achieve a weaker noise benefit. Simulations illustrate the predicted noise benefits in three well-known Markov models. The first model is a two-parameter Ehrenfest diffusion model that shows how noise benefits can occur in the class of birth-death processes. The second model is a Wright-Fisher model of genotype drift in population genetics. The third model is a chemical reaction network of zeolite crystallization. A fourth simulation shows a convergence rate increase of 64% for states that satisfy the theorem and an increase of 53% for states that satisfy the corollary. A final simulation shows that even suboptimal noise can speed convergence if the noise applies over successive time cycles. Noise benefits tend to be sharpest in Markov models that do not converge quickly and that do not have strong absorbing states.

Ponzi scheme diffusion in complex networks

NASA Astrophysics Data System (ADS)

Zhu, Anding; Fu, Peihua; Zhang, Qinghe; Chen, Zhenyue

2017-08-01

Ponzi schemes taking the form of Internet-based financial schemes have been negatively affecting China's economy for the last two years. Because there is currently a lack of modeling research on Ponzi scheme diffusion within social networks yet, we develop a potential-investor-divestor (PID) model to investigate the diffusion dynamics of Ponzi scheme in both homogeneous and inhomogeneous networks. Our simulation study of artificial and real Facebook social networks shows that the structure of investor networks does indeed affect the characteristics of dynamics. Both the average degree of distribution and the power-law degree of distribution will reduce the spreading critical threshold and will speed up the rate of diffusion. A high speed of diffusion is the key to alleviating the interest burden and improving the financial outcomes for the Ponzi scheme operator. The zero-crossing point of fund flux function we introduce proves to be a feasible index for reflecting the fast-worsening situation of fiscal instability and predicting the forthcoming collapse. The faster the scheme diffuses, the higher a peak it will reach and the sooner it will collapse. We should keep a vigilant eye on the harm of Ponzi scheme diffusion through modern social networks.

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

NASA Astrophysics Data System (ADS)

Wang, Junliang; Yang, Jungang; Zhang, Jie; Wang, Xiaoxi; Zhang, Wenjun Chris

2018-07-01

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.

Suppressing epidemic spreading by risk-averse migration in dynamical networks

NASA Astrophysics Data System (ADS)

Yang, Han-Xin; Tang, Ming; Wang, Zhen

2018-01-01

In this paper, we study the interplay between individual behaviors and epidemic spreading in a dynamical network. We distribute agents on a square-shaped region with periodic boundary conditions. Every agent is regarded as a node of the network and a wireless link is established between two agents if their geographical distance is less than a certain radius. At each time, every agent assesses the epidemic situation and make decisions on whether it should stay in or leave its current place. An agent will leave its current place with a speed if the number of infected neighbors reaches or exceeds a critical value E. Owing to the movement of agents, the network's structure is dynamical. Interestingly, we find that there exists an optimal value of E leading to the maximum epidemic threshold. This means that epidemic spreading can be effectively controlled by risk-averse migration. Besides, we find that the epidemic threshold increases as the recovering rate increases, decreases as the contact radius increases, and is maximized by an optimal moving speed. Our findings offer a deeper understanding of epidemic spreading in dynamical networks.

Speed and segmentation control mechanisms characterized in rhythmically-active circuits created from spinal neurons produced from genetically-tagged embryonic stem cells

PubMed Central

Sternfeld, Matthew J; Hinckley, Christopher A; Moore, Niall J; Pankratz, Matthew T; Hilde, Kathryn L; Driscoll, Shawn P; Hayashi, Marito; Amin, Neal D; Bonanomi, Dario; Gifford, Wesley D; Sharma, Kamal; Goulding, Martyn; Pfaff, Samuel L

2017-01-01

Flexible neural networks, such as the interconnected spinal neurons that control distinct motor actions, can switch their activity to produce different behaviors. Both excitatory (E) and inhibitory (I) spinal neurons are necessary for motor behavior, but the influence of recruiting different ratios of E-to-I cells remains unclear. We constructed synthetic microphysical neural networks, called circuitoids, using precise combinations of spinal neuron subtypes derived from mouse stem cells. Circuitoids of purified excitatory interneurons were sufficient to generate oscillatory bursts with properties similar to in vivo central pattern generators. Inhibitory V1 neurons provided dual layers of regulation within excitatory rhythmogenic networks - they increased the rhythmic burst frequency of excitatory V3 neurons, and segmented excitatory motor neuron activity into sub-networks. Accordingly, the speed and pattern of spinal circuits that underlie complex motor behaviors may be regulated by quantitatively gating the intra-network cellular activity ratio of E-to-I neurons. DOI: http://dx.doi.org/10.7554/eLife.21540.001 PMID:28195039

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Transition Features from Simplicity-Universality to Complexity-Diversification Under UHNTF

NASA Astrophysics Data System (ADS)

Fang, Jin-Qing; Li, Yong

2010-02-01

A large unified hybrid network model with a variable speed growth (LUHNM-VSG) is proposed as third model of the unified hybrid network theoretical framework (UHNTF). A hybrid growth ratio vg of deterministic linking number to random linking number and variable speed growth index α are introduced in it. The main effects of vg and α on topological transition features of the LUHNM-VSG are revealed. For comparison with the other models, we construct a type of the network complexity pyramid with seven levels, in which from the bottom level-1 to the top level-7 of the pyramid simplicity-universality is increasing but complexity-diversity is decreasing. The transition relations between them depend on matching of four hybrid ratios (dr, fd, gr, vg). Thus the most of network models can be investigated in the unification way via four hybrid ratios (dr, fd, gr, vg). The LUHNM-VSG as the level-1 of the pyramid is much better and closer to description of real-world networks as well as has potential application.

Astronomy, Data and the Problem of Large File Transfers

NASA Astrophysics Data System (ADS)

Bryant, J.; Sutorius, E.; Bunclark, P. S.

2008-08-01

During the lifetime of a survey a considerable amount of data are produced, this data needs to be moved between processing centres quickly and efficiently. Over time there has been a jostling as to which method of transferring data from one location to another is best: tape, disk or network, as they say ``Never underestimate the bandwidth of a station wagon full of tapes hurtling down the highway." With the VDFS the most painless solution seems to have been using network transfers. We started by using JANET to transfer our data but the rising monetary cost and unreliable transfer speeds when dealing with terabyte scale data volumes led us to investigate alternatives. Here we describe our work on connecting to the UKLight network, run by UKERNA, alongside JANET. This network provided us with a dedicated 1Gbit/s dark fibre for our sole use that allows us to transfer astronomical data between CASU and WFAU at speeds that are limited more by end server hardware than by the network (so maybe we can beat that station wagon.)

Toward the automated generation of genome-scale metabolic networks in the SEED.

PubMed

DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

2007-04-26

Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the stage for the automated generation of substantially complete metabolic networks for over 400 complete genome sequences currently in the SEED. With each genome that is processed using our tools, the database of common components grows to cover more of the diversity of metabolic pathways. This increases the likelihood that components of reaction networks for subsequently processed genomes can be retrieved from the database, rather than assembled and verified manually.

Noise-enhanced convolutional neural networks.

PubMed

Audhkhasi, Kartik; Osoba, Osonde; Kosko, Bart

2016-06-01

Injecting carefully chosen noise can speed convergence in the backpropagation training of a convolutional neural network (CNN). The Noisy CNN algorithm speeds training on average because the backpropagation algorithm is a special case of the generalized expectation-maximization (EM) algorithm and because such carefully chosen noise always speeds up the EM algorithm on average. The CNN framework gives a practical way to learn and recognize images because backpropagation scales with training data. It has only linear time complexity in the number of training samples. The Noisy CNN algorithm finds a special separating hyperplane in the network's noise space. The hyperplane arises from the likelihood-based positivity condition that noise-boosts the EM algorithm. The hyperplane cuts through a uniform-noise hypercube or Gaussian ball in the noise space depending on the type of noise used. Noise chosen from above the hyperplane speeds training on average. Noise chosen from below slows it on average. The algorithm can inject noise anywhere in the multilayered network. Adding noise to the output neurons reduced the average per-iteration training-set cross entropy by 39% on a standard MNIST image test set of handwritten digits. It also reduced the average per-iteration training-set classification error by 47%. Adding noise to the hidden layers can also reduce these performance measures. The noise benefit is most pronounced for smaller data sets because the largest EM hill-climbing gains tend to occur in the first few iterations. This noise effect can assist random sampling from large data sets because it allows a smaller random sample to give the same or better performance than a noiseless sample gives. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exploring methods of cGPS transient detections for the Chilean cGPS network in conjunction with displacement predictions from seismic catalogues: To what extent can we detect seismic and aseismic motion in the cGPS network?

NASA Astrophysics Data System (ADS)

Bedford, J. R.; Moreno, M.; Oncken, O.; Li, S.; Schurr, B.; Metzger, S.; Baez, J. C.; Deng, Z.; Melnick, D.

2016-12-01

Various algorithms for the detection of transient deformation in cGPS networks are under currently being developed to relieve us of by-eye detection, which is an error prone and time-expensive activity. Such algorithms aim to separate the time series into secular, seasonal, and transient components. Additional white and coloured noise, as well as common-mode (network correlated) noise, may remain in the separated transient component of the signal, depending on the processing flow before the separation step. The a-priori knowledge of regional seismicity can assist in the recognition of steps in the data, which are generally corrected for if they are above the noise-floor. Sometimes, the cumulative displacement caused by small earthquakes can create a seemingly continuous transient signal in the cGPS leading to confusion as to whether to attribute this transient motion as seismic or aseismic. Here we demonstrate the efficacy of various transient detection algorithms for subsets of the Chilean cGPS network and present the optimal processing flow for teasing out the transients. We present a step-detection and removal algorithm and estimate the seismic efficiency of any detected transient signals by forward modelling the surface displacements of the earthquakes and comparing to the recovered transient signals. A major challenge in separating signals in the Chilean cGPS network is the overlapping of postseismic effects at adjacent segments: For example, a Mw 9 earthquake will produce a postseismic viscoelastic relaxation that is sustained over decades and several hundreds of kilometres. Additionally, it has been observed in Chile and Japan that following moderately large earthquakes (e.g. Mw > 8) the secular velocities of adjacent segments in the subduction margin suddenly change and remain changed: this effect may be related to a change in speed of slab subduction rather than viscoelastic relaxation, and therefore the signal separation algorithms that assume a time-independent secular velocity at each station may need to be revised to account for this effect. Accordingly, we categorize the recovered separated secular and transient signals of a particular station in terms of the seismic cycle in both its own and adjacent segments and discuss the appropriate modelling strategy for this station given its category.

Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

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

Yang, Dr. Li

2010-08-01

The alerts produced by network-based intrusion detection systems, e.g. Snort, can be difficult for network administrators to efficiently review and respond to due to the enormous number of alerts generated in a short time frame. This work describes how the visualization of raw IDS alert data assists network administrators in understanding the current state of a network and quickens the process of reviewing and responding to intrusion attempts. The project presented in this work consists of three primary components. The first component provides a visual mapping of the network topology that allows the end-user to easily browse clustered alerts. Themore » second component is based on the flocking behavior of birds such that birds tend to follow other birds with similar behaviors. This component allows the end-user to see the clustering process and provides an efficient means for reviewing alert data. The third component discovers and visualizes patterns of multistage attacks by profiling the attacker s behaviors.« less

ATM encryption testing

NASA Astrophysics Data System (ADS)

Capell, Joyce; Deeth, David

1996-01-01

This paper describes why encryption was selected by Lockheed Martin Missiles & Space as the means for securing ATM networks. The ATM encryption testing program is part of an ATM network trial provided by Pacific Bell under the California Research Education Network (CalREN). The problem being addressed is the threat to data security which results when changing from a packet switched network infrastructure to a circuit switched ATM network backbone. As organizations move to high speed cell-based networks, there is a break down in the traditional security model which is designed to protect packet switched data networks from external attacks. This is due to the fact that most data security firewalls filter IP packets, restricting inbound and outbound protocols, e.g. ftp. ATM networks, based on cell-switching over virtual circuits, does not support this method for restricting access since the protocol information is not carried by each cell. ATM switches set up multiple virtual connections, thus there is no longer a single point of entry into the internal network. The problem is further complicated by the fact that ATM networks support high speed multi-media applications, including real time video and video teleconferencing which are incompatible with packet switched networks. The ability to restrict access to Lockheed Martin networks in support of both unclassified and classified communications is required before ATM network technology can be fully deployed. The Lockheed Martin CalREN ATM testbed provides the opportunity to test ATM encryption prototypes with actual applications to assess the viability of ATM encryption methodologies prior to installing large scale ATM networks. Two prototype ATM encryptors are being tested: (1) `MILKBUSH' a prototype encryptor developed by NSA for transmission of government classified data over ATM networks, and (2) a prototype ATM encryptor developed by Sandia National Labs in New Mexico, for the encryption of proprietary data.

Redundant speed control for brushless Hall effect motor

NASA Technical Reports Server (NTRS)

Nola, F. J. (Inventor)

1973-01-01

A speed control system for a brushless Hall effect device equipped direct current (D.C.) motor is described. Separate windings of the motor are powered by separate speed responsive power sources. A change in speed, upward or downward, because of the failure of a component of one of the power sources results in a corrective signal being generated in the other power source to supply an appropriate power level and polarity to one winding to cause the motor to be corrected in speed.

Feasibility Study on CNC Multioperation Grinding of Jet Engine Components Using Force Sensing Adaptive Control.

DTIC Science & Technology

1982-09-30

OF TI4IS PIAGE(,,aW Date Eateed) cont. block 20: .... differential wheelwear and thereby prevent form errors. Wheel sharpness can also be monitored to...80 5. NOMENCLATURE V = Work surface speed (m/s) w Nw = Work speed (RPM) Vs = Wheel surface speed (m/sec) Ns = Wheel ...speed (RPM) Vt = Traverse speed (m/sec) 0 = Work diameter (mm)W D = Wheel diameter (mm) z= Dress lead (um/rev) c = 2*diamond depth-of-dress (um) d

(DURIP 10) High Speed Intensified Imaging System For Studies Of Mixing And Combustion In Supersonic Flows And Hydrocarbon Flame Structure Measurements At Elevated Pressures

DTIC Science & Technology

2016-11-09

software, and their networking to augment optical diagnostics employed in supersonic reacting and non-reacting flow experiments . A high-speed...facility at Caltech. Experiments to date have made use of this equipment, extending previous capabilities to high-speed schlieren quantitative flow...visualization and image correlation velocimetry, with further experiments currently in progress. 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17

Dual processing of visual rotation for bipedal stance control.

PubMed

Day, Brian L; Muller, Timothy; Offord, Joanna; Di Giulio, Irene

2016-10-01

When standing, the gain of the body-movement response to a sinusoidally moving visual scene has been shown to get smaller with faster stimuli, possibly through changes in the apportioning of visual flow to self-motion or environment motion. We investigated whether visual-flow speed similarly influences the postural response to a discrete, unidirectional rotation of the visual scene in the frontal plane. Contrary to expectation, the evoked postural response consisted of two sequential components with opposite relationships to visual motion speed. With faster visual rotation the early component became smaller, not through a change in gain but by changes in its temporal structure, while the later component grew larger. We propose that the early component arises from the balance control system minimising apparent self-motion, while the later component stems from the postural system realigning the body with gravity. The source of visual motion is inherently ambiguous such that movement of objects in the environment can evoke self-motion illusions and postural adjustments. Theoretically, the brain can mitigate this problem by combining visual signals with other types of information. A Bayesian model that achieves this was previously proposed and predicts a decreasing gain of postural response with increasing visual motion speed. Here we test this prediction for discrete, unidirectional, full-field visual rotations in the frontal plane of standing subjects. The speed (0.75-48 deg s(-1) ) and direction of visual rotation was pseudo-randomly varied and mediolateral responses were measured from displacements of the trunk and horizontal ground reaction forces. The behaviour evoked by this visual rotation was more complex than has hitherto been reported, consisting broadly of two consecutive components with respective latencies of ∼190 ms and >0.7 s. Both components were sensitive to visual rotation speed, but with diametrically opposite relationships. Thus, the early component decreased with faster visual rotation, while the later component increased. Furthermore, the decrease in size of the early component was not achieved by a simple attenuation of gain, but by a change in its temporal structure. We conclude that the two components represent expressions of different motor functions, both pertinent to the control of bipedal stance. We propose that the early response stems from the balance control system attempting to minimise unintended body motion, while the later response arises from the postural control system attempting to align the body with gravity. © 2016 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Coordinated Speed Oscillations in Schooling Killifish Enrich Social Communication

NASA Astrophysics Data System (ADS)

Swain, Daniel T.; Couzin, Iain D.; Leonard, Naomi Ehrich

2015-10-01

We examine the spatial dynamics of individuals in small schools of banded killifish ( Fundulus diaphanus) that exhibit rhythmic, oscillating speed, typically with sustained, coordinated, out-of-phase speed oscillations as they move around a shallow water tank. We show that the relative motion among the fish yields a periodically time-varying network of social interactions that enriches visually driven social communication. The oscillations lead to the regular making and breaking of occlusions, which we term "switching." We show that the rate of convergence to consensus (biologically, the capacity for individuals in groups to achieve effective coordinated motion) governed by the switching outperforms static alternatives, and performs as well as the less practical case of every fish sensing every other fish. We show further that the oscillations in speed yield oscillations in relative bearing between fish over a range that includes the angles previously predicted to be optimal for a fish to detect changes in heading and speed of its neighbors. To investigate systematically, we derive and analyze a dynamic model of interacting agents that move with oscillatory speed. We show that coordinated circular motion of the school leads to systematic cycling of spatial ordering of agents and possibilities for enriched spatial density of measurements of the external environment. Our results highlight the potential benefits of dynamic communication topologies in collective animal behavior, and suggest new, useful control laws for the distributed coordination of mobile robotic networks.

[Application of wavelet transform and neural network in the near-infrared spectrum analysis of oil shale].

PubMed

Li, Su-Yi; Ji, Yan-Ju; Liu, Wei-Yu; Wang, Zhi-Hong

2013-04-01

In the present study, an innovative method is proposed, employing both wavelet transform and neural network, to analyze the near-infrared spectrum data in oil shale survey. The method entails using db8 wavelet at 3 levels decomposition to process raw data, using the transformed data as the input matrix, and creating the model through neural network. To verify the validity of the method, this study analyzes 30 synthesized oil shale samples, in which 20 samples are randomly selected for network training, the other 10 for model prediction, and uses the full spectrum and the wavelet transformed spectrum to carry out 10 network models, respectively. Results show that the mean speed of the full spectrum neural network modeling is 570.33 seconds, and the predicted residual sum of squares (PRESS) and correlation coefficient of prediction are 0.006 012 and 0.843 75, respectively. In contrast, the mean speed of the wavelet network modeling method is 3.15 seconds, and the mean PRESS and correlation coefficient of prediction are 0.002 048 and 0.953 19, respectively. These results demonstrate that the wavelet neural network modeling method is significantly superior to the full spectrum neural network modeling method. This study not only provides a new method for more efficient and accurate detection of the oil content of oil shale, but also indicates the potential for applying wavelet transform and neutral network in broad near-infrared spectrum analysis.

A speed limit compliance model for dynamic speed display sign.

PubMed

Ardeshiri, Anam; Jeihani, Mansoureh

2014-12-01

Violating speed limits is a major cause of motor vehicle crashes. Various techniques have been adopted to ensure that posted speed limits are obeyed by drivers. This study investigates the effect of dynamic speed display signs (DSDSs) on drivers' compliance with posted speed limit. An extensive speed data collection upstream of, adjacent to, and downstream of DSDS locations on multiple road classes with different speed limits (25, 35, and 45 mph) was performed short-term and long-term after DSDS installation. Conventional statistical analysis, regression models, and a Bayesian network were developed to assess the DSDS's effectiveness. General compliance with speed limit (upstream of the DSDS location), time of day, day of week, duration of DSDS operation, and distance from the DSDS location were significantly correlated with speed limit compliance adjacent to the DSDS. While compliance with the speed limit due to the DSDS increased by 5%, speed reduction occurred in 40% of the cases. Since drivers were likely to increase their speed after passing the DSDS, it should be installed on critical points supplemented with enforcement. Copyright © 2014 Elsevier Ltd. All rights reserved.

Working Memory Influences Processing Speed and Reading Fluency in ADHD

PubMed Central

Jacobson, Lisa A.; Ryan, Matthew; Martin, Rebecca B.; Ewen, Joshua; Mostofsky, Stewart H.; Denckla, Martha B.; Mahone, E. Mark

2012-01-01

Processing speed deficits affect reading efficiency, even among individuals who recognize and decode words accurately. Children with ADHD who decode words accurately can still have inefficient reading fluency, leading to a bottleneck in other cognitive processes. This “slowing” in ADHD is associated with deficits in fundamental components of executive function underlying processing speed, including response selection. The purpose of the present study was to deconstruct processing speed in order to determine which components of executive control best explain the “processing” speed deficits related to reading fluency in ADHD. Participants (41 ADHD, 21 controls), ages 9-14, screened for language disorders, word reading deficits, and psychiatric disorders, were administered measures of copying speed, processing speed, reading fluency, working memory, reaction time, inhibition, and auditory attention span. Compared to controls, children with ADHD showed reduced oral and silent reading fluency, and reduced processing speed—driven primarily by deficits on WISC-IV Coding. In contrast, groups did not differ on copying speed. After controlling for copying speed, sex, severity of ADHD-related symptomatology, and GAI, slowed “processing” speed (i.e., Coding) was significantly associated with verbal span and measures of working memory, but not with measures of response control/inhibition, lexical retrieval speed, reaction time, or intra-subject variability. Further, “processing” speed (i.e., Coding, residualized for copying speed) and working memory were significant predictors of oral reading fluency. Abnormalities in working memory and response selection (which are frontally-mediated and enter into the output side of processing speed) may play an important role in deficits in reading fluency in ADHD, potentially more than posteriorally-mediated problems with orienting of attention or perceiving the stimulus. PMID:21287422

The response of a high-speed train wheel to a harmonic wheel-rail force

NASA Astrophysics Data System (ADS)

Sheng, Xiaozhen; Liu, Yuxia; Zhou, Xin

2016-09-01

The maximum speed of China's high-speed trains currently is 300km/h and expected to increase to 350-400km/h. As a wheel travels along the rail at such a high speed, it is subject to a force rotating at the same speed along its periphery. This fast moving force contains not only the axle load component, but also many components of high frequencies generated from wheel-rail interactions. Rotation of the wheel also introduces centrifugal and gyroscopic effects. How the wheel responds is fundamental to many issues, including wheel-rail contact, traction, wear and noise. In this paper, by making use of its axial symmetry, a special finite element scheme is developed for responses of a train wheel subject to a vertical and harmonic wheel-rail force. This FE scheme only requires a 2D mesh over a cross-section containing the wheel axis but includes all the effects induced by wheel rotation. Nodal displacements, as a periodic function of the cross-section angle 6, can be decomposed, using Fourier series, into a number of components at different circumferential orders. The derived FE equation is solved for each circumferential order. The sum of responses at all circumferential orders gives the actual response of the wheel.

NASA and Industry Benefits of ACTS High Speed Network Interoperability Experiments

NASA Technical Reports Server (NTRS)

Zernic, M. J.; Beering, D. R.; Brooks, D. E.

2000-01-01

This paper provides synopses of the design. implementation, and results of key high data rate communications experiments utilizing the technologies of NASA's Advanced Communications Technology Satellite (ACTS). Specifically, the network protocol and interoperability performance aspects will be highlighted. The objectives of these key experiments will be discussed in their relevant context to NASA missions, as well as, to the comprehensive communications industry. Discussion of the experiment implementation will highlight the technical aspects of hybrid network connectivity, a variety of high-speed interoperability architectures, a variety of network node platforms, protocol layers, internet-based applications, and new work focused on distinguishing between link errors and congestion. In addition, this paper describes the impact of leveraging government-industry partnerships to achieve technical progress and forge synergistic relationships. These relationships will be the key to success as NASA seeks to combine commercially available technology with its own internal technology developments to realize more robust and cost effective communications for space operations.

Least Square Fast Learning Network for modeling the combustion efficiency of a 300WM coal-fired boiler.

PubMed

Li, Guoqiang; Niu, Peifeng; Wang, Huaibao; Liu, Yongchao

2014-03-01

This paper presents a novel artificial neural network with a very fast learning speed, all of whose weights and biases are determined by the twice Least Square method, so it is called Least Square Fast Learning Network (LSFLN). In addition, there is another difference from conventional neural networks, which is that the output neurons of LSFLN not only receive the information from the hidden layer neurons, but also receive the external information itself directly from the input neurons. In order to test the validity of LSFLN, it is applied to 6 classical regression applications, and also employed to build the functional relation between the combustion efficiency and operating parameters of a 300WM coal-fired boiler. Experimental results show that, compared with other methods, LSFLN with very less hidden neurons could achieve much better regression precision and generalization ability at a much faster learning speed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A solution to neural field equations by a recurrent neural network method

NASA Astrophysics Data System (ADS)

Alharbi, Abir

2012-09-01

Neural field equations (NFE) are used to model the activity of neurons in the brain, it is introduced from a single neuron 'integrate-and-fire model' starting point. The neural continuum is spatially discretized for numerical studies, and the governing equations are modeled as a system of ordinary differential equations. In this article the recurrent neural network approach is used to solve this system of ODEs. This consists of a technique developed by combining the standard numerical method of finite-differences with the Hopfield neural network. The architecture of the net, energy function, updating equations, and algorithms are developed for the NFE model. A Hopfield Neural Network is then designed to minimize the energy function modeling the NFE. Results obtained from the Hopfield-finite-differences net show excellent performance in terms of accuracy and speed. The parallelism nature of the Hopfield approaches may make them easier to implement on fast parallel computers and give them the speed advantage over the traditional methods.

Performance of gigabit FDDI

NASA Technical Reports Server (NTRS)

Game, David; Maly, Kurt J.

1990-01-01

Great interest exists in developing high speed protocols which will be able to support data rates at gigabit speeds. Hardware currently exists which can experimentally transmit at data rates exceeding a gigabit per second, but it is not clear as to what types of protocols will provide the best performance. One possibility is to examine current protocols and their extensibility to these speeds. Scaling of Fiber Distributed Data Interface (FDDI) to gigabit speeds is studied. More specifically, delay statistics are included to provide insight as to which parameters (network length, packet length or number of nodes) have the greatest effect on performance.

Exploration of Potential Future Fleet Architectures

DTIC Science & Technology

2005-07-01

alternative architectures are those espoused by the OFT sponsoring office: flexibility, adaptability, agility, speed, and information dominance through...including naval forces, which we used. The OFT advocates flexibility, adaptability, agility, speed, and information dominance through networking...challenges and transnational threats. In future conflicts, the Navy has plans to expand strike power, realize information dominance , and transform methods

Planning for complementarity : an examination of the role and opportunities of first-tier and second-tier cities along the high-speed rail network in California [research brief].

DOT National Transportation Integrated Search

2012-03-01

Californias High Speed Rail (HSR) offers opportunities for positive urban transformation in station cities, but the economic, urban design, real estate, and municipal behavior variables that may influence such change are understudied. This researc...

High speed multiwire photon camera

NASA Technical Reports Server (NTRS)

Lacy, Jeffrey L. (Inventor)

1991-01-01

An improved multiwire proportional counter camera having particular utility in the field of clinical nuclear medicine imaging. The detector utilizes direct coupled, low impedance, high speed delay lines, the segments of which are capacitor-inductor networks. A pile-up rejection test is provided to reject confused events otherwise caused by multiple ionization events occuring during the readout window.

High speed multiwire photon camera

NASA Technical Reports Server (NTRS)

Lacy, Jeffrey L. (Inventor)

1989-01-01

An improved multiwire proportional counter camera having particular utility in the field of clinical nuclear medicine imaging. The detector utilizes direct coupled, low impedance, high speed delay lines, the segments of which are capacitor-inductor networks. A pile-up rejection test is provided to reject confused events otherwise caused by multiple ionization events occurring during the readout window.

75 FR 36071 - Framework for Broadband Internet Service

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-24

... contractor, Best Copy and Printing, Inc. (BCPI), Portals II, 445 12th Street, SW., Room CY-B402, Washington...-leading high-speed broadband networks--both wired and wireless--lies at the very core of the FCC's mission... subscribers with high-speed Internet access, as well as many applications or functions that can be used with...

An Identity-Based Anti-Quantum Privacy-Preserving Blind Authentication in Wireless Sensor Networks.

PubMed

Zhu, Hongfei; Tan, Yu-An; Zhu, Liehuang; Wang, Xianmin; Zhang, Quanxin; Li, Yuanzhang

2018-05-22

With the development of wireless sensor networks, IoT devices are crucial for the Smart City; these devices change people's lives such as e-payment and e-voting systems. However, in these two systems, the state-of-art authentication protocols based on traditional number theory cannot defeat a quantum computer attack. In order to protect user privacy and guarantee trustworthy of big data, we propose a new identity-based blind signature scheme based on number theorem research unit lattice, this scheme mainly uses a rejection sampling theorem instead of constructing a trapdoor. Meanwhile, this scheme does not depend on complex public key infrastructure and can resist quantum computer attack. Then we design an e-payment protocol using the proposed scheme. Furthermore, we prove our scheme is secure in the random oracle, and satisfies confidentiality, integrity, and non-repudiation. Finally, we demonstrate that the proposed scheme outperforms the other traditional existing identity-based blind signature schemes in signing speed and verification speed, outperforms the other lattice-based blind signature in signing speed, verification speed, and signing secret key size.

An Identity-Based Anti-Quantum Privacy-Preserving Blind Authentication in Wireless Sensor Networks

PubMed Central

Zhu, Hongfei; Tan, Yu-an; Zhu, Liehuang; Wang, Xianmin; Zhang, Quanxin; Li, Yuanzhang

2018-01-01

With the development of wireless sensor networks, IoT devices are crucial for the Smart City; these devices change people’s lives such as e-payment and e-voting systems. However, in these two systems, the state-of-art authentication protocols based on traditional number theory cannot defeat a quantum computer attack. In order to protect user privacy and guarantee trustworthy of big data, we propose a new identity-based blind signature scheme based on number theorem research unit lattice, this scheme mainly uses a rejection sampling theorem instead of constructing a trapdoor. Meanwhile, this scheme does not depend on complex public key infrastructure and can resist quantum computer attack. Then we design an e-payment protocol using the proposed scheme. Furthermore, we prove our scheme is secure in the random oracle, and satisfies confidentiality, integrity, and non-repudiation. Finally, we demonstrate that the proposed scheme outperforms the other traditional existing identity-based blind signature schemes in signing speed and verification speed, outperforms the other lattice-based blind signature in signing speed, verification speed, and signing secret key size. PMID:29789475

Security Aspects of an Enterprise-Wide Network Architecture.

ERIC Educational Resources Information Center

Loew, Robert; Stengel, Ingo; Bleimann, Udo; McDonald, Aidan

1999-01-01

Presents an overview of two projects that concern local area networks and the common point between networks as they relate to network security. Discusses security architectures based on firewall components, packet filters, application gateways, security-management components, an intranet solution, user registration by Web form, and requests for…

Extensibility and limitations of FDDI

NASA Technical Reports Server (NTRS)

Game, David; Maly, Kurt J.

1990-01-01

Recently two standards for Metropolitan Area Networks (MANs), Fiber Distributed Data Interface (FDDI) and Distributed Queue Dual Bus (DQDB), have emerged as the primary competitors for the MAN arena. Great interest exists in building higher speed networks which support large numbers of node and greater distance, and it is not clear what types of protocols are needed for this type of environment. There is some question as to whether or not these MAN standards can be extended to such environments. The extensibility of FDDI to the Gbps range and a long distance environment is investigated. Specification parameters which affect performance are shown and a measure is provided for predicting utilization of FDDI. A comparison of FDDI at 100 Mbps and 1 Gbps is presented. Some specific problems with FDDI are addressed and modifications which improve the viability of FDDI in such high speed networks are investigated.

A Novel Adjustment Method for Shearer Traction Speed through Integration of T-S Cloud Inference Network and Improved PSO

PubMed Central

Si, Lei; Wang, Zhongbin; Yang, Yinwei

2014-01-01

In order to efficiently and accurately adjust the shearer traction speed, a novel approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO algorithm employs parameter automation adjustment strategy and velocity resetting to significantly improve the performance of basic PSO algorithm in global search and fine-tuning of the solutions, and the flowchart of proposed approach is designed. Furthermore, some simulation examples are carried out and comparison results indicate that the proposed method is feasible, efficient, and is outperforming others. Finally, an industrial application example of coal mining face is demonstrated to specify the effect of proposed system. PMID:25506358

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Role of uncrosslinked chains in droplets dynamics on silicone elastomers.

PubMed

Hourlier-Fargette, Aurélie; Antkowiak, Arnaud; Chateauminois, Antoine; Neukirch, Sébastien

2017-05-21

We report an unexpected behavior in wetting dynamics on soft silicone substrates: the dynamics of aqueous droplets deposited on vertical plates of such elastomers exhibits two successive speed regimes. This macroscopic observation is found to be closely related to microscopic phenomena occurring at the scale of the polymer network: we show that uncrosslinked chains found in most widely used commercial silicone elastomers are responsible for this surprising behavior. A direct visualization of the uncrosslinked oligomers collected by water droplets is performed, evidencing that a capillarity-induced phase separation occurs: uncrosslinked oligomers are extracted from the silicone elastomer network by the water-glycerol mixture droplet. The sharp speed change is shown to coincide with an abrupt transition in surface tension of the droplets, when a critical surface concentration in uncrosslinked oligomer chains is reached. We infer that a droplet shifts to a second regime with a faster speed when it is completely covered with a homogeneous oil film.

Stress Testing of Data-Communication Networks

NASA Technical Reports Server (NTRS)

Leucht, Kurt; Bedette, Guy

2006-01-01

NetStress is a computer program that stress-tests a data-communication network and components thereof. NetStress comprises two components running, respectively, in a transmitting system and a receiving system connected to a network under test