A Network Coding Based Routing Protocol for Underwater Sensor Networks

PubMed Central

Wu, Huayang; Chen, Min; Guan, Xin

2012-01-01

Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs). Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR).We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC) comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime. PMID:22666045

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

PubMed

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres

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

Ortiz-Rodriguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.

In this work a neutron spectrum unfolding code, based on artificial intelligence technology is presented. The code called ''Neutron Spectrometry and Dosimetry with Artificial Neural Networks and two Bonner spheres'', (NSDann2BS), was designed in a graphical user interface under the LabVIEW programming environment. The main features of this code are to use an embedded artificial neural network architecture optimized with the ''Robust design of artificial neural networks methodology'' and to use two Bonner spheres as the only piece of information. In order to build the code here presented, once the net topology was optimized and properly trained, knowledge stored atmore » synaptic weights was extracted and using a graphical framework build on the LabVIEW programming environment, the NSDann2BS code was designed. This code is friendly, intuitive and easy to use for the end user. The code is freely available upon request to authors. To demonstrate the use of the neural net embedded in the NSDann2BS code, the rate counts of {sup 252}Cf, {sup 241}AmBe and {sup 239}PuBe neutron sources measured with a Bonner spheres system.« less

NSDann2BS, a neutron spectrum unfolding code based on neural networks technology and two bonner spheres

NASA Astrophysics Data System (ADS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-07-01

In this work a neutron spectrum unfolding code, based on artificial intelligence technology is presented. The code called "Neutron Spectrometry and Dosimetry with Artificial Neural Networks and two Bonner spheres", (NSDann2BS), was designed in a graphical user interface under the LabVIEW programming environment. The main features of this code are to use an embedded artificial neural network architecture optimized with the "Robust design of artificial neural networks methodology" and to use two Bonner spheres as the only piece of information. In order to build the code here presented, once the net topology was optimized and properly trained, knowledge stored at synaptic weights was extracted and using a graphical framework build on the LabVIEW programming environment, the NSDann2BS code was designed. This code is friendly, intuitive and easy to use for the end user. The code is freely available upon request to authors. To demonstrate the use of the neural net embedded in the NSDann2BS code, the rate counts of 252Cf, 241AmBe and 239PuBe neutron sources measured with a Bonner spheres system.

A New Wavelength Optimization and Energy-Saving Scheme Based on Network Coding in Software-Defined WDM-PON Networks

NASA Astrophysics Data System (ADS)

Ren, Danping; Wu, Shanshan; Zhang, Lijing

2016-09-01

In view of the characteristics of the global control and flexible monitor of software-defined networks (SDN), we proposes a new optical access network architecture dedicated to Wavelength Division Multiplexing-Passive Optical Network (WDM-PON) systems based on SDN. The network coding (NC) technology is also applied into this architecture to enhance the utilization of wavelength resource and reduce the costs of light source. Simulation results show that this scheme can optimize the throughput of the WDM-PON network, greatly reduce the system time delay and energy consumption.

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks

PubMed Central

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-01-01

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C/2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C/2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi’s model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments. PMID:29401668

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks.

PubMed

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.

Design and Simulation of Material-Integrated Distributed Sensor Processing with a Code-Based Agent Platform and Mobile Multi-Agent Systems

PubMed Central

Bosse, Stefan

2015-01-01

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques. PMID:25690550

Design and simulation of material-integrated distributed sensor processing with a code-based agent platform and mobile multi-agent systems.

PubMed

Bosse, Stefan

2015-02-16

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

A neutron spectrum unfolding computer code based on artificial neural networks

NASA Astrophysics Data System (ADS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2014-02-01

The Bonner Spheres Spectrometer consists of a thermal neutron sensor placed at the center of a number of moderating polyethylene spheres of different diameters. From the measured readings, information can be derived about the spectrum of the neutron field where measurements were made. Disadvantages of the Bonner system are the weight associated with each sphere and the need to sequentially irradiate the spheres, requiring long exposure periods. Provided a well-established response matrix and adequate irradiation conditions, the most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. The drawbacks associated with traditional unfolding procedures have motivated the need of complementary approaches. Novel methods based on Artificial Intelligence, mainly Artificial Neural Networks, have been widely investigated. In this work, a neutron spectrum unfolding code based on neural nets technology is presented. This code is called Neutron Spectrometry and Dosimetry with Artificial Neural networks unfolding code that was designed in a graphical interface. The core of the code is an embedded neural network architecture previously optimized using the robust design of artificial neural networks methodology. The main features of the code are: easy to use, friendly and intuitive to the user. This code was designed for a Bonner Sphere System based on a 6LiI(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. The main feature of the code is that as entrance data, for unfolding the neutron spectrum, only seven rate counts measured with seven Bonner spheres are required; simultaneously the code calculates 15 dosimetric quantities as well as the total flux for radiation protection purposes. This code generates a full report with all information of the unfolding in the HTML format. NSDann unfolding code is freely available, upon request to the authors.

Mobile Security Enclaves

DTIC Science & Technology

2011-09-01

LAI Location Area Identity MANET Mobile Ad - hoc Network MCC Mobile Country Code MCD Mobile Communications Device MNC Mobile Network Code ...tower or present within a geographical area. These conditions relate directly to users who often operate with mobile ad - hoc networks. These types of...infrastructures. First responders can use these mobile base stations to set up their own networks on the fly, similar to mobile ad - hoc networks

NetCoDer: A Retransmission Mechanism for WSNs Based on Cooperative Relays and Network Coding

PubMed Central

Valle, Odilson T.; Montez, Carlos; Medeiros de Araujo, Gustavo; Vasques, Francisco; Moraes, Ricardo

2016-01-01

Some of the most difficult problems to deal with when using Wireless Sensor Networks (WSNs) are related to the unreliable nature of communication channels. In this context, the use of cooperative diversity techniques and the application of network coding concepts may be promising solutions to improve the communication reliability. In this paper, we propose the NetCoDer scheme to address this problem. Its design is based on merging cooperative diversity techniques and network coding concepts. We evaluate the effectiveness of the NetCoDer scheme through both an experimental setup with real WSN nodes and a simulation assessment, comparing NetCoDer performance against state-of-the-art TDMA-based (Time Division Multiple Access) retransmission techniques: BlockACK, Master/Slave and Redundant TDMA. The obtained results highlight that the proposed NetCoDer scheme clearly improves the network performance when compared with other retransmission techniques. PMID:27258280

The queueing perspective of asynchronous network coding in two-way relay network

NASA Astrophysics Data System (ADS)

Liang, Yaping; Chang, Qing; Li, Xianxu

2018-04-01

Asynchronous network coding (NC) has potential to improve the wireless network performance compared with a routing or the synchronous network coding. Recent researches concentrate on the optimization between throughput/energy consuming and delay with a couple of independent input flow. However, the implementation of NC requires a thorough investigation of its impact on relevant queueing systems where few work focuses on. Moreover, few works study the probability density function (pdf) in network coding scenario. In this paper, the scenario with two independent Poisson input flows and one output flow is considered. The asynchronous NC-based strategy is that a new arrival evicts a head packet holding in its queue when waiting for another packet from the other flow to encode. The pdf for the output flow which contains both coded and uncoded packets is derived. Besides, the statistic characteristics of this strategy are analyzed. These results are verified by numerical simulations.

Channel coding for underwater acoustic single-carrier CDMA communication system

NASA Astrophysics Data System (ADS)

Liu, Lanjun; Zhang, Yonglei; Zhang, Pengcheng; Zhou, Lin; Niu, Jiong

2017-01-01

CDMA is an effective multiple access protocol for underwater acoustic networks, and channel coding can effectively reduce the bit error rate (BER) of the underwater acoustic communication system. For the requirements of underwater acoustic mobile networks based on CDMA, an underwater acoustic single-carrier CDMA communication system (UWA/SCCDMA) based on the direct-sequence spread spectrum is proposed, and its channel coding scheme is studied based on convolution, RA, Turbo and LDPC coding respectively. The implementation steps of the Viterbi algorithm of convolutional coding, BP and minimum sum algorithms of RA coding, Log-MAP and SOVA algorithms of Turbo coding, and sum-product algorithm of LDPC coding are given. An UWA/SCCDMA simulation system based on Matlab is designed. Simulation results show that the UWA/SCCDMA based on RA, Turbo and LDPC coding have good performance such that the communication BER is all less than 10-6 in the underwater acoustic channel with low signal to noise ratio (SNR) from -12 dB to -10dB, which is about 2 orders of magnitude lower than that of the convolutional coding. The system based on Turbo coding with Log-MAP algorithm has the best performance.

Layered Wyner-Ziv video coding.

PubMed

Xu, Qian; Xiong, Zixiang

2006-12-01

Following recent theoretical works on successive Wyner-Ziv coding (WZC), we propose a practical layered Wyner-Ziv video coder using the DCT, nested scalar quantization, and irregular LDPC code based Slepian-Wolf coding (or lossless source coding with side information at the decoder). Our main novelty is to use the base layer of a standard scalable video coder (e.g., MPEG-4/H.26L FGS or H.263+) as the decoder side information and perform layered WZC for quality enhancement. Similar to FGS coding, there is no performance difference between layered and monolithic WZC when the enhancement bitstream is generated in our proposed coder. Using an H.26L coded version as the base layer, experiments indicate that WZC gives slightly worse performance than FGS coding when the channel (for both the base and enhancement layers) is noiseless. However, when the channel is noisy, extensive simulations of video transmission over wireless networks conforming to the CDMA2000 1X standard show that H.26L base layer coding plus Wyner-Ziv enhancement layer coding are more robust against channel errors than H.26L FGS coding. These results demonstrate that layered Wyner-Ziv video coding is a promising new technique for video streaming over wireless networks.

A Hybrid Path-Oriented Code Assignment CDMA-Based MAC Protocol for Underwater Acoustic Sensor Networks

PubMed Central

Chen, Huifang; Fan, Guangyu; Xie, Lei; Cui, Jun-Hong

2013-01-01

Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field and message forwarding to the sink hop-by-hop, the sensors near the sink have to transmit more packets than those far from the sink, and then a funneling effect occurs, which leads to packet congestion, collisions and losses, especially in UWASNs with long propagation delays. An improved CDMA-based MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC), is proposed for UWASNs in this paper. In the proposed MAC protocol, both the round-robin method and CDMA technology are adopted to make the sink receive packets from multiple paths simultaneously. Since the number of paths for information gathering is much less than that of nodes, the length of the spreading code used in the POCA-CDMA-MAC protocol is shorter greatly than that used in the CDMA-based protocols with transmitter-oriented code assignment (TOCA) or receiver-oriented code assignment (ROCA). Simulation results show that the proposed POCA-CDMA-MAC protocol achieves a higher network throughput and a lower end-to-end delay compared to other CDMA-based MAC protocols. PMID:24193100

A hybrid path-oriented code assignment CDMA-based MAC protocol for underwater acoustic sensor networks.

PubMed

Chen, Huifang; Fan, Guangyu; Xie, Lei; Cui, Jun-Hong

2013-11-04

Due to the characteristics of underwater acoustic channel, media access control (MAC) protocols designed for underwater acoustic sensor networks (UWASNs) are quite different from those for terrestrial wireless sensor networks. Moreover, in a sink-oriented network with event information generation in a sensor field and message forwarding to the sink hop-by-hop, the sensors near the sink have to transmit more packets than those far from the sink, and then a funneling effect occurs, which leads to packet congestion, collisions and losses, especially in UWASNs with long propagation delays. An improved CDMA-based MAC protocol, named path-oriented code assignment (POCA) CDMA MAC (POCA-CDMA-MAC), is proposed for UWASNs in this paper. In the proposed MAC protocol, both the round-robin method and CDMA technology are adopted to make the sink receive packets from multiple paths simultaneously. Since the number of paths for information gathering is much less than that of nodes, the length of the spreading code used in the POCA-CDMA-MAC protocol is shorter greatly than that used in the CDMA-based protocols with transmitter-oriented code assignment (TOCA) or receiver-oriented code assignment (ROCA). Simulation results show that the proposed POCA-CDMA-MAC protocol achieves a higher network throughput and a lower end-to-end delay compared to other CDMA-based MAC protocols.

Impact of dynamic rate coding aspects of mobile phone networks on forensic voice comparison.

PubMed

Alzqhoul, Esam A S; Nair, Balamurali B T; Guillemin, Bernard J

2015-09-01

Previous studies have shown that landline and mobile phone networks are different in their ways of handling the speech signal, and therefore in their impact on it. But the same is also true of the different networks within the mobile phone arena. There are two major mobile phone technologies currently in use today, namely the global system for mobile communications (GSM) and code division multiple access (CDMA) and these are fundamentally different in their design. For example, the quality of the coded speech in the GSM network is a function of channel quality, whereas in the CDMA network it is determined by channel capacity (i.e., the number of users sharing a cell site). This paper examines the impact on the speech signal of a key feature of these networks, namely dynamic rate coding, and its subsequent impact on the task of likelihood-ratio-based forensic voice comparison (FVC). Surprisingly, both FVC accuracy and precision are found to be better for both GSM- and CDMA-coded speech than for uncoded. Intuitively one expects FVC accuracy to increase with increasing coded speech quality. This trend is shown to occur for the CDMA network, but, surprisingly, not for the GSM network. Further, in respect to comparisons between these two networks, FVC accuracy for CDMA-coded speech is shown to be slightly better than for GSM-coded speech, particularly when the coded-speech quality is high, but in terms of FVC precision the two networks are shown to be very similar. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

A Large Scale Code Resolution Service Network in the Internet of Things

PubMed Central

Yu, Haining; Zhang, Hongli; Fang, Binxing; Yu, Xiangzhan

2012-01-01

In the Internet of Things a code resolution service provides a discovery mechanism for a requester to obtain the information resources associated with a particular product code immediately. In large scale application scenarios a code resolution service faces some serious issues involving heterogeneity, big data and data ownership. A code resolution service network is required to address these issues. Firstly, a list of requirements for the network architecture and code resolution services is proposed. Secondly, in order to eliminate code resolution conflicts and code resolution overloads, a code structure is presented to create a uniform namespace for code resolution records. Thirdly, we propose a loosely coupled distributed network consisting of heterogeneous, independent; collaborating code resolution services and a SkipNet based code resolution service named SkipNet-OCRS, which not only inherits DHT's advantages, but also supports administrative control and autonomy. For the external behaviors of SkipNet-OCRS, a novel external behavior mode named QRRA mode is proposed to enhance security and reduce requester complexity. For the internal behaviors of SkipNet-OCRS, an improved query algorithm is proposed to increase query efficiency. It is analyzed that integrating SkipNet-OCRS into our resolution service network can meet our proposed requirements. Finally, simulation experiments verify the excellent performance of SkipNet-OCRS. PMID:23202207

A large scale code resolution service network in the Internet of Things.

PubMed

Yu, Haining; Zhang, Hongli; Fang, Binxing; Yu, Xiangzhan

2012-11-07

In the Internet of Things a code resolution service provides a discovery mechanism for a requester to obtain the information resources associated with a particular product code immediately. In large scale application scenarios a code resolution service faces some serious issues involving heterogeneity, big data and data ownership. A code resolution service network is required to address these issues. Firstly, a list of requirements for the network architecture and code resolution services is proposed. Secondly, in order to eliminate code resolution conflicts and code resolution overloads, a code structure is presented to create a uniform namespace for code resolution records. Thirdly, we propose a loosely coupled distributed network consisting of heterogeneous, independent; collaborating code resolution services and a SkipNet based code resolution service named SkipNet-OCRS, which not only inherits DHT’s advantages, but also supports administrative control and autonomy. For the external behaviors of SkipNet-OCRS, a novel external behavior mode named QRRA mode is proposed to enhance security and reduce requester complexity. For the internal behaviors of SkipNet-OCRS, an improved query algorithm is proposed to increase query efficiency. It is analyzed that integrating SkipNet-OCRS into our resolution service network can meet our proposed requirements. Finally, simulation experiments verify the excellent performance of SkipNet-OCRS.

Statistical mechanics of broadcast channels using low-density parity-check codes.

PubMed

Nakamura, Kazutaka; Kabashima, Yoshiyuki; Morelos-Zaragoza, Robert; Saad, David

2003-03-01

We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.

A Network Coding Based Hybrid ARQ Protocol for Underwater Acoustic Sensor Networks

PubMed Central

Wang, Hao; Wang, Shilian; Zhang, Eryang; Zou, Jianbin

2016-01-01

Underwater Acoustic Sensor Networks (UASNs) have attracted increasing interest in recent years due to their extensive commercial and military applications. However, the harsh underwater channel causes many challenges for the design of reliable underwater data transport protocol. In this paper, we propose an energy efficient data transport protocol based on network coding and hybrid automatic repeat request (NCHARQ) to ensure reliability, efficiency and availability in UASNs. Moreover, an adaptive window length estimation algorithm is designed to optimize the throughput and energy consumption tradeoff. The algorithm can adaptively change the code rate and can be insensitive to the environment change. Extensive simulations and analysis show that NCHARQ significantly reduces energy consumption with short end-to-end delay. PMID:27618044

Deep Constrained Siamese Hash Coding Network and Load-Balanced Locality-Sensitive Hashing for Near Duplicate Image Detection.

PubMed

Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen

2018-09-01

We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

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

Ortiz-Rodriguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetrymore » with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.« less

Evaluating the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks

NASA Astrophysics Data System (ADS)

Ortiz-Rodríguez, J. M.; Reyes Alfaro, A.; Reyes Haro, A.; Solís Sánches, L. O.; Miranda, R. Castañeda; Cervantes Viramontes, J. M.; Vega-Carrillo, H. R.

2013-07-01

In this work the performance of two neutron spectrum unfolding codes based on iterative procedures and artificial neural networks is evaluated. The first one code based on traditional iterative procedures and called Neutron spectrometry and dosimetry from the Universidad Autonoma de Zacatecas (NSDUAZ) use the SPUNIT iterative algorithm and was designed to unfold neutron spectrum and calculate 15 dosimetric quantities and 7 IAEA survey meters. The main feature of this code is the automated selection of the initial guess spectrum trough a compendium of neutron spectrum compiled by the IAEA. The second one code known as Neutron spectrometry and dosimetry with artificial neural networks (NDSann) is a code designed using neural nets technology. The artificial intelligence approach of neural net does not solve mathematical equations. By using the knowledge stored at synaptic weights on a neural net properly trained, the code is capable to unfold neutron spectrum and to simultaneously calculate 15 dosimetric quantities, needing as entrance data, only the rate counts measured with a Bonner spheres system. Similarities of both NSDUAZ and NSDann codes are: they follow the same easy and intuitive user's philosophy and were designed in a graphical interface under the LabVIEW programming environment. Both codes unfold the neutron spectrum expressed in 60 energy bins, calculate 15 dosimetric quantities and generate a full report in HTML format. Differences of these codes are: NSDUAZ code was designed using classical iterative approaches and needs an initial guess spectrum in order to initiate the iterative procedure. In NSDUAZ, a programming routine was designed to calculate 7 IAEA instrument survey meters using the fluence-dose conversion coefficients. NSDann code use artificial neural networks for solving the ill-conditioned equation system of neutron spectrometry problem through synaptic weights of a properly trained neural network. Contrary to iterative procedures, in neural net approach it is possible to reduce the rate counts used to unfold the neutron spectrum. To evaluate these codes a computer tool called Neutron Spectrometry and dosimetry computer tool was designed. The results obtained with this package are showed. The codes here mentioned are freely available upon request to the authors.

A novel all-optical label processing for OPS networks based on multiple OOC sequences from multiple-groups OOC

NASA Astrophysics Data System (ADS)

Qiu, Kun; Zhang, Chongfu; Ling, Yun; Wang, Yibo

2007-11-01

This paper proposes an all-optical label processing scheme using multiple optical orthogonal codes sequences (MOOCS) for optical packet switching (OPS) (MOOCS-OPS) networks, for the first time to the best of our knowledge. In this scheme, the multiple optical orthogonal codes (MOOC) from multiple-groups optical orthogonal codes (MGOOC) are permuted and combined to obtain the MOOCS for the optical labels, which are used to effectively enlarge the capacity of available optical codes for optical labels. The optical label processing (OLP) schemes are reviewed and analyzed, the principles of MOOCS-based optical labels for OPS networks are given, and analyzed, then the MOOCS-OPS topology and the key realization units of the MOOCS-based optical label packets are studied in detail, respectively. The performances of this novel all-optical label processing technology are analyzed, the corresponding simulation is performed. These analysis and results show that the proposed scheme can overcome the lack of available optical orthogonal codes (OOC)-based optical labels due to the limited number of single OOC for optical label with the short code length, and indicate that the MOOCS-OPS scheme is feasible.

Incorporation of Condensation Heat Transfer in a Flow Network Code

NASA Technical Reports Server (NTRS)

Anthony, Miranda; Majumdar, Alok; McConnaughey, Paul K. (Technical Monitor)

2001-01-01

In this paper we have investigated the condensation of water vapor in a short tube. A numerical model of condensation heat transfer was incorporated in a flow network code. The flow network code that we have used in this paper is Generalized Fluid System Simulation Program (GFSSP). GFSSP is a finite volume based flow network code. Four different condensation models were presented in the paper. Soliman's correlation has been found to be the most stable in low flow rates which is of particular interest in this application. Another highlight of this investigation is conjugate or coupled heat transfer between solid or fluid. This work was done in support of NASA's International Space Station program.

Network perturbation by recurrent regulatory variants in cancer

PubMed Central

Cho, Ara; Lee, Insuk; Choi, Jung Kyoon

2017-01-01

Cancer driving genes have been identified as recurrently affected by variants that alter protein-coding sequences. However, a majority of cancer variants arise in noncoding regions, and some of them are thought to play a critical role through transcriptional perturbation. Here we identified putative transcriptional driver genes based on combinatorial variant recurrence in cis-regulatory regions. The identified genes showed high connectivity in the cancer type-specific transcription regulatory network, with high outdegree and many downstream genes, highlighting their causative role during tumorigenesis. In the protein interactome, the identified transcriptional drivers were not as highly connected as coding driver genes but appeared to form a network module centered on the coding drivers. The coding and regulatory variants associated via these interactions between the coding and transcriptional drivers showed exclusive and complementary occurrence patterns across tumor samples. Transcriptional cancer drivers may act through an extensive perturbation of the regulatory network and by altering protein network modules through interactions with coding driver genes. PMID:28333928

Decoding small surface codes with feedforward neural networks

NASA Astrophysics Data System (ADS)

Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen

2018-01-01

Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.

A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks.

PubMed

Wang, Hao; Wang, Shilian; Bu, Renfei; Zhang, Eryang

2017-08-08

Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs.

Anisotropic connectivity implements motion-based prediction in a spiking neural network.

PubMed

Kaplan, Bernhard A; Lansner, Anders; Masson, Guillaume S; Perrinet, Laurent U

2013-01-01

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show that the applied connection pattern leads to motion-based prediction in an experiment tracking a moving dot. In contrast to our proposed model, a network with random or isotropic connectivity fails to predict the path when the moving dot disappears. Furthermore, we show that a simple linear decoding approach is sufficient to transform neuronal spiking activity into a probabilistic estimate for reading out the target trajectory.

The Energy Coding of a Structural Neural Network Based on the Hodgkin-Huxley Model.

PubMed

Zhu, Zhenyu; Wang, Rubin; Zhu, Fengyun

2018-01-01

Based on the Hodgkin-Huxley model, the present study established a fully connected structural neural network to simulate the neural activity and energy consumption of the network by neural energy coding theory. The numerical simulation result showed that the periodicity of the network energy distribution was positively correlated to the number of neurons and coupling strength, but negatively correlated to signal transmitting delay. Moreover, a relationship was established between the energy distribution feature and the synchronous oscillation of the neural network, which showed that when the proportion of negative energy in power consumption curve was high, the synchronous oscillation of the neural network was apparent. In addition, comparison with the simulation result of structural neural network based on the Wang-Zhang biophysical model of neurons showed that both models were essentially consistent.

Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic

NASA Astrophysics Data System (ADS)

Li, Yan; Dai, Shifang; Wu, Weiwei

2016-12-01

Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.

An adaptive distributed data aggregation based on RCPC for wireless sensor networks

NASA Astrophysics Data System (ADS)

Hua, Guogang; Chen, Chang Wen

2006-05-01

One of the most important design issues in wireless sensor networks is energy efficiency. Data aggregation has significant impact on the energy efficiency of the wireless sensor networks. With massive deployment of sensor nodes and limited energy supply, data aggregation has been considered as an essential paradigm for data collection in sensor networks. Recently, distributed source coding has been demonstrated to possess several advantages in data aggregation for wireless sensor networks. Distributed source coding is able to encode sensor data with lower bit rate without direct communication among sensor nodes. To ensure reliable and high throughput transmission with the aggregated data, we proposed in this research a progressive transmission and decoding of Rate-Compatible Punctured Convolutional (RCPC) coded data aggregation with distributed source coding. Our proposed 1/2 RSC codes with Viterbi algorithm for distributed source coding are able to guarantee that, even without any correlation between the data, the decoder can always decode the data correctly without wasting energy. The proposed approach achieves two aspects in adaptive data aggregation for wireless sensor networks. First, the RCPC coding facilitates adaptive compression corresponding to the correlation of the sensor data. When the data correlation is high, higher compression ration can be achieved. Otherwise, lower compression ratio will be achieved. Second, the data aggregation is adaptively accumulated. There is no waste of energy in the transmission; even there is no correlation among the data, the energy consumed is at the same level as raw data collection. Experimental results have shown that the proposed distributed data aggregation based on RCPC is able to achieve high throughput and low energy consumption data collection for wireless sensor networks

Continuous-variable quantum network coding for coherent states

NASA Astrophysics Data System (ADS)

Shang, Tao; Li, Ke; Liu, Jian-wei

2017-04-01

As far as the spectral characteristic of quantum information is concerned, the existing quantum network coding schemes can be looked on as the discrete-variable quantum network coding schemes. Considering the practical advantage of continuous variables, in this paper, we explore two feasible continuous-variable quantum network coding (CVQNC) schemes. Basic operations and CVQNC schemes are both provided. The first scheme is based on Gaussian cloning and ADD/SUB operators and can transmit two coherent states across with a fidelity of 1/2, while the second scheme utilizes continuous-variable quantum teleportation and can transmit two coherent states perfectly. By encoding classical information on quantum states, quantum network coding schemes can be utilized to transmit classical information. Scheme analysis shows that compared with the discrete-variable paradigms, the proposed CVQNC schemes provide better network throughput from the viewpoint of classical information transmission. By modulating the amplitude and phase quadratures of coherent states with classical characters, the first scheme and the second scheme can transmit 4{log _2}N and 2{log _2}N bits of information by a single network use, respectively.

On optimal designs of transparent WDM networks with 1 + 1 protection leveraged by all-optical XOR network coding schemes

NASA Astrophysics Data System (ADS)

Dao, Thanh Hai

2018-01-01

Network coding techniques are seen as the new dimension to improve the network performances thanks to the capability of utilizing network resources more efficiently. Indeed, the application of network coding to the realm of failure recovery in optical networks has been marking a major departure from traditional protection schemes as it could potentially achieve both rapid recovery and capacity improvement, challenging the prevailing wisdom of trading capacity efficiency for speed recovery and vice versa. In this context, the maturing of all-optical XOR technologies appears as a good match to the necessity of a more efficient protection in transparent optical networks. In addressing this opportunity, we propose to use a practical all-optical XOR network coding to leverage the conventional 1 + 1 optical path protection in transparent WDM optical networks. The network coding-assisted protection solution combines protection flows of two demands sharing the same destination node in supportive conditions, paving the way for reducing the backup capacity. A novel mathematical model taking into account the operation of new protection scheme for optimal network designs is formulated as the integer linear programming. Numerical results based on extensive simulations on realistic topologies, COST239 and NSFNET networks, are presented to highlight the benefits of our proposal compared to the conventional approach in terms of wavelength resources efficiency and network throughput.

An efficient and reliable geographic routing protocol based on partial network coding for underwater sensor networks.

PubMed

Hao, Kun; Jin, Zhigang; Shen, Haifeng; Wang, Ying

2015-05-28

Efficient routing protocols for data packet delivery are crucial to underwater sensor networks (UWSNs). However, communication in UWSNs is a challenging task because of the characteristics of the acoustic channel. Network coding is a promising technique for efficient data packet delivery thanks to the broadcast nature of acoustic channels and the relatively high computation capabilities of the sensor nodes. In this work, we present GPNC, a novel geographic routing protocol for UWSNs that incorporates partial network coding to encode data packets and uses sensor nodes' location information to greedily forward data packets to sink nodes. GPNC can effectively reduce network delays and retransmissions of redundant packets causing additional network energy consumption. Simulation results show that GPNC can significantly improve network throughput and packet delivery ratio, while reducing energy consumption and network latency when compared with other routing protocols.

Medical reliable network using concatenated channel codes through GSM network.

PubMed

Ahmed, Emtithal; Kohno, Ryuji

2013-01-01

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

A Novel Design of Reconfigurable Wavelength-Time Optical Codes to Enhance Security in Optical CDMA Networks

NASA Astrophysics Data System (ADS)

Nasaruddin; Tsujioka, Tetsuo

An optical CDMA (OCDMA) system is a flexible technology for future broadband multiple access networks. A secure OCDMA network in broadband optical access technologies is also becoming an issue of great importance. In this paper, we propose novel reconfigurable wavelength-time (W-T) optical codes that lead to secure transmission in OCDMA networks. The proposed W-T optical codes are constructed by using quasigroups (QGs) for wavelength hopping and one-dimensional optical orthogonal codes (OOCs) for time spreading; we call them QGs/OOCs. Both QGs and OOCs are randomly generated by a computer search to ensure that an eavesdropper could not improve its interception performance by making use of the coding structure. Then, the proposed reconfigurable QGs/OOCs can provide more codewords, and many different code set patterns, which differ in both wavelength and time positions for given code parameters. Moreover, the bit error probability of the proposed codes is analyzed numerically. To realize the proposed codes, a secure system is proposed by employing reconfigurable encoders/decoders based on array waveguide gratings (AWGs), which allow the users to change their codeword patterns to protect against eavesdropping. Finally, the probability of breaking a certain codeword in the proposed system is evaluated analytically. The results show that the proposed codes and system can provide a large codeword pattern, and decrease the probability of breaking a certain codeword, to enhance OCDMA network security.

A method of non-contact reading code based on computer vision

NASA Astrophysics Data System (ADS)

Zhang, Chunsen; Zong, Xiaoyu; Guo, Bingxuan

2018-03-01

With the purpose of guarantee the computer information exchange security between internal and external network (trusted network and un-trusted network), A non-contact Reading code method based on machine vision has been proposed. Which is different from the existing network physical isolation method. By using the computer monitors, camera and other equipment. Deal with the information which will be on exchanged, Include image coding ,Generate the standard image , Display and get the actual image , Calculate homography matrix, Image distort correction and decoding in calibration, To achieve the computer information security, Non-contact, One-way transmission between the internal and external network , The effectiveness of the proposed method is verified by experiments on real computer text data, The speed of data transfer can be achieved 24kb/s. The experiment shows that this algorithm has the characteristics of high security, fast velocity and less loss of information. Which can meet the daily needs of the confidentiality department to update the data effectively and reliably, Solved the difficulty of computer information exchange between Secret network and non-secret network, With distinctive originality, practicability, and practical research value.

A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks

PubMed Central

Wang, Hao; Wang, Shilian; Bu, Renfei; Zhang, Eryang

2017-01-01

Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs. PMID:28786915

Maximization Network Throughput Based on Improved Genetic Algorithm and Network Coding for Optical Multicast Networks

NASA Astrophysics Data System (ADS)

Wei, Chengying; Xiong, Cuilian; Liu, Huanlin

2017-12-01

Maximal multicast stream algorithm based on network coding (NC) can improve the network's throughput for wavelength-division multiplexing (WDM) networks, which however is far less than the network's maximal throughput in terms of theory. And the existing multicast stream algorithms do not give the information distribution pattern and routing in the meantime. In the paper, an improved genetic algorithm is brought forward to maximize the optical multicast throughput by NC and to determine the multicast stream distribution by hybrid chromosomes construction for multicast with single source and multiple destinations. The proposed hybrid chromosomes are constructed by the binary chromosomes and integer chromosomes, while the binary chromosomes represent optical multicast routing and the integer chromosomes indicate the multicast stream distribution. A fitness function is designed to guarantee that each destination can receive the maximum number of decoding multicast streams. The simulation results showed that the proposed method is far superior over the typical maximal multicast stream algorithms based on NC in terms of network throughput in WDM networks.

Container-code recognition system based on computer vision and deep neural networks

NASA Astrophysics Data System (ADS)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks.

PubMed

Yu, Shidi; Liu, Xiao; Liu, Anfeng; Xiong, Naixue; Cai, Zhiping; Wang, Tian

2018-05-10

Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD) scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1) with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2) As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3) The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that the proposed ABRCD scheme shows better performance in different broadcast situations. Compared to previous schemes, the transmission delay is reduced by 41.11~78.42%, the number of broadcasts is reduced by 36.18~94.27% and the energy utilization ratio is improved up to 583.42%, while the network lifetime can be prolonged up to 274.99%.

An Adaption Broadcast Radius-Based Code Dissemination Scheme for Low Energy Wireless Sensor Networks

PubMed Central

Yu, Shidi; Liu, Xiao; Cai, Zhiping; Wang, Tian

2018-01-01

Due to the Software Defined Network (SDN) technology, Wireless Sensor Networks (WSNs) are getting wider application prospects for sensor nodes that can get new functions after updating program codes. The issue of disseminating program codes to every node in the network with minimum delay and energy consumption have been formulated and investigated in the literature. The minimum-transmission broadcast (MTB) problem, which aims to reduce broadcast redundancy, has been well studied in WSNs where the broadcast radius is assumed to be fixed in the whole network. In this paper, an Adaption Broadcast Radius-based Code Dissemination (ABRCD) scheme is proposed to reduce delay and improve energy efficiency in duty cycle-based WSNs. In the ABCRD scheme, a larger broadcast radius is set in areas with more energy left, generating more optimized performance than previous schemes. Thus: (1) with a larger broadcast radius, program codes can reach the edge of network from the source in fewer hops, decreasing the number of broadcasts and at the same time, delay. (2) As the ABRCD scheme adopts a larger broadcast radius for some nodes, program codes can be transmitted to more nodes in one broadcast transmission, diminishing the number of broadcasts. (3) The larger radius in the ABRCD scheme causes more energy consumption of some transmitting nodes, but radius enlarging is only conducted in areas with an energy surplus, and energy consumption in the hot-spots can be reduced instead due to some nodes transmitting data directly to sink without forwarding by nodes in the original hot-spot, thus energy consumption can almost reach a balance and network lifetime can be prolonged. The proposed ABRCD scheme first assigns a broadcast radius, which doesn’t affect the network lifetime, to nodes having different distance to the code source, then provides an algorithm to construct a broadcast backbone. In the end, a comprehensive performance analysis and simulation result shows that the proposed ABRCD scheme shows better performance in different broadcast situations. Compared to previous schemes, the transmission delay is reduced by 41.11~78.42%, the number of broadcasts is reduced by 36.18~94.27% and the energy utilization ratio is improved up to 583.42%, while the network lifetime can be prolonged up to 274.99%. PMID:29748525

A reaction-diffusion-based coding rate control mechanism for camera sensor networks.

PubMed

Yamamoto, Hiroshi; Hyodo, Katsuya; Wakamiya, Naoki; Murata, Masayuki

2010-01-01

A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal.

Three-tier multi-granularity switching system based on PCE

NASA Astrophysics Data System (ADS)

Wang, Yubao; Sun, Hao; Liu, Yanfei

2017-10-01

With the growing demand for business communications, electrical signal processing optical path switching can't meet the demand. The multi-granularity switch system that can improve node routing and switching capabilities came into being. In the traditional network, each node is responsible for calculating the path; synchronize the whole network state, which will increase the burden on the network, so the concept of path calculation element (PCE) is proposed. The PCE is responsible for routing and allocating resources in the network1. In the traditional band-switched optical network, the wavelength is used as the basic routing unit, resulting in relatively low wavelength utilization. Due to the limitation of wavelength continuity, the routing design of the band technology becomes complicated, which directly affects the utilization of the system. In this paper, optical code granularity is adopted. There is no continuity of the optical code, and the number of optical codes is more flexible than the wavelength. For the introduction of optical code switching, we propose a Code Group Routing Entity (CGRE) algorithm. In short, the combination of three-tier multi-granularity optical switching system and PCE can simplify the network structure, reduce the node load, and enhance the network scalability and survivability. Realize the intelligentization of optical network.

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

Finite-SNR analysis for partial relaying cooperation with channel coding and opportunistic relay selection

NASA Astrophysics Data System (ADS)

Vu, Thang X.; Duhamel, Pierre; Chatzinotas, Symeon; Ottersten, Bjorn

2017-12-01

This work studies the performance of a cooperative network which consists of two channel-coded sources, multiple relays, and one destination. To achieve high spectral efficiency, we assume that a single time slot is dedicated to relaying. Conventional network-coded-based cooperation (NCC) selects the best relay which uses network coding to serve the two sources simultaneously. The bit error rate (BER) performance of NCC with channel coding, however, is still unknown. In this paper, we firstly study the BER of NCC via a closed-form expression and analytically show that NCC only achieves diversity of order two regardless of the number of available relays and the channel code. Secondly, we propose a novel partial relaying-based cooperation (PARC) scheme to improve the system diversity in the finite signal-to-noise ratio (SNR) regime. In particular, closed-form expressions for the system BER and diversity order of PARC are derived as a function of the operating SNR value and the minimum distance of the channel code. We analytically show that the proposed PARC achieves full (instantaneous) diversity order in the finite SNR regime, given that an appropriate channel code is used. Finally, numerical results verify our analysis and demonstrate a large SNR gain of PARC over NCC in the SNR region of interest.

Smart photonic networks and computer security for image data

NASA Astrophysics Data System (ADS)

Campello, Jorge; Gill, John T.; Morf, Martin; Flynn, Michael J.

1998-02-01

Work reported here is part of a larger project on 'Smart Photonic Networks and Computer Security for Image Data', studying the interactions of coding and security, switching architecture simulations, and basic technologies. Coding and security: coding methods that are appropriate for data security in data fusion networks were investigated. These networks have several characteristics that distinguish them form other currently employed networks, such as Ethernet LANs or the Internet. The most significant characteristics are very high maximum data rates; predominance of image data; narrowcasting - transmission of data form one source to a designated set of receivers; data fusion - combining related data from several sources; simple sensor nodes with limited buffering. These characteristics affect both the lower level network design and the higher level coding methods.Data security encompasses privacy, integrity, reliability, and availability. Privacy, integrity, and reliability can be provided through encryption and coding for error detection and correction. Availability is primarily a network issue; network nodes must be protected against failure or routed around in the case of failure. One of the more promising techniques is the use of 'secret sharing'. We consider this method as a special case of our new space-time code diversity based algorithms for secure communication. These algorithms enable us to exploit parallelism and scalable multiplexing schemes to build photonic network architectures. A number of very high-speed switching and routing architectures and their relationships with very high performance processor architectures were studied. Indications are that routers for very high speed photonic networks can be designed using the very robust and distributed TCP/IP protocol, if suitable processor architecture support is available.

Trace Replay and Network Simulation Tool

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

Acun, Bilge; Jain, Nikhil; Bhatele, Abhinav

2015-03-23

TraceR is a trace reply tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performances and understanding network behavior by simulating messaging in High Performance Computing applications on interconnection networks.

Trace Replay and Network Simulation Tool

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

Jain, Nikhil; Bhatele, Abhinav; Acun, Bilge

TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.

GLOBECOM '87 - Global Telecommunications Conference, Tokyo, Japan, Nov. 15-18, 1987, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

The present conference on global telecommunications discusses topics in the fields of Integrated Services Digital Network (ISDN) technology field trial planning and results to date, motion video coding, ISDN networking, future network communications security, flexible and intelligent voice/data networks, Asian and Pacific lightwave and radio systems, subscriber radio systems, the performance of distributed systems, signal processing theory, satellite communications modulation and coding, and terminals for the handicapped. Also discussed are knowledge-based technologies for communications systems, future satellite transmissions, high quality image services, novel digital signal processors, broadband network access interface, traffic engineering for ISDN design and planning, telecommunications software, coherent optical communications, multimedia terminal systems, advanced speed coding, portable and mobile radio communications, multi-Gbit/second lightwave transmission systems, enhanced capability digital terminals, communications network reliability, advanced antimultipath fading techniques, undersea lightwave transmission, image coding, modulation and synchronization, adaptive signal processing, integrated optical devices, VLSI technologies for ISDN, field performance of packet switching, CSMA protocols, optical transport system architectures for broadband ISDN, mobile satellite communications, indoor wireless communication, echo cancellation in communications, and distributed network algorithms.

Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

NASA Astrophysics Data System (ADS)

Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik

2015-05-01

In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.

Combining Topological Hardware and Topological Software: Color-Code Quantum Computing with Topological Superconductor Networks

NASA Astrophysics Data System (ADS)

Litinski, Daniel; Kesselring, Markus S.; Eisert, Jens; von Oppen, Felix

2017-07-01

We present a scalable architecture for fault-tolerant topological quantum computation using networks of voltage-controlled Majorana Cooper pair boxes and topological color codes for error correction. Color codes have a set of transversal gates which coincides with the set of topologically protected gates in Majorana-based systems, namely, the Clifford gates. In this way, we establish color codes as providing a natural setting in which advantages offered by topological hardware can be combined with those arising from topological error-correcting software for full-fledged fault-tolerant quantum computing. We provide a complete description of our architecture, including the underlying physical ingredients. We start by showing that in topological superconductor networks, hexagonal cells can be employed to serve as physical qubits for universal quantum computation, and we present protocols for realizing topologically protected Clifford gates. These hexagonal-cell qubits allow for a direct implementation of open-boundary color codes with ancilla-free syndrome read-out and logical T gates via magic-state distillation. For concreteness, we describe how the necessary operations can be implemented using networks of Majorana Cooper pair boxes, and we give a feasibility estimate for error correction in this architecture. Our approach is motivated by nanowire-based networks of topological superconductors, but it could also be realized in alternative settings such as quantum-Hall-superconductor hybrids.

Performance improvement of optical CDMA networks with stochastic artificial bee colony optimization technique

NASA Astrophysics Data System (ADS)

Panda, Satyasen

2018-05-01

This paper proposes a modified artificial bee colony optimization (ABC) algorithm based on levy flight swarm intelligence referred as artificial bee colony levy flight stochastic walk (ABC-LFSW) optimization for optical code division multiple access (OCDMA) network. The ABC-LFSW algorithm is used to solve asset assignment problem based on signal to noise ratio (SNR) optimization in OCDM networks with quality of service constraints. The proposed optimization using ABC-LFSW algorithm provides methods for minimizing various noises and interferences, regulating the transmitted power and optimizing the network design for improving the power efficiency of the optical code path (OCP) from source node to destination node. In this regard, an optical system model is proposed for improving the network performance with optimized input parameters. The detailed discussion and simulation results based on transmitted power allocation and power efficiency of OCPs are included. The experimental results prove the superiority of the proposed network in terms of power efficiency and spectral efficiency in comparison to networks without any power allocation approach.

Architecture design and performance evaluation of multigranularity optical networks based on optical code division multiplexing

NASA Astrophysics Data System (ADS)

Huang, Shaowei; Baba, Ken-Ichi; Murata, Masayuki; Kitayama, Ken-Ichi

2006-12-01

In traditional lambda-based multigranularity optical networks, a lambda is always treated as the basic routing unit, resulting in low wavelength utilization. On the basis of optical code division multiplexing (OCDM) technology, a novel OCDM-based multigranularity optical cross-connect (MG-OXC) is proposed. Compared with the traditional lambda-based MG-OXC, its switching capability has been extended to support fiber switching, waveband switching, lambda switching, and OCDM switching. In a network composed of OCDM-based MG-OXCs, a single wavelength can be shared by distinct label switched paths (LSPs) called OCDM-LSPs, and OCDM-LSP switching can be implemented in the optical domain. To improve the network flexibility for an OCDM-LSP provisioning, two kinds of switches enabling hybrid optical code (OC)-wavelength conversion are designed. Simulation results indicate that a blocking probability reduction of 2 orders can be obtained by deploying only five OCs to a single wavelength. Furthermore, compared with time-division-multiplexing LSP (TDM-LSP), owing to the asynchronous accessibility and the OC conversion, OCDM-LSPs have been shown to permit a simpler switch architecture and achieve better blocking performance than TDM-LSPs.

Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding

NASA Astrophysics Data System (ADS)

Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang

2009-12-01

Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.

BGen: A UML Behavior Network Generator Tool

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

2010-01-01

BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

Connectivity Restoration in Wireless Sensor Networks via Space Network Coding.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing

2017-04-20

The problem of finding the number and optimal positions of relay nodes for restoring the network connectivity in partitioned Wireless Sensor Networks (WSNs) is Non-deterministic Polynomial-time hard (NP-hard) and thus heuristic methods are preferred to solve it. This paper proposes a novel polynomial time heuristic algorithm, namely, Relay Placement using Space Network Coding (RPSNC), to solve this problem, where Space Network Coding, also called Space Information Flow (SIF), is a new research paradigm that studies network coding in Euclidean space, in which extra relay nodes can be introduced to reduce the cost of communication. Unlike contemporary schemes that are often based on Minimum Spanning Tree (MST), Euclidean Steiner Minimal Tree (ESMT) or a combination of MST with ESMT, RPSNC is a new min-cost multicast space network coding approach that combines Delaunay triangulation and non-uniform partitioning techniques for generating a number of candidate relay nodes, and then linear programming is applied for choosing the optimal relay nodes and computing their connection links with terminals. Subsequently, an equilibrium method is used to refine the locations of the optimal relay nodes, by moving them to balanced positions. RPSNC can adapt to any density distribution of relay nodes and terminals, as well as any density distribution of terminals. The performance and complexity of RPSNC are analyzed and its performance is validated through simulation experiments.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Hybrid scheduling mechanisms for Next-generation Passive Optical Networks based on network coding

NASA Astrophysics Data System (ADS)

Zhao, Jijun; Bai, Wei; Liu, Xin; Feng, Nan; Maier, Martin

2014-10-01

Network coding (NC) integrated into Passive Optical Networks (PONs) is regarded as a promising solution to achieve higher throughput and energy efficiency. To efficiently support multimedia traffic under this new transmission mode, novel NC-based hybrid scheduling mechanisms for Next-generation PONs (NG-PONs) including energy management, time slot management, resource allocation, and Quality-of-Service (QoS) scheduling are proposed in this paper. First, we design an energy-saving scheme that is based on Bidirectional Centric Scheduling (BCS) to reduce the energy consumption of both the Optical Line Terminal (OLT) and Optical Network Units (ONUs). Next, we propose an intra-ONU scheduling and an inter-ONU scheduling scheme, which takes NC into account to support service differentiation and QoS assurance. The presented simulation results show that BCS achieves higher energy efficiency under low traffic loads, clearly outperforming the alternative NC-based Upstream Centric Scheduling (UCS) scheme. Furthermore, BCS is shown to provide better QoS assurance.

Special issue on network coding

NASA Astrophysics Data System (ADS)

Monteiro, Francisco A.; Burr, Alister; Chatzigeorgiou, Ioannis; Hollanti, Camilla; Krikidis, Ioannis; Seferoglu, Hulya; Skachek, Vitaly

2017-12-01

Future networks are expected to depart from traditional routing schemes in order to embrace network coding (NC)-based schemes. These have created a lot of interest both in academia and industry in recent years. Under the NC paradigm, symbols are transported through the network by combining several information streams originating from the same or different sources. This special issue contains thirteen papers, some dealing with design aspects of NC and related concepts (e.g., fountain codes) and some showcasing the application of NC to new services and technologies, such as data multi-view streaming of video or underwater sensor networks. One can find papers that show how NC turns data transmission more robust to packet losses, faster to decode, and more resilient to network changes, such as dynamic topologies and different user options, and how NC can improve the overall throughput. This issue also includes papers showing that NC principles can be used at different layers of the networks (including the physical layer) and how the same fundamental principles can lead to new distributed storage systems. Some of the papers in this issue have a theoretical nature, including code design, while others describe hardware testbeds and prototypes.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

FPGA implementation of advanced FEC schemes for intelligent aggregation networks

NASA Astrophysics Data System (ADS)

Zou, Ding; Djordjevic, Ivan B.

2016-02-01

In state-of-the-art fiber-optics communication systems the fixed forward error correction (FEC) and constellation size are employed. While it is important to closely approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithm; rate-adaptive techniques, which enable increased information rates over short links and reliable transmission over long links, are likely to become more important with ever-increasing network traffic demands. In this invited paper, we describe a rate adaptive non-binary LDPC coding technique, and demonstrate its flexibility and good performance exhibiting no error floor at BER down to 10-15 in entire code rate range, by FPGA-based emulation, making it a viable solution in the next-generation high-speed intelligent aggregation networks.

Mixture block coding with progressive transmission in packet video. Appendix 1: Item 2. M.S. Thesis

NASA Technical Reports Server (NTRS)

Chen, Yun-Chung

1989-01-01

Video transmission will become an important part of future multimedia communication because of dramatically increasing user demand for video, and rapid evolution of coding algorithm and VLSI technology. Video transmission will be part of the broadband-integrated services digital network (B-ISDN). Asynchronous transfer mode (ATM) is a viable candidate for implementation of B-ISDN due to its inherent flexibility, service independency, and high performance. According to the characteristics of ATM, the information has to be coded into discrete cells which travel independently in the packet switching network. A practical realization of an ATM video codec called Mixture Block Coding with Progressive Transmission (MBCPT) is presented. This variable bit rate coding algorithm shows how a constant quality performance can be obtained according to user demand. Interactions between codec and network are emphasized including packetization, service synchronization, flow control, and error recovery. Finally, some simulation results based on MBCPT coding with error recovery are presented.

Hybrid optical CDMA-FSO communications network under spatially correlated gamma-gamma scintillation.

PubMed

Jurado-Navas, Antonio; Raddo, Thiago R; Garrido-Balsells, José María; Borges, Ben-Hur V; Olmos, Juan José Vegas; Monroy, Idelfonso Tafur

2016-07-25

In this paper, we propose a new hybrid network solution based on asynchronous optical code-division multiple-access (OCDMA) and free-space optical (FSO) technologies for last-mile access networks, where fiber deployment is impractical. The architecture of the proposed hybrid OCDMA-FSO network is thoroughly described. The users access the network in a fully asynchronous manner by means of assigned fast frequency hopping (FFH)-based codes. In the FSO receiver, an equal gain-combining technique is employed along with intensity modulation and direct detection. New analytical formalisms for evaluating the average bit error rate (ABER) performance are also proposed. These formalisms, based on the spatially correlated gamma-gamma statistical model, are derived considering three distinct scenarios, namely, uncorrelated, totally correlated, and partially correlated channels. Numerical results show that users can successfully achieve error-free ABER levels for the three scenarios considered as long as forward error correction (FEC) algorithms are employed. Therefore, OCDMA-FSO networks can be a prospective alternative to deliver high-speed communication services to access networks with deficient fiber infrastructure.

Interactive Video Coding and Transmission over Heterogeneous Wired-to-Wireless IP Networks Using an Edge Proxy

NASA Astrophysics Data System (ADS)

Pei, Yong; Modestino, James W.

2004-12-01

Digital video delivered over wired-to-wireless networks is expected to suffer quality degradation from both packet loss and bit errors in the payload. In this paper, the quality degradation due to packet loss and bit errors in the payload are quantitatively evaluated and their effects are assessed. We propose the use of a concatenated forward error correction (FEC) coding scheme employing Reed-Solomon (RS) codes and rate-compatible punctured convolutional (RCPC) codes to protect the video data from packet loss and bit errors, respectively. Furthermore, the performance of a joint source-channel coding (JSCC) approach employing this concatenated FEC coding scheme for video transmission is studied. Finally, we describe an improved end-to-end architecture using an edge proxy in a mobile support station to implement differential error protection for the corresponding channel impairments expected on the two networks. Results indicate that with an appropriate JSCC approach and the use of an edge proxy, FEC-based error-control techniques together with passive error-recovery techniques can significantly improve the effective video throughput and lead to acceptable video delivery quality over time-varying heterogeneous wired-to-wireless IP networks.

Supervised Learning Based on Temporal Coding in Spiking Neural Networks.

PubMed

Mostafa, Hesham

2017-08-01

Gradient descent training techniques are remarkably successful in training analog-valued artificial neural networks (ANNs). Such training techniques, however, do not transfer easily to spiking networks due to the spike generation hard nonlinearity and the discrete nature of spike communication. We show that in a feedforward spiking network that uses a temporal coding scheme where information is encoded in spike times instead of spike rates, the network input-output relation is differentiable almost everywhere. Moreover, this relation is piecewise linear after a transformation of variables. Methods for training ANNs thus carry directly to the training of such spiking networks as we show when training on the permutation invariant MNIST task. In contrast to rate-based spiking networks that are often used to approximate the behavior of ANNs, the networks we present spike much more sparsely and their behavior cannot be directly approximated by conventional ANNs. Our results highlight a new approach for controlling the behavior of spiking networks with realistic temporal dynamics, opening up the potential for using these networks to process spike patterns with complex temporal information.

Data Delivery Method Based on Neighbor Nodes' Information in a Mobile Ad Hoc Network

PubMed Central

Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

2014-01-01

This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow. PMID:24672371

Data delivery method based on neighbor nodes' information in a mobile ad hoc network.

PubMed

Kashihara, Shigeru; Hayashi, Takuma; Taenaka, Yuzo; Okuda, Takeshi; Yamaguchi, Suguru

2014-01-01

This paper proposes a data delivery method based on neighbor nodes' information to achieve reliable communication in a mobile ad hoc network (MANET). In a MANET, it is difficult to deliver data reliably due to instabilities in network topology and wireless network condition which result from node movement. To overcome such unstable communication, opportunistic routing and network coding schemes have lately attracted considerable attention. Although an existing method that employs such schemes, MAC-independent opportunistic routing and encoding (MORE), Chachulski et al. (2007), improves the efficiency of data delivery in an unstable wireless mesh network, it does not address node movement. To efficiently deliver data in a MANET, the method proposed in this paper thus first employs the same opportunistic routing and network coding used in MORE and also uses the location information and transmission probabilities of neighbor nodes to adapt to changeable network topology and wireless network condition. The simulation experiments showed that the proposed method can achieve efficient data delivery with low network load when the movement speed is relatively slow.

Opportunistic quantum network coding based on quantum teleportation

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Authorship attribution of source code by using back propagation neural network based on particle swarm optimization

PubMed Central

Xu, Guoai; Li, Qi; Guo, Yanhui; Zhang, Miao

2017-01-01

Authorship attribution is to identify the most likely author of a given sample among a set of candidate known authors. It can be not only applied to discover the original author of plain text, such as novels, blogs, emails, posts etc., but also used to identify source code programmers. Authorship attribution of source code is required in diverse applications, ranging from malicious code tracking to solving authorship dispute or software plagiarism detection. This paper aims to propose a new method to identify the programmer of Java source code samples with a higher accuracy. To this end, it first introduces back propagation (BP) neural network based on particle swarm optimization (PSO) into authorship attribution of source code. It begins by computing a set of defined feature metrics, including lexical and layout metrics, structure and syntax metrics, totally 19 dimensions. Then these metrics are input to neural network for supervised learning, the weights of which are output by PSO and BP hybrid algorithm. The effectiveness of the proposed method is evaluated on a collected dataset with 3,022 Java files belong to 40 authors. Experiment results show that the proposed method achieves 91.060% accuracy. And a comparison with previous work on authorship attribution of source code for Java language illustrates that this proposed method outperforms others overall, also with an acceptable overhead. PMID:29095934

Braiding by Majorana tracking and long-range CNOT gates with color codes

NASA Astrophysics Data System (ADS)

Litinski, Daniel; von Oppen, Felix

2017-11-01

Color-code quantum computation seamlessly combines Majorana-based hardware with topological error correction. Specifically, as Clifford gates are transversal in two-dimensional color codes, they enable the use of the Majoranas' non-Abelian statistics for gate operations at the code level. Here, we discuss the implementation of color codes in arrays of Majorana nanowires that avoid branched networks such as T junctions, thereby simplifying their realization. We show that, in such implementations, non-Abelian statistics can be exploited without ever performing physical braiding operations. Physical braiding operations are replaced by Majorana tracking, an entirely software-based protocol which appropriately updates the Majoranas involved in the color-code stabilizer measurements. This approach minimizes the required hardware operations for single-qubit Clifford gates. For Clifford completeness, we combine color codes with surface codes, and use color-to-surface-code lattice surgery for long-range multitarget CNOT gates which have a time overhead that grows only logarithmically with the physical distance separating control and target qubits. With the addition of magic state distillation, our architecture describes a fault-tolerant universal quantum computer in systems such as networks of tetrons, hexons, or Majorana box qubits, but can also be applied to nontopological qubit platforms.

High-throughput and low-latency 60GHz small-cell network architectures over radio-over-fiber technologies

NASA Astrophysics Data System (ADS)

Pleros, N.; Kalfas, G.; Mitsolidou, C.; Vagionas, C.; Tsiokos, D.; Miliou, A.

2017-01-01

Future broadband access networks in the 5G framework will need to be bilateral, exploiting both optical and wireless technologies. This paper deals with new approaches and synergies on radio-over-fiber (RoF) technologies and how those can be leveraged to seamlessly converge wireless technology for agility and mobility with passive optical networks (PON)-based backhauling. The proposed convergence paradigm is based upon a holistic network architecture mixing mm-wave wireless access with photonic integration, dynamic capacity allocation and network coding schemes to enable high bandwidth and low-latency fixed and 60GHz wireless personal area communications for gigabit rate per user, proposing and deploying on top a Medium-Transparent MAC (MT-MAC) protocol as a low-latency bandwidth allocation mechanism. We have evaluated alternative network topologies between the central office (CO) and the access point module (APM) for data rates up to 2.5 Gb/s and SC frequencies up to 60 GHz. Optical network coding is demonstrated for SCM-based signaling to enhance bandwidth utilization and facilitate optical-wireless convergence in 5G applications, reporting medium-transparent network coding directly at the physical layer between end-users communicating over a RoF infrastructure. Towards equipping the physical layer with the appropriate agility to support MT-MAC protocols, a monolithic InP-based Remote Antenna Unit optoelectronic PIC interface is shown that ensures control over the optical resource allocation assisting at the same time broadband wireless service. Finally, the MT-MAC protocol is analysed and simulation and analytical theoretical results are presented that are found to be in good agreement confirming latency values lower than 1msec for small- to mid-load conditions.

ANN modeling of DNA sequences: new strategies using DNA shape code.

PubMed

Parbhane, R V; Tambe, S S; Kulkarni, B D

2000-09-01

Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.

Wireless visual sensor network resource allocation using cross-layer optimization

NASA Astrophysics Data System (ADS)

Bentley, Elizabeth S.; Matyjas, John D.; Medley, Michael J.; Kondi, Lisimachos P.

2009-01-01

In this paper, we propose an approach to manage network resources for a Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our approach allows one to determine the capacity of the visual sensor network based on the number of nodes and the quality of video that must be transmitted. For bandwidth-limited applications, one can also determine the minimum bandwidth needed to accommodate a number of nodes with a specific target chip rate. Video captured by a sensor node camera is encoded and decoded using the H.264 video codec by a centralized control unit at the network layer. To reduce the computational complexity of the solution, Universal Rate-Distortion Characteristics (URDCs) are obtained experimentally to relate bit error probabilities to the distortion of corrupted video. Bit error rates are found first by using Viterbi's upper bounds on the bit error probability and second, by simulating nodes transmitting data spread by Total Square Correlation (TSC) codes over a Rayleigh-faded DS-CDMA channel and receiving that data using Auxiliary Vector (AV) filtering.

Empirical evaluation of H.265/HEVC-based dynamic adaptive video streaming over HTTP (HEVC-DASH)

NASA Astrophysics Data System (ADS)

Irondi, Iheanyi; Wang, Qi; Grecos, Christos

2014-05-01

Real-time HTTP streaming has gained global popularity for delivering video content over Internet. In particular, the recent MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard enables on-demand, live, and adaptive Internet streaming in response to network bandwidth fluctuations. Meanwhile, emerging is the new-generation video coding standard, H.265/HEVC (High Efficiency Video Coding) promises to reduce the bandwidth requirement by 50% at the same video quality when compared with the current H.264/AVC standard. However, little existing work has addressed the integration of the DASH and HEVC standards, let alone empirical performance evaluation of such systems. This paper presents an experimental HEVC-DASH system, which is a pull-based adaptive streaming solution that delivers HEVC-coded video content through conventional HTTP servers where the client switches to its desired quality, resolution or bitrate based on the available network bandwidth. Previous studies in DASH have focused on H.264/AVC, whereas we present an empirical evaluation of the HEVC-DASH system by implementing a real-world test bed, which consists of an Apache HTTP Server with GPAC, an MP4Client (GPAC) with open HEVC-based DASH client and a NETEM box in the middle emulating different network conditions. We investigate and analyze the performance of HEVC-DASH by exploring the impact of various network conditions such as packet loss, bandwidth and delay on video quality. Furthermore, we compare the Intra and Random Access profiles of HEVC coding with the Intra profile of H.264/AVC when the correspondingly encoded video is streamed with DASH. Finally, we explore the correlation among the quality metrics and network conditions, and empirically establish under which conditions the different codecs can provide satisfactory performance.

Evolutionary Computation with Spatial Receding Horizon Control to Minimize Network Coding Resources

PubMed Central

Leeson, Mark S.

2014-01-01

The minimization of network coding resources, such as coding nodes and links, is a challenging task, not only because it is a NP-hard problem, but also because the problem scale is huge; for example, networks in real world may have thousands or even millions of nodes and links. Genetic algorithms (GAs) have a good potential of resolving NP-hard problems like the network coding problem (NCP), but as a population-based algorithm, serious scalability and applicability problems are often confronted when GAs are applied to large- or huge-scale systems. Inspired by the temporal receding horizon control in control engineering, this paper proposes a novel spatial receding horizon control (SRHC) strategy as a network partitioning technology, and then designs an efficient GA to tackle the NCP. Traditional network partitioning methods can be viewed as a special case of the proposed SRHC, that is, one-step-wide SRHC, whilst the method in this paper is a generalized N-step-wide SRHC, which can make a better use of global information of network topologies. Besides the SRHC strategy, some useful designs are also reported in this paper. The advantages of the proposed SRHC and GA for the NCP are illustrated by extensive experiments, and they have a good potential of being extended to other large-scale complex problems. PMID:24883371

Video transmission on ATM networks. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Chen, Yun-Chung

1993-01-01

The broadband integrated services digital network (B-ISDN) is expected to provide high-speed and flexible multimedia applications. Multimedia includes data, graphics, image, voice, and video. Asynchronous transfer mode (ATM) is the adopted transport techniques for B-ISDN and has the potential for providing a more efficient and integrated environment for multimedia. It is believed that most broadband applications will make heavy use of visual information. The prospect of wide spread use of image and video communication has led to interest in coding algorithms for reducing bandwidth requirements and improving image quality. The major results of a study on the bridging of network transmission performance and video coding are: Using two representative video sequences, several video source models are developed. The fitness of these models are validated through the use of statistical tests and network queuing performance. A dual leaky bucket algorithm is proposed as an effective network policing function. The concept of the dual leaky bucket algorithm can be applied to a prioritized coding approach to achieve transmission efficiency. A mapping of the performance/control parameters at the network level into equivalent parameters at the video coding level is developed. Based on that, a complete set of principles for the design of video codecs for network transmission is proposed.

A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases

PubMed Central

Yang, Xiaofei; Gao, Lin; Guo, Xingli; Shi, Xinghua; Wu, Hao; Song, Fei; Wang, Bingbo

2014-01-01

Increasing evidence has indicated that long non-coding RNAs (lncRNAs) are implicated in and associated with many complex human diseases. Despite of the accumulation of lncRNA-disease associations, only a few studies had studied the roles of these associations in pathogenesis. In this paper, we investigated lncRNA-disease associations from a network view to understand the contribution of these lncRNAs to complex diseases. Specifically, we studied both the properties of the diseases in which the lncRNAs were implicated, and that of the lncRNAs associated with complex diseases. Regarding the fact that protein coding genes and lncRNAs are involved in human diseases, we constructed a coding-non-coding gene-disease bipartite network based on known associations between diseases and disease-causing genes. We then applied a propagation algorithm to uncover the hidden lncRNA-disease associations in this network. The algorithm was evaluated by leave-one-out cross validation on 103 diseases in which at least two genes were known to be involved, and achieved an AUC of 0.7881. Our algorithm successfully predicted 768 potential lncRNA-disease associations between 66 lncRNAs and 193 diseases. Furthermore, our results for Alzheimer's disease, pancreatic cancer, and gastric cancer were verified by other independent studies. PMID:24498199

Energy coding in biological neural networks

PubMed Central

Zhang, Zhikang

2007-01-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model’s ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function. PMID:19003513

Cardinality enhancement utilizing Sequential Algorithm (SeQ) code in OCDMA system

NASA Astrophysics Data System (ADS)

Fazlina, C. A. S.; Rashidi, C. B. M.; Rahman, A. K.; Aljunid, S. A.

2017-11-01

Optical Code Division Multiple Access (OCDMA) has been important with increasing demand for high capacity and speed for communication in optical networks because of OCDMA technique high efficiency that can be achieved, hence fibre bandwidth is fully used. In this paper we will focus on Sequential Algorithm (SeQ) code with AND detection technique using Optisystem design tool. The result revealed SeQ code capable to eliminate Multiple Access Interference (MAI) and improve Bit Error Rate (BER), Phase Induced Intensity Noise (PIIN) and orthogonally between users in the system. From the results, SeQ shows good performance of BER and capable to accommodate 190 numbers of simultaneous users contrast with existing code. Thus, SeQ code have enhanced the system about 36% and 111% of FCC and DCS code. In addition, SeQ have good BER performance 10-25 at 155 Mbps in comparison with 622 Mbps, 1 Gbps and 2 Gbps bit rate. From the plot graph, 155 Mbps bit rate is suitable enough speed for FTTH and LAN networks. Resolution can be made based on the superior performance of SeQ code. Thus, these codes will give an opportunity in OCDMA system for better quality of service in an optical access network for future generation's usage

Clique-Based Neural Associative Memories with Local Coding and Precoding.

PubMed

Mofrad, Asieh Abolpour; Parker, Matthew G; Ferdosi, Zahra; Tadayon, Mohammad H

2016-08-01

Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.

Fiber-Bragg-Grating-Based Optical Code-Division Multiple Access Passive Optical Network Using Dual-Baseband Modulation Scheme

NASA Astrophysics Data System (ADS)

Lin, Wen-Piao; Wu, He-Long

2005-08-01

We propose a fiber-Bragg-grating (FBG)-based optical code-division multiple access passive optical network (OCDMA-PON) using a dual-baseband modulation scheme. A mathematical model is developed to study the performance of this scheme. According to the analyzed results, this scheme can allow a tolerance of the spectral power distortion (SPD) ratio of 25% with a bit error rate (BER) of 10-9 when the modified pseudorandom noise (PN) code length is 16. Moreover, we set up a simulated system to evaluate the baseband and radio frequency (RF) band transmission characteristics. The simulation results demonstrate that our proposed OCDMA-PON can provide a cost-effective and scalable fiber-to-the-home solution.

Priority-based methods for reducing the impact of packet loss on HEVC encoded video streams

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2013-02-01

The rapid growth in the use of video streaming over IP networks has outstripped the rate at which new network infrastructure has been deployed. These bandwidth-hungry applications now comprise a significant part of all Internet traffic and present major challenges for network service providers. The situation is more acute in mobile networks where the available bandwidth is often limited. Work towards the standardisation of High Efficiency Video Coding (HEVC), the next generation video coding scheme, is currently on track for completion in 2013. HEVC offers the prospect of a 50% improvement in compression over the current H.264 Advanced Video Coding standard (H.264/AVC) for the same quality. However, there has been very little published research on HEVC streaming or the challenges of delivering HEVC streams in resource-constrained network environments. In this paper we consider the problem of adapting an HEVC encoded video stream to meet the bandwidth limitation in a mobile networks environment. Video sequences were encoded using the Test Model under Consideration (TMuC HM6) for HEVC. Network abstraction layers (NAL) units were packetized, on a one NAL unit per RTP packet basis, and transmitted over a realistic hybrid wired/wireless testbed configured with dynamically changing network path conditions and multiple independent network paths from the streamer to the client. Two different schemes for the prioritisation of RTP packets, based on the NAL units they contain, have been implemented and empirically compared using a range of video sequences, encoder configurations, bandwidths and network topologies. In the first prioritisation method the importance of an RTP packet was determined by the type of picture and the temporal switching point information carried in the NAL unit header. Packets containing parameter set NAL units and video coding layer (VCL) NAL units of the instantaneous decoder refresh (IDR) and the clean random access (CRA) pictures were given the highest priority followed by NAL units containing pictures used as reference pictures from which others can be predicted. The second method assigned a priority to each NAL unit based on the rate-distortion cost of the VCL coding units contained in the NAL unit. The sum of the rate-distortion costs of each coding unit contained in a NAL unit was used as the priority weighting. The preliminary results of extensive experiments have shown that all three schemes offered an improvement in PSNR, when comparing original and decoded received streams, over uncontrolled packet loss. Using the first method consistently delivered a significant average improvement of 0.97dB over the uncontrolled scenario while the second method provided a measurable, but less consistent, improvement across the range of testing conditions and encoder configurations.

Layer-based buffer aware rate adaptation design for SHVC video streaming

NASA Astrophysics Data System (ADS)

Gudumasu, Srinivas; Hamza, Ahmed; Asbun, Eduardo; He, Yong; Ye, Yan

2016-09-01

This paper proposes a layer based buffer aware rate adaptation design which is able to avoid abrupt video quality fluctuation, reduce re-buffering latency and improve bandwidth utilization when compared to a conventional simulcast based adaptive streaming system. The proposed adaptation design schedules DASH segment requests based on the estimated bandwidth, dependencies among video layers and layer buffer fullness. Scalable HEVC video coding is the latest state-of-art video coding technique that can alleviate various issues caused by simulcast based adaptive video streaming. With scalable coded video streams, the video is encoded once into a number of layers representing different qualities and/or resolutions: a base layer (BL) and one or more enhancement layers (EL), each incrementally enhancing the quality of the lower layers. Such layer based coding structure allows fine granularity rate adaptation for the video streaming applications. Two video streaming use cases are presented in this paper. The first use case is to stream HD SHVC video over a wireless network where available bandwidth varies, and the performance comparison between proposed layer-based streaming approach and conventional simulcast streaming approach is provided. The second use case is to stream 4K/UHD SHVC video over a hybrid access network that consists of a 5G millimeter wave high-speed wireless link and a conventional wired or WiFi network. The simulation results verify that the proposed layer based rate adaptation approach is able to utilize the bandwidth more efficiently. As a result, a more consistent viewing experience with higher quality video content and minimal video quality fluctuations can be presented to the user.

Network coding based joint signaling and dynamic bandwidth allocation scheme for inter optical network unit communication in passive optical networks

NASA Astrophysics Data System (ADS)

Wei, Pei; Gu, Rentao; Ji, Yuefeng

2014-06-01

As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.

Perceptually tuned low-bit-rate video codec for ATM networks

NASA Astrophysics Data System (ADS)

Chou, Chun-Hsien

1996-02-01

In order to maintain high visual quality in transmitting low bit-rate video signals over asynchronous transfer mode (ATM) networks, a layered coding scheme that incorporates the human visual system (HVS), motion compensation (MC), and conditional replenishment (CR) is presented in this paper. An empirical perceptual model is proposed to estimate the spatio- temporal just-noticeable distortion (STJND) profile for each frame, by which perceptually important (PI) prediction-error signals can be located. Because of the limited channel capacity of the base layer, only coded data of motion vectors, the PI signals within a small strip of the prediction-error image and, if there are remaining bits, the PI signals outside the strip are transmitted by the cells of the base-layer channel. The rest of the coded data are transmitted by the second-layer cells which may be lost due to channel error or network congestion. Simulation results show that visual quality of the reconstructed CIF sequence is acceptable when the capacity of the base-layer channel is allocated with 2 multiplied by 64 kbps and the cells of the second layer are all lost.

Protection of HEVC Video Delivery in Vehicular Networks with RaptorQ Codes

PubMed Central

Martínez-Rach, Miguel; López, Otoniel; Malumbres, Manuel Pérez

2014-01-01

With future vehicles equipped with processing capability, storage, and communications, vehicular networks will become a reality. A vast number of applications will arise that will make use of this connectivity. Some of them will be based on video streaming. In this paper we focus on HEVC video coding standard streaming in vehicular networks and how it deals with packet losses with the aid of RaptorQ, a Forward Error Correction scheme. As vehicular networks are packet loss prone networks, protection mechanisms are necessary if we want to guarantee a minimum level of quality of experience to the final user. We have run simulations to evaluate which configurations fit better in this type of scenarios. PMID:25136675

Phylogenetic Network for European mtDNA

PubMed Central

Finnilä, Saara; Lehtonen, Mervi S.; Majamaa, Kari

2001-01-01

The sequence in the first hypervariable segment (HVS-I) of the control region has been used as a source of evolutionary information in most phylogenetic analyses of mtDNA. Population genetic inference would benefit from a better understanding of the variation in the mtDNA coding region, but, thus far, complete mtDNA sequences have been rare. We determined the nucleotide sequence in the coding region of mtDNA from 121 Finns, by conformation-sensitive gel electrophoresis and subsequent sequencing and by direct sequencing of the D loop. Furthermore, 71 sequences from our previous reports were included, so that the samples represented all the mtDNA haplogroups present in the Finnish population. We found a total of 297 variable sites in the coding region, which allowed the compilation of unambiguous phylogenetic networks. The D loop harbored 104 variable sites, and, in most cases, these could be localized within the coding-region networks, without discrepancies. Interestingly, many homoplasies were detected in the coding region. Nucleotide variation in the rRNA and tRNA genes was 6%, and that in the third nucleotide positions of structural genes amounted to 22% of that in the HVS-I. The complete networks enabled the relationships between the mtDNA haplogroups to be analyzed. Phylogenetic networks based on the entire coding-region sequence in mtDNA provide a rich source for further population genetic studies, and complete sequences make it easier to differentiate between disease-causing mutations and rare polymorphisms. PMID:11349229

Network analysis for the visualization and analysis of qualitative data.

PubMed

Pokorny, Jennifer J; Norman, Alex; Zanesco, Anthony P; Bauer-Wu, Susan; Sahdra, Baljinder K; Saron, Clifford D

2018-03-01

We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures. Here, as a proof of concept, we applied this method to a set of interview transcripts that had been coded in 2 different ways and the resultant network graphs were examined. The creation of network graphs allows researchers an opportunity to view and share their qualitative data in an innovative way that may provide new insights and enhance transparency of the analytical process by which they reach their conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Doctoral Students' Identity Positioning in Networked Learning Environments

ERIC Educational Resources Information Center

Koole, Marguerite; Stack, Sara

2016-01-01

In this study, the authors explored identity positioning as perceived by doctoral learners in online, networked-learning environments. The study examined two distance doctoral programs at a Canadian university. It was a qualitative study based on methodologies involving open coding and discourse analysis. The social positioning cycle, based on…

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

DTIC Science & Technology

2014-09-30

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

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.

Finger Vein Recognition Based on Local Directional Code

PubMed Central

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-01-01

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP. PMID:23202194

Finger vein recognition based on local directional code.

PubMed

Meng, Xianjing; Yang, Gongping; Yin, Yilong; Xiao, Rongyang

2012-11-05

Finger vein patterns are considered as one of the most promising biometric authentication methods for its security and convenience. Most of the current available finger vein recognition methods utilize features from a segmented blood vessel network. As an improperly segmented network may degrade the recognition accuracy, binary pattern based methods are proposed, such as Local Binary Pattern (LBP), Local Derivative Pattern (LDP) and Local Line Binary Pattern (LLBP). However, the rich directional information hidden in the finger vein pattern has not been fully exploited by the existing local patterns. Inspired by the Webber Local Descriptor (WLD), this paper represents a new direction based local descriptor called Local Directional Code (LDC) and applies it to finger vein recognition. In LDC, the local gradient orientation information is coded as an octonary decimal number. Experimental results show that the proposed method using LDC achieves better performance than methods using LLBP.

A neutron spectrum unfolding code based on generalized regression artificial neural networks.

PubMed

Del Rosario Martinez-Blanco, Ma; Ornelas-Vargas, Gerardo; Castañeda-Miranda, Celina Lizeth; Solís-Sánchez, Luis Octavio; Castañeda-Miranada, Rodrigo; Vega-Carrillo, Héctor René; Celaya-Padilla, Jose M; Garza-Veloz, Idalia; Martínez-Fierro, Margarita; Ortiz-Rodríguez, José Manuel

2016-11-01

The most delicate part of neutron spectrometry, is the unfolding process. The derivation of the spectral information is not simple because the unknown is not given directly as a result of the measurements. Novel methods based on Artificial Neural Networks have been widely investigated. In prior works, back propagation neural networks (BPNN) have been used to solve the neutron spectrometry problem, however, some drawbacks still exist using this kind of neural nets, i.e. the optimum selection of the network topology and the long training time. Compared to BPNN, it's usually much faster to train a generalized regression neural network (GRNN). That's mainly because spread constant is the only parameter used in GRNN. Another feature is that the network will converge to a global minimum, provided that the optimal values of spread has been determined and that the dataset adequately represents the problem space. In addition, GRNN are often more accurate than BPNN in the prediction. These characteristics make GRNNs to be of great interest in the neutron spectrometry domain. This work presents a computational tool based on GRNN capable to solve the neutron spectrometry problem. This computational code, automates the pre-processing, training and testing stages using a k-fold cross validation of 3 folds, the statistical analysis and the post-processing of the information, using 7 Bonner spheres rate counts as only entrance data. The code was designed for a Bonner Spheres System based on a 6 LiI(Eu) neutron detector and a response matrix expressed in 60 energy bins taken from an International Atomic Energy Agency compilation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational models of location-invariant orthographic processing

NASA Astrophysics Data System (ADS)

Dandurand, Frédéric; Hannagan, Thomas; Grainger, Jonathan

2013-03-01

We trained three topologies of backpropagation neural networks to discriminate 2000 words (lexical representations) presented at different positions of a horizontal letter array. The first topology (zero-deck) contains no hidden layer, the second (one-deck) has a single hidden layer, and for the last topology (two-deck), the task is divided in two subtasks implemented as two stacked neural networks, with explicit word-centred letters as intermediate representations. All topologies successfully simulated two key benchmark phenomena observed in skilled human reading: transposed-letter priming and relative-position priming. However, the two-deck topology most accurately simulated the ability to discriminate words from nonwords, while containing the fewest connection weights. We analysed the internal representations after training. Zero-deck networks implement a letter-based scheme with a position bias to differentiate anagrams. One-deck networks implement a holographic overlap coding in which representations are essentially letter-based and words are linear combinations of letters. Two-deck networks also implement holographic-coding.

Optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Harp, D.

2010-12-01

The process of decision making to protect groundwater resources requires a detailed estimation of uncertainties in model predictions. Various uncertainties associated with modeling a natural system, such as: (1) measurement and computational errors; (2) uncertainties in the conceptual model and model-parameter estimates; (3) simplifications in model setup and numerical representation of governing processes, contribute to the uncertainties in the model predictions. Due to this combination of factors, the sources of predictive uncertainties are generally difficult to quantify individually. Decision support related to optimal design of monitoring networks requires (1) detailed analyses of existing uncertainties related to model predictions of groundwater flow and contaminant transport, (2) optimization of the proposed monitoring network locations in terms of their efficiency to detect contaminants and provide early warning. We apply existing and newly-proposed methods to quantify predictive uncertainties and to optimize well locations. An important aspect of the analysis is the application of newly-developed optimization technique based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods which proved to be robust and computationally efficient. These techniques and algorithms are bundled in a software package called MADS. MADS (Model Analyses for Decision Support) is an object-oriented code that is capable of performing various types of model analyses and supporting model-based decision making. The code can be executed under different computational modes, which include (1) sensitivity analyses (global and local), (2) Monte Carlo analysis, (3) model calibration, (4) parameter estimation, (5) uncertainty quantification, and (6) model selection. The code can be externally coupled with any existing model simulator through integrated modules that read/write input and output files using a set of template and instruction files (consistent with the PEST I/O protocol). MADS can also be internally coupled with a series of built-in analytical simulators. MADS provides functionality to work directly with existing control files developed for the code PEST (Doherty 2009). To perform the computational modes mentioned above, the code utilizes (1) advanced Latin-Hypercube sampling techniques (including Improved Distributed Sampling), (2) various gradient-based Levenberg-Marquardt optimization methods, (3) advanced global optimization methods (including Particle Swarm Optimization), and (4) a selection of alternative objective functions. The code has been successfully applied to perform various model analyses related to environmental management of real contamination sites. Examples include source identification problems, quantification of uncertainty, model calibration, and optimization of monitoring networks. The methodology and software codes are demonstrated using synthetic and real case studies where monitoring networks are optimized taking into account the uncertainty in model predictions of contaminant transport.

Accuracy comparison among different machine learning techniques for detecting malicious codes

NASA Astrophysics Data System (ADS)

Narang, Komal

2016-03-01

In this paper, a machine learning based model for malware detection is proposed. It can detect newly released malware i.e. zero day attack by analyzing operation codes on Android operating system. The accuracy of Naïve Bayes, Support Vector Machine (SVM) and Neural Network for detecting malicious code has been compared for the proposed model. In the experiment 400 benign files, 100 system files and 500 malicious files have been used to construct the model. The model yields the best accuracy 88.9% when neural network is used as classifier and achieved 95% and 82.8% accuracy for sensitivity and specificity respectively.

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok

2012-01-01

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

ANNA: A Convolutional Neural Network Code for Spectroscopic Analysis

NASA Astrophysics Data System (ADS)

Lee-Brown, Donald; Anthony-Twarog, Barbara J.; Twarog, Bruce A.

2018-01-01

We present ANNA, a Python-based convolutional neural network code for the automated analysis of stellar spectra. ANNA provides a flexible framework that allows atmospheric parameters such as temperature and metallicity to be determined with accuracies comparable to those of established but less efficient techniques. ANNA performs its parameterization extremely quickly; typically several thousand spectra can be analyzed in less than a second. Additionally, the code incorporates features which greatly speed up the training process necessary for the neural network to measure spectra accurately, resulting in a tool that can easily be run on a single desktop or laptop computer. Thus, ANNA is useful in an era when spectrographs increasingly have the capability to collect dozens to hundreds of spectra each night. This talk will cover the basic features included in ANNA and demonstrate its performance in two use cases: an open cluster abundance analysis involving several hundred spectra, and a metal-rich field star study. Applicability of the code to large survey datasets will also be discussed.

MATIN: a random network coding based framework for high quality peer-to-peer live video streaming.

PubMed

Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

2013-01-01

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

Self-Configuration and Localization in Ad Hoc Wireless Sensor Networks

DTIC Science & Technology

2010-08-31

Goddard I. SUMMARY OF CONTRIBUTIONS We explored the error mechanisms of iterative decoding of low-density parity-check ( LDPC ) codes . This work has resulted...important problems in the area of channel coding , as their unpredictable behavior has impeded the deployment of LDPC codes in many real-world applications. We...tree-based decoders of LDPC codes , including the extrinsic tree decoder, and an investigation into their performance and bounding capabilities [5], [6

Coding Instead of Splitting - Algebraic Combinations in Time and Space

DTIC Science & Technology

2016-06-09

sources message. For certain classes of two-unicast-Z networks, we show that the rate-tuple ( N ,1) is achievable as long as the individual source...destination cuts for the two source-destination pairs are respectively at least as large as N and 1, and the generalized network sharing cut - a bound...previously defined by Kamath et. al. - is at least as large as N + 1. We show this through a novel achievable scheme which is based on random linear coding at

Coding visual features extracted from video sequences.

PubMed

Baroffio, Luca; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2014-05-01

Visual features are successfully exploited in several applications (e.g., visual search, object recognition and tracking, etc.) due to their ability to efficiently represent image content. Several visual analysis tasks require features to be transmitted over a bandwidth-limited network, thus calling for coding techniques to reduce the required bit budget, while attaining a target level of efficiency. In this paper, we propose, for the first time, a coding architecture designed for local features (e.g., SIFT, SURF) extracted from video sequences. To achieve high coding efficiency, we exploit both spatial and temporal redundancy by means of intraframe and interframe coding modes. In addition, we propose a coding mode decision based on rate-distortion optimization. The proposed coding scheme can be conveniently adopted to implement the analyze-then-compress (ATC) paradigm in the context of visual sensor networks. That is, sets of visual features are extracted from video frames, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast to the traditional compress-then-analyze (CTA) paradigm, in which video sequences acquired at a node are compressed and then sent to a central unit for further processing. In this paper, we compare these coding paradigms using metrics that are routinely adopted to evaluate the suitability of visual features in the context of content-based retrieval, object recognition, and tracking. Experimental results demonstrate that, thanks to the significant coding gains achieved by the proposed coding scheme, ATC outperforms CTA with respect to all evaluation metrics.

Prediction of U-Mo dispersion nuclear fuels with Al-Si alloy using artificial neural network

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

Susmikanti, Mike, E-mail: mike@batan.go.id; Sulistyo, Jos, E-mail: soj@batan.go.id

2014-09-30

Dispersion nuclear fuels, consisting of U-Mo particles dispersed in an Al-Si matrix, are being developed as fuel for research reactors. The equilibrium relationship for a mixture component can be expressed in the phase diagram. It is important to analyze whether a mixture component is in equilibrium phase or another phase. The purpose of this research it is needed to built the model of the phase diagram, so the mixture component is in the stable or melting condition. Artificial neural network (ANN) is a modeling tool for processes involving multivariable non-linear relationships. The objective of the present work is to developmore » code based on artificial neural network models of system equilibrium relationship of U-Mo in Al-Si matrix. This model can be used for prediction of type of resulting mixture, and whether the point is on the equilibrium phase or in another phase region. The equilibrium model data for prediction and modeling generated from experimentally data. The artificial neural network with resilient backpropagation method was chosen to predict the dispersion of nuclear fuels U-Mo in Al-Si matrix. This developed code was built with some function in MATLAB. For simulations using ANN, the Levenberg-Marquardt method was also used for optimization. The artificial neural network is able to predict the equilibrium phase or in the phase region. The develop code based on artificial neural network models was built, for analyze equilibrium relationship of U-Mo in Al-Si matrix.« less

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks.

PubMed

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-07-09

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption.

Source Authentication for Code Dissemination Supporting Dynamic Packet Size in Wireless Sensor Networks †

PubMed Central

Kim, Daehee; Kim, Dongwan; An, Sunshin

2016-01-01

Code dissemination in wireless sensor networks (WSNs) is a procedure for distributing a new code image over the air in order to update programs. Due to the fact that WSNs are mostly deployed in unattended and hostile environments, secure code dissemination ensuring authenticity and integrity is essential. Recent works on dynamic packet size control in WSNs allow enhancing the energy efficiency of code dissemination by dynamically changing the packet size on the basis of link quality. However, the authentication tokens attached by the base station become useless in the next hop where the packet size can vary according to the link quality of the next hop. In this paper, we propose three source authentication schemes for code dissemination supporting dynamic packet size. Compared to traditional source authentication schemes such as μTESLA and digital signatures, our schemes provide secure source authentication under the environment, where the packet size changes in each hop, with smaller energy consumption. PMID:27409616

Applications of Coding in Network Communications

ERIC Educational Resources Information Center

Chang, Christopher SungWook

2012-01-01

This thesis uses the tool of network coding to investigate fast peer-to-peer file distribution, anonymous communication, robust network construction under uncertainty, and prioritized transmission. In a peer-to-peer file distribution system, we use a linear optimization approach to show that the network coding framework significantly simplifies…

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

ARC-2001-ACD01-0018

NASA Image and Video Library

2001-02-16

New Center Network Deployment ribbon Cutting: from left to right: Maryland Edwards, Code JT upgrade project deputy task manager; Ed Murphy, foundry networks systems engineer; Bohdan Cmaylo, Code JT upgrade project task manager, Scott Santiago, Division Chief, Code JT; Greg Miller, Raytheon Network engineer and Frank Daras, Raytheon network engineering manager.

Learning and coding in biological neural networks

NASA Astrophysics Data System (ADS)

Fiete, Ila Rani

How can large groups of neurons that locally modify their activities learn to collectively perform a desired task? Do studies of learning in small networks tell us anything about learning in the fantastically large collection of neurons that make up a vertebrate brain? What factors do neurons optimize by encoding sensory inputs or motor commands in the way they do? In this thesis I present a collection of four theoretical works: each of the projects was motivated by specific constraints and complexities of biological neural networks, as revealed by experimental studies; together, they aim to partially address some of the central questions of neuroscience posed above. We first study the role of sparse neural activity, as seen in the coding of sequential commands in a premotor area responsible for birdsong. We show that the sparse coding of temporal sequences in the songbird brain can, in a network where the feedforward plastic weights must translate the sparse sequential code into a time-varying muscle code, facilitate learning by minimizing synaptic interference. Next, we propose a biologically plausible synaptic plasticity rule that can perform goal-directed learning in recurrent networks of voltage-based spiking neurons that interact through conductances. Learning is based on the correlation of noisy local activity with a global reward signal; we prove that this rule performs stochastic gradient ascent on the reward. Thus, if the reward signal quantifies network performance on some desired task, the plasticity rule provably drives goal-directed learning in the network. To assess the convergence properties of the learning rule, we compare it with a known example of learning in the brain. Song-learning in finches is a clear example of a learned behavior, with detailed available neurophysiological data. With our learning rule, we train an anatomically accurate model birdsong network that drives a sound source to mimic an actual zebrafinch song. Simulation and theoretical results on the scalability of this rule show that learning with stochastic gradient ascent may be adequately fast to explain learning in the bird. Finally, we address the more general issue of the scalability of stochastic gradient learning on quadratic cost surfaces in linear systems, as a function of system size and task characteristics, by deriving analytical expressions for the learning curves.

Design of Provider-Provisioned Website Protection Scheme against Malware Distribution

NASA Astrophysics Data System (ADS)

Yagi, Takeshi; Tanimoto, Naoto; Hariu, Takeo; Itoh, Mitsutaka

Vulnerabilities in web applications expose computer networks to security threats, and many websites are used by attackers as hopping sites to attack other websites and user terminals. These incidents prevent service providers from constructing secure networking environments. To protect websites from attacks exploiting vulnerabilities in web applications, service providers use web application firewalls (WAFs). WAFs filter accesses from attackers by using signatures, which are generated based on the exploit codes of previous attacks. However, WAFs cannot filter unknown attacks because the signatures cannot reflect new types of attacks. In service provider environments, the number of exploit codes has recently increased rapidly because of the spread of vulnerable web applications that have been developed through cloud computing. Thus, generating signatures for all exploit codes is difficult. To solve these problems, our proposed scheme detects and filters malware downloads that are sent from websites which have already received exploit codes. In addition, to collect information for detecting malware downloads, web honeypots, which automatically extract the communication records of exploit codes, are used. According to the results of experiments using a prototype, our scheme can filter attacks automatically so that service providers can provide secure and cost-effective network environments.

Wireless Headset Communication System

NASA Technical Reports Server (NTRS)

Lau, Wilfred K.; Swanson, Richard; Christensen, Kurt K.

1995-01-01

System combines features of pagers, walkie-talkies, and cordless telephones. Wireless headset communication system uses digital modulation on spread spectrum to avoid interference among units. Consists of base station, 4 radio/antenna modules, and as many as 16 remote units with headsets. Base station serves as network controller, audio-mixing network, and interface to such outside services as computers, telephone networks, and other base stations. Developed for use at Kennedy Space Center, system also useful in industrial maintenance, emergency operations, construction, and airport operations. Also, digital capabilities exploited; by adding bar-code readers for use in taking inventories.

MATIN: A Random Network Coding Based Framework for High Quality Peer-to-Peer Live Video Streaming

PubMed Central

Barekatain, Behrang; Khezrimotlagh, Dariush; Aizaini Maarof, Mohd; Ghaeini, Hamid Reza; Salleh, Shaharuddin; Quintana, Alfonso Ariza; Akbari, Behzad; Cabrera, Alicia Triviño

2013-01-01

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay. PMID:23940530

Propagation of spiking regularity and double coherence resonance in feedforward networks.

PubMed

Men, Cong; Wang, Jiang; Qin, Ying-Mei; Deng, Bin; Tsang, Kai-Ming; Chan, Wai-Lok

2012-03-01

We investigate the propagation of spiking regularity in noisy feedforward networks (FFNs) based on FitzHugh-Nagumo neuron model systematically. It is found that noise could modulate the transmission of firing rate and spiking regularity. Noise-induced synchronization and synfire-enhanced coherence resonance are also observed when signals propagate in noisy multilayer networks. It is interesting that double coherence resonance (DCR) with the combination of synaptic input correlation and noise intensity is finally attained after the processing layer by layer in FFNs. Furthermore, inhibitory connections also play essential roles in shaping DCR phenomena. Several properties of the neuronal network such as noise intensity, correlation of synaptic inputs, and inhibitory connections can serve as control parameters in modulating both rate coding and the order of temporal coding.

Neural coding in graphs of bidirectional associative memories.

PubMed

Bouchain, A David; Palm, Günther

2012-01-24

In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

Essential RNA-Based Technologies and Their Applications in Plant Functional Genomics.

PubMed

Teotia, Sachin; Singh, Deepali; Tang, Xiaoqing; Tang, Guiliang

2016-02-01

Genome sequencing has not only extended our understanding of the blueprints of many plant species but has also revealed the secrets of coding and non-coding genes. We present here a brief introduction to and personal account of key RNA-based technologies, as well as their development and applications for functional genomics of plant coding and non-coding genes, with a focus on short tandem target mimics (STTMs), artificial microRNAs (amiRNAs), and CRISPR/Cas9. In addition, their use in multiplex technologies for the functional dissection of gene networks is discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Efficacy analysis of LDPC coded APSK modulated differential space-time-frequency coded for wireless body area network using MB-pulsed OFDM UWB technology.

PubMed

Manimegalai, C T; Gauni, Sabitha; Kalimuthu, K

2017-12-04

Wireless body area network (WBAN) is a breakthrough technology in healthcare areas such as hospital and telemedicine. The human body has a complex mixture of different tissues. It is expected that the nature of propagation of electromagnetic signals is distinct in each of these tissues. This forms the base for the WBAN, which is different from other environments. In this paper, the knowledge of Ultra Wide Band (UWB) channel is explored in the WBAN (IEEE 802.15.6) system. The measurements of parameters in frequency range from 3.1-10.6 GHz are taken. The proposed system, transmits data up to 480 Mbps by using LDPC coded APSK Modulated Differential Space-Time-Frequency Coded MB-OFDM to increase the throughput and power efficiency.

Network coding multiuser scheme for indoor visible light communications

NASA Astrophysics Data System (ADS)

Zhang, Jiankun; Dang, Anhong

2017-12-01

Visible light communication (VLC) is a unique alternative for indoor data transfer and developing beyond point-to-point. However, for realizing high-capacity networks, VLC is facing challenges including the constrained bandwidth of the optical access point and random occlusion. A network coding scheme for VLC (NC-VLC) is proposed, with increased throughput and system robustness. Based on the Lambertian illumination model, theoretical decoding failure probability of the multiuser NC-VLC system is derived, and the impact of the system parameters on the performance is analyzed. Experiments demonstrate the proposed scheme successfully in the indoor multiuser scenario. These results indicate that the NC-VLC system shows a good performance under the link loss and random occlusion.

Spatiotemporal coding in the cortex: information flow-based learning in spiking neural networks.

PubMed

Deco, G; Schürmann, B

1999-05-15

We introduce a learning paradigm for networks of integrate-and-fire spiking neurons that is based on an information-theoretic criterion. This criterion can be viewed as a first principle that demonstrates the experimentally observed fact that cortical neurons display synchronous firing for some stimuli and not for others. The principle can be regarded as the postulation of a nonparametric reconstruction method as optimization criteria for learning the required functional connectivity that justifies and explains synchronous firing for binding of features as a mechanism for spatiotemporal coding. This can be expressed in an information-theoretic way by maximizing the discrimination ability between different sensory inputs in minimal time.

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things

PubMed Central

Akan, Ozgur B.

2018-01-01

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST). PMID:29538405

D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.

PubMed

Aktas, Metin; Kuscu, Murat; Dinc, Ergin; Akan, Ozgur B

2018-01-01

Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).

Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks.

PubMed

Scarpetta, Silvia; Giacco, Ferdinando

2013-04-01

We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stable precise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units.

Probing the functions of long non-coding RNAs by exploiting the topology of global association and interaction network.

PubMed

Deng, Lei; Wu, Hongjie; Liu, Chuyao; Zhan, Weihua; Zhang, Jingpu

2018-06-01

Long non-coding RNAs (lncRNAs) are involved in many biological processes, such as immune response, development, differentiation and gene imprinting and are associated with diseases and cancers. But the functions of the vast majority of lncRNAs are still unknown. Predicting the biological functions of lncRNAs is one of the key challenges in the post-genomic era. In our work, We first build a global network including a lncRNA similarity network, a lncRNA-protein association network and a protein-protein interaction network according to the expressions and interactions, then extract the topological feature vectors of the global network. Using these features, we present an SVM-based machine learning approach, PLNRGO, to annotate human lncRNAs. In PLNRGO, we construct a training data set according to the proteins with GO annotations and train a binary classifier for each GO term. We assess the performance of PLNRGO on our manually annotated lncRNA benchmark and a protein-coding gene benchmark with known functional annotations. As a result, the performance of our method is significantly better than that of other state-of-the-art methods in terms of maximum F-measure and coverage. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance Evaluation of a Field Programmable Gate Array-Based System for Detecting and Tracking Peer-to-Peer Protocols on a Gigabit Ethernet Network

DTIC Science & Technology

2010-06-01

Ron’s Code 4 . . . . . . . . . . . . . . . . . . . 18 2.3.3 Virtual Private Network and Secure Shell Tunnels 19 2.3.4 Darknets ...created using Iodine. 2.2 Analyzing and Classifying Network Traffic Before the advent of Darknets and anonymizers like Tor (see Section 2.3), ana... darknets , and the Tor network. 2.3.1 Byte Padding. Byte padding is the most primitive obfuscation method used to hide payloads in network traffic. When byte

GeNN: a code generation framework for accelerated brain simulations

NASA Astrophysics Data System (ADS)

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations.

PubMed

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-07

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/.

GeNN: a code generation framework for accelerated brain simulations

PubMed Central

Yavuz, Esin; Turner, James; Nowotny, Thomas

2016-01-01

Large-scale numerical simulations of detailed brain circuit models are important for identifying hypotheses on brain functions and testing their consistency and plausibility. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper, we present the GeNN (GPU-enhanced Neuronal Networks) framework, which aims to facilitate the use of graphics accelerators for computational models of large-scale neuronal networks to address this challenge. GeNN is an open source library that generates code to accelerate the execution of network simulations on NVIDIA GPUs, through a flexible and extensible interface, which does not require in-depth technical knowledge from the users. We present performance benchmarks showing that 200-fold speedup compared to a single core of a CPU can be achieved for a network of one million conductance based Hodgkin-Huxley neurons but that for other models the speedup can differ. GeNN is available for Linux, Mac OS X and Windows platforms. The source code, user manual, tutorials, Wiki, in-depth example projects and all other related information can be found on the project website http://genn-team.github.io/genn/. PMID:26740369

Real-time video streaming using H.264 scalable video coding (SVC) in multihomed mobile networks: a testbed approach

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2011-03-01

Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.

Location Based Service in Indoor Environment Using Quick Response Code Technology

NASA Astrophysics Data System (ADS)

Hakimpour, F.; Zare Zardiny, A.

2014-10-01

Today by extensive use of intelligent mobile phones, increased size of screens and enriching the mobile phones by Global Positioning System (GPS) technology use of location based services have been considered by public users more than ever.. Based on the position of users, they can receive the desired information from different LBS providers. Any LBS system generally includes five main parts: mobile devices, communication network, positioning system, service provider and data provider. By now many advances have been gained in relation to any of these parts; however the users positioning especially in indoor environments is propounded as an essential and critical issue in LBS. It is well known that GPS performs too poorly inside buildings to provide usable indoor positioning. On the other hand, current indoor positioning technologies such as using RFID or WiFi network need different hardware and software infrastructures. In this paper, we propose a new method to overcome these challenges. This method is using the Quick Response (QR) Code Technology. QR Code is a 2D encrypted barcode with a matrix structure which consists of black modules arranged in a square grid. Scanning and data retrieving process from QR Code is possible by use of different camera-enabled mobile phones only by installing the barcode reader software. This paper reviews the capabilities of QR Code technology and then discusses the advantages of using QR Code in Indoor LBS (ILBS) system in comparison to other technologies. Finally, some prospects of using QR Code are illustrated through implementation of a scenario. The most important advantages of using this new technology in ILBS are easy implementation, spending less expenses, quick data retrieval, possibility of printing the QR Code on different products and no need for complicated hardware and software infrastructures.

Extension of analog network coding in wireless information exchange

NASA Astrophysics Data System (ADS)

Chen, Cheng; Huang, Jiaqing

2012-01-01

Ever since the concept of analog network coding(ANC) was put forward by S.Katti, much attention has been focused on how to utilize analog network coding to take advantage of wireless interference, which used to be considered generally harmful, to improve throughput performance. Previously, only the case of two nodes that need to exchange information has been fully discussed while the issue of extending analog network coding to more than three nodes remains undeveloped. In this paper, we propose a practical transmission scheme to extend analog network coding to more than two nodes that need to exchange information among themselves. We start with the case of three nodes that need to exchange information and demonstrate that through utilizing our algorithm, the throughput can achieve 33% and 20% increase compared with that of traditional transmission scheduling and digital network coding, respectively. Then, we generalize the algorithm so that it can fit for occasions with any number of nodes. We also discuss some technical issues and throughput analysis as well as the bit error rate.

Quality of experience enhancement of high efficiency video coding video streaming in wireless packet networks using multiple description coding

NASA Astrophysics Data System (ADS)

Boumehrez, Farouk; Brai, Radhia; Doghmane, Noureddine; Mansouri, Khaled

2018-01-01

Recently, video streaming has attracted much attention and interest due to its capability to process and transmit large data. We propose a quality of experience (QoE) model relying on high efficiency video coding (HEVC) encoder adaptation scheme, in turn based on the multiple description coding (MDC) for video streaming. The main contributions of the paper are (1) a performance evaluation of the new and emerging video coding standard HEVC/H.265, which is based on the variation of quantization parameter (QP) values depending on different video contents to deduce their influence on the sequence to be transmitted, (2) QoE support multimedia applications in wireless networks are investigated, so we inspect the packet loss impact on the QoE of transmitted video sequences, (3) HEVC encoder parameter adaptation scheme based on MDC is modeled with the encoder parameter and objective QoE model. A comparative study revealed that the proposed MDC approach is effective for improving the transmission with a peak signal-to-noise ratio (PSNR) gain of about 2 to 3 dB. Results show that a good choice of QP value can compensate for transmission channel effects and improve received video quality, although HEVC/H.265 is also sensitive to packet loss. The obtained results show the efficiency of our proposed method in terms of PSNR and mean-opinion-score.

Phase synchronization motion and neural coding in dynamic transmission of neural information.

PubMed

Wang, Rubin; Zhang, Zhikang; Qu, Jingyi; Cao, Jianting

2011-07-01

In order to explore the dynamic characteristics of neural coding in the transmission of neural information in the brain, a model of neural network consisting of three neuronal populations is proposed in this paper using the theory of stochastic phase dynamics. Based on the model established, the neural phase synchronization motion and neural coding under spontaneous activity and stimulation are examined, for the case of varying network structure. Our analysis shows that, under the condition of spontaneous activity, the characteristics of phase neural coding are unrelated to the number of neurons participated in neural firing within the neuronal populations. The result of numerical simulation supports the existence of sparse coding within the brain, and verifies the crucial importance of the magnitudes of the coupling coefficients in neural information processing as well as the completely different information processing capability of neural information transmission in both serial and parallel couplings. The result also testifies that under external stimulation, the bigger the number of neurons in a neuronal population, the more the stimulation influences the phase synchronization motion and neural coding evolution in other neuronal populations. We verify numerically the experimental result in neurobiology that the reduction of the coupling coefficient between neuronal populations implies the enhancement of lateral inhibition function in neural networks, with the enhancement equivalent to depressing neuronal excitability threshold. Thus, the neuronal populations tend to have a stronger reaction under the same stimulation, and more neurons get excited, leading to more neurons participating in neural coding and phase synchronization motion.

Use of FEC coding to improve statistical multiplexing performance for video transport over ATM networks

NASA Astrophysics Data System (ADS)

Kurceren, Ragip; Modestino, James W.

1998-12-01

The use of forward error-control (FEC) coding, possibly in conjunction with ARQ techniques, has emerged as a promising approach for video transport over ATM networks for cell-loss recovery and/or bit error correction, such as might be required for wireless links. Although FEC provides cell-loss recovery capabilities it also introduces transmission overhead which can possibly cause additional cell losses. A methodology is described to maximize the number of video sources multiplexed at a given quality of service (QoS), measured in terms of decoded cell loss probability, using interlaced FEC codes. The transport channel is modelled as a block interference channel (BIC) and the multiplexer as single server, deterministic service, finite buffer supporting N users. Based upon an information-theoretic characterization of the BIC and large deviation bounds on the buffer overflow probability, the described methodology provides theoretically achievable upper limits on the number of sources multiplexed. Performance of specific coding techniques using interlaced nonbinary Reed-Solomon (RS) codes and binary rate-compatible punctured convolutional (RCPC) codes is illustrated.

DoD Electronic Data Interchange (EDI) Convention: ASC X12 Transaction Set 836 Contract Award (Version 003010)

DTIC Science & Technology

1993-01-01

upon designation of DoD Activity Address Code (DoDAAC) or other code coordinated with the value-added network (VAN). Mandatory ISA06 106 Interc.ange...coordinated with the value-added network (VAN). Non-DoD activities use identification code qualified by ISA05 and coordinated with the VAN. Mandatory...designation of DoD Activity Address Code (DoDAAC) or other code coordinated with the value-added network (VAN). Mandatory ISA08 107 Interchange Receiver

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

Analysis of hybrid subcarrier multiplexing of OCDMA based on single photodiode detection

NASA Astrophysics Data System (ADS)

Ahmad, N. A. A.; Junita, M. N.; Aljunid, S. A.; Rashidi, C. B. M.; Endut, R.

2017-11-01

This paper analyzes the performance of subcarrier multiplexing (SCM) of spectral amplitude coding optical code multiple access (SAC-OCDMA) by applying Recursive Combinatorial (RC) code based on single photodiode detection (SPD). SPD is used in the receiver part to reduce the effect of multiple access interference (MAI) which contributes as a dominant noise in incoherent SAC-OCDMA systems. Results indicate that the SCM OCDMA network performance could be improved by using lower data rates and higher number of weight. Total number of users can also be enhanced by adding lower data rates and higher number of subcarriers.

Automatic Implementation of Ttethernet-Based Time-Triggered Avionics Applications

NASA Astrophysics Data System (ADS)

Gorcitz, Raul Adrian; Carle, Thomas; Lesens, David; Monchaux, David; Potop-Butucaruy, Dumitru; Sorel, Yves

2015-09-01

The design of safety-critical embedded systems such as those used in avionics still involves largely manual phases. But in avionics the definition of standard interfaces embodied in standards such as ARINC 653 or TTEthernet should allow the definition of fully automatic code generation flows that reduce the costs while improving the quality of the generated code, much like compilers have done when replacing manual assembly coding. In this paper, we briefly present such a fully automatic implementation tool, called Lopht, for ARINC653-based time-triggered systems, and then explain how it is currently extended to include support for TTEthernet networks.

Competing endogenous RNA network crosstalk reveals novel molecular markers in colorectal cancer.

PubMed

Samir, Nehal; Matboli, Marwa; El-Tayeb, Hanaa; El-Tawdi, Ahmed; Hassan, Mohmed K; Waly, Amr; El-Akkad, Hesham A E; Ramadan, Mohamed G; Al-Belkini, Tarek N; El-Khamisy, Sherif; El-Asmar, Farid

2018-05-08

The competing endogenous RNA networks play a pivotal role in cancer diagnosis and progression. Novel properstrategies for early detection of colorectal cancer (CRC) are strongly needed. We investigated a novel CRC-specific RNA-based integrated competing endogenous network composed of lethal3 malignant brain tumor like1 (L3MBTL1) gene, long non-coding intergenic RNA- (lncRNA RP11-909B2.1) and homo sapiens microRNA-595 (hsa-miRNA-595) using in silico data analysis. RT-qPCR-based validation of the network was achieved in serum of 70 patients with CRC, 40 patients with benign colorectal neoplasm, and 20 healthy controls. Moreover, in cancer tissues of 20 of the 70 CRC cases were involved in the study. The expression of RNA-based biomarker network in both CRC and adjacent non-tumor tissues and their correlation with the serum levels of this network members was investigated. Lastly, the expression levels of the chosen ceRNA was verified in CRC cell line. Our results revealed that the three RNAs-based biomarker network (long non-coding intergenic RNA-[lncRNA RP11-909B2.1], Homo sapiens microRNA-595 [hsa-miRNA-595], and L3MBTL1 mRNA), had high sensitivity and specificity for discriminating CRC from healthy controls and also from benign colorectal neoplasm. The data suggest that among these three RNAs, serum lncRNA RP11-909B2.1 could be a promising independent prognostic factors in CRC. The circulatory RNA based biomarker panel can act as potential biomarker for CRC diagnosis and prognosis. © 2018 Wiley Periodicals, Inc.

Structured Set Intra Prediction With Discriminative Learning in a Max-Margin Markov Network for High Efficiency Video Coding

PubMed Central

Dai, Wenrui; Xiong, Hongkai; Jiang, Xiaoqian; Chen, Chang Wen

2014-01-01

This paper proposes a novel model on intra coding for High Efficiency Video Coding (HEVC), which simultaneously predicts blocks of pixels with optimal rate distortion. It utilizes the spatial statistical correlation for the optimal prediction based on 2-D contexts, in addition to formulating the data-driven structural interdependences to make the prediction error coherent with the probability distribution, which is desirable for successful transform and coding. The structured set prediction model incorporates a max-margin Markov network (M3N) to regulate and optimize multiple block predictions. The model parameters are learned by discriminating the actual pixel value from other possible estimates to maximize the margin (i.e., decision boundary bandwidth). Compared to existing methods that focus on minimizing prediction error, the M3N-based model adaptively maintains the coherence for a set of predictions. Specifically, the proposed model concurrently optimizes a set of predictions by associating the loss for individual blocks to the joint distribution of succeeding discrete cosine transform coefficients. When the sample size grows, the prediction error is asymptotically upper bounded by the training error under the decomposable loss function. As an internal step, we optimize the underlying Markov network structure to find states that achieve the maximal energy using expectation propagation. For validation, we integrate the proposed model into HEVC for optimal mode selection on rate-distortion optimization. The proposed prediction model obtains up to 2.85% bit rate reduction and achieves better visual quality in comparison to the HEVC intra coding. PMID:25505829

Single-shot secure quantum network coding on butterfly network with free public communication

NASA Astrophysics Data System (ADS)

Owari, Masaki; Kato, Go; Hayashi, Masahito

2018-01-01

Quantum network coding on the butterfly network has been studied as a typical example of quantum multiple cast network. We propose a secure quantum network code for the butterfly network with free public classical communication in the multiple unicast setting under restricted eavesdropper’s power. This protocol certainly transmits quantum states when there is no attack. We also show the secrecy with shared randomness as additional resource when the eavesdropper wiretaps one of the channels in the butterfly network and also derives the information sending through public classical communication. Our protocol does not require verification process, which ensures single-shot security.

Bearing performance degradation assessment based on time-frequency code features and SOM network

NASA Astrophysics Data System (ADS)

Zhang, Yan; Tang, Baoping; Han, Yan; Deng, Lei

2017-04-01

Bearing performance degradation assessment and prognostics are extremely important in supporting maintenance decision and guaranteeing the system’s reliability. To achieve this goal, this paper proposes a novel feature extraction method for the degradation assessment and prognostics of bearings. Features of time-frequency codes (TFCs) are extracted from the time-frequency distribution using a hybrid procedure based on short-time Fourier transform (STFT) and non-negative matrix factorization (NMF) theory. An alternative way to design the health indicator is investigated by quantifying the similarity between feature vectors using a self-organizing map (SOM) network. On the basis of this idea, a new health indicator called time-frequency code quantification error (TFCQE) is proposed to assess the performance degradation of the bearing. This indicator is constructed based on the bearing real-time behavior and the SOM model that is previously trained with only the TFC vectors under the normal condition. Vibration signals collected from the bearing run-to-failure tests are used to validate the developed method. The comparison results demonstrate the superiority of the proposed TFCQE indicator over many other traditional features in terms of feature quality metrics, incipient degradation identification and achieving accurate prediction. Highlights • Time-frequency codes are extracted to reflect the signals’ characteristics. • SOM network served as a tool to quantify the similarity between feature vectors. • A new health indicator is proposed to demonstrate the whole stage of degradation development. • The method is useful for extracting the degradation features and detecting the incipient degradation. • The superiority of the proposed method is verified using experimental data.

Identification of Novel Long Non-coding and Circular RNAs in Human Papillomavirus-Mediated Cervical Cancer

PubMed Central

Wang, Hongbo; Zhao, Yingchao; Chen, Mingyue; Cui, Jie

2017-01-01

Cervical cancer is the third most common cancer worldwide and the fourth leading cause of cancer-associated mortality in women. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) may play key roles in the carcinogenesis of different cancers; however, little is known about the mechanisms of lncRNAs and circRNAs in the progression and metastasis of cervical cancer. In this study, we explored the expression profiles of lncRNAs, circRNAs, miRNAs, and mRNAs in HPV16 (human papillomavirus genotype 16) mediated cervical squamous cell carcinoma and matched adjacent non-tumor (ATN) tissues from three patients with high-throughput RNA sequencing (RNA-seq). In total, we identified 19 lncRNAs, 99 circRNAs, 28 miRNAs, and 304 mRNAs that were commonly differentially expressed (DE) in different patients. Among the non-coding RNAs, 3 lncRNAs and 44 circRNAs are novel to our knowledge. Functional enrichment analysis showed that DE lncRNAs, miRNAs, and mRNAs were enriched in pathways crucial to cancer as well as other gene ontology (GO) terms. Furthermore, the co-expression network and function prediction suggested that all 19 DE lncRNAs could play different roles in the carcinogenesis and development of cervical cancer. The competing endogenous RNA (ceRNA) network based on DE coding and non-coding RNAs showed that each miRNA targeted a number of lncRNAs and circRNAs. The link between part of the miRNAs in the network and cervical cancer has been validated in previous studies, and these miRNAs targeted the majority of the novel non-coding RNAs, thus suggesting that these novel non-coding RNAs may be involved in cervical cancer. Taken together, our study shows that DE non-coding RNAs could be further developed as diagnostic and therapeutic biomarkers of cervical cancer. The complex ceRNA network also lays the foundation for future research of the roles of coding and non-coding RNAs in cervical cancer. PMID:28970820

Ground-state coding in partially connected neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1989-01-01

Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.

Remote coding scheme based on waveguide Bragg grating in PLC splitter chip for PON monitoring.

PubMed

Zhang, Xuan; Lu, Fengjun; Chen, Si; Zhao, Xingqun; Zhu, Min; Sun, Xiaohan

2016-03-07

A distributing arranged waveguide Bragg gratings (WBGs) in PLC splitter chip based remote coding scheme is proposed and analyzed for passive optical network (PON) monitoring, by which the management system can identify each drop fiber link through the same reflector in the terminal of each optical network unit, even though there exist several equidistant users. The corresponding coding and capacity models are respectively established and investigated so that we can obtain a minimum number of the WBGs needed under the condition of the distributed structure. Signal-to-noise ratio (SNR) model related to the number of equidistant users is also developed to extend the analyses for the overall performance of the system. Simulation results show the proposed scheme is feasible and allow the monitoring of a 64 users PON with SNR range of 7.5~10.6dB. The scheme can solve some of difficulties of construction site at the lower user cost for PON system.

Evolutionary Construction of Block-Based Neural Networks in Consideration of Failure

NASA Astrophysics Data System (ADS)

Takamori, Masahito; Koakutsu, Seiichi; Hamagami, Tomoki; Hirata, Hironori

In this paper we propose a modified gene coding and an evolutionary construction in consideration of failure in evolutionary construction of Block-Based Neural Networks. In the modified gene coding, we arrange the genes of weights on a chromosome in consideration of the position relation of the genes of weight and structure. By the modified gene coding, the efficiency of search by crossover is increased. Thereby, it is thought that improvement of the convergence rate of construction and shortening of construction time can be performed. In the evolutionary construction in consideration of failure, the structure which is adapted for failure is built in the state where failure occured. Thereby, it is thought that BBNN can be reconstructed in a short time at the time of failure. To evaluate the proposed method, we apply it to pattern classification and autonomous mobile robot control problems. The computational experiments indicate that the proposed method can improve convergence rate of construction and shorten of construction and reconstruction time.

Resource Management In Peer-To-Peer Networks: A Nadse Approach

NASA Astrophysics Data System (ADS)

Patel, R. B.; Garg, Vishal

2011-12-01

This article presents a common solution to Peer-to-Peer (P2P) network problems and distributed computing with the help of "Neighbor Assisted Distributed and Scalable Environment" (NADSE). NADSE supports both device and code mobility. In this article mainly we focus on the NADSE based resource management technique. How information dissemination and searching is speedup when using the NADSE service provider node in large network. Results show that performance of the NADSE network is better in comparison to Gnutella, and Freenet.

Benefit of adaptive FEC in shared backup path protected elastic optical network.

PubMed

Guo, Hong; Dai, Hua; Wang, Chao; Li, Yongcheng; Bose, Sanjay K; Shen, Gangxiang

2015-07-27

We apply an adaptive forward error correction (FEC) allocation strategy to an Elastic Optical Network (EON) operated with shared backup path protection (SBPP). To maximize the protected network capacity that can be carried, an Integer Linear Programing (ILP) model and a spectrum window plane (SWP)-based heuristic algorithm are developed. Simulation results show that the FEC coding overhead required by the adaptive FEC scheme is significantly lower than that needed by a fixed FEC allocation strategy resulting in higher network capacity for the adaptive strategy. The adaptive FEC allocation strategy can also significantly outperform the fixed FEC allocation strategy both in terms of the spare capacity redundancy and the average FEC coding overhead needed per optical channel. The proposed heuristic algorithm is efficient and not only performs closer to the ILP model but also does much better than the shortest-path algorithm.

Brief Report: Databases in the Asia-Pacific Region: The Potential for a Distributed Network Approach.

PubMed

Lai, Edward Chia-Cheng; Man, Kenneth K C; Chaiyakunapruk, Nathorn; Cheng, Ching-Lan; Chien, Hsu-Chih; Chui, Celine S L; Dilokthornsakul, Piyameth; Hardy, N Chantelle; Hsieh, Cheng-Yang; Hsu, Chung Y; Kubota, Kiyoshi; Lin, Tzu-Chieh; Liu, Yanfang; Park, Byung Joo; Pratt, Nicole; Roughead, Elizabeth E; Shin, Ju-Young; Watcharathanakij, Sawaeng; Wen, Jin; Wong, Ian C K; Yang, Yea-Huei Kao; Zhang, Yinghong; Setoguchi, Soko

2015-11-01

This study describes the availability and characteristics of databases in Asian-Pacific countries and assesses the feasibility of a distributed network approach in the region. A web-based survey was conducted among investigators using healthcare databases in the Asia-Pacific countries. Potential survey participants were identified through the Asian Pharmacoepidemiology Network. Investigators from a total of 11 databases participated in the survey. Database sources included four nationwide claims databases from Japan, South Korea, and Taiwan; two nationwide electronic health records from Hong Kong and Singapore; a regional electronic health record from western China; two electronic health records from Thailand; and cancer and stroke registries from Taiwan. We identified 11 databases with capabilities for distributed network approaches. Many country-specific coding systems and terminologies have been already converted to international coding systems. The harmonization of health expenditure data is a major obstacle for future investigations attempting to evaluate issues related to medical costs.

BASiNET-BiologicAl Sequences NETwork: a case study on coding and non-coding RNAs identification.

PubMed

Ito, Eric Augusto; Katahira, Isaque; Vicente, Fábio Fernandes da Rocha; Pereira, Luiz Filipe Protasio; Lopes, Fabrício Martins

2018-06-05

With the emergence of Next Generation Sequencing (NGS) technologies, a large volume of sequence data in particular de novo sequencing was rapidly produced at relatively low costs. In this context, computational tools are increasingly important to assist in the identification of relevant information to understand the functioning of organisms. This work introduces BASiNET, an alignment-free tool for classifying biological sequences based on the feature extraction from complex network measurements. The method initially transform the sequences and represents them as complex networks. Then it extracts topological measures and constructs a feature vector that is used to classify the sequences. The method was evaluated in the classification of coding and non-coding RNAs of 13 species and compared to the CNCI, PLEK and CPC2 methods. BASiNET outperformed all compared methods in all adopted organisms and datasets. BASiNET have classified sequences in all organisms with high accuracy and low standard deviation, showing that the method is robust and non-biased by the organism. The proposed methodology is implemented in open source in R language and freely available for download at https://cran.r-project.org/package=BASiNET.

Performance Analysis of OCDMA Based on AND Detection in FTTH Access Network Using PIN & APD Photodiodes

NASA Astrophysics Data System (ADS)

Aldouri, Muthana; Aljunid, S. A.; Ahmad, R. Badlishah; Fadhil, Hilal A.

2011-06-01

In order to comprise between PIN photo detector and avalanche photodiodes in a system used double weight (DW) code to be a performance of the optical spectrum CDMA in FTTH network with point-to-multi-point (P2MP) application. The performance of PIN against APD is compared through simulation by using opt system software version 7. In this paper we used two networks designed as follows one used PIN photo detector and the second using APD photo diode, both two system using with and without erbium doped fiber amplifier (EDFA). It is found that APD photo diode in this system is better than PIN photo detector for all simulation results. The conversion used a Mach-Zehnder interferometer (MZI) wavelength converter. Also we are study, the proposing a detection scheme known as AND subtraction detection technique implemented with fiber Bragg Grating (FBG) act as encoder and decoder. This FBG is used to encode and decode the spectral amplitude coding namely double weight (DW) code in Optical Code Division Multiple Access (OCDMA). The performances are characterized through bit error rate (BER) and bit rate (BR) also the received power at various bit rate.

Prioritized Degree Distribution in Wireless Sensor Networks with a Network Coded Data Collection Method

PubMed Central

Wan, Jan; Xiong, Naixue; Zhang, Wei; Zhang, Qinchao; Wan, Zheng

2012-01-01

The reliability of wireless sensor networks (WSNs) can be greatly affected by failures of sensor nodes due to energy exhaustion or the influence of brutal external environment conditions. Such failures seriously affect the data persistence and collection efficiency. Strategies based on network coding technology for WSNs such as LTCDS can improve the data persistence without mass redundancy. However, due to the bad intermediate performance of LTCDS, a serious ‘cliff effect’ may appear during the decoding period, and source data are hard to recover from sink nodes before sufficient encoded packets are collected. In this paper, the influence of coding degree distribution strategy on the ‘cliff effect’ is observed and the prioritized data storage and dissemination algorithm PLTD-ALPHA is presented to achieve better data persistence and recovering performance. With PLTD-ALPHA, the data in sensor network nodes present a trend that their degree distribution increases along with the degree level predefined, and the persistent data packets can be submitted to the sink node according to its degree in order. Finally, the performance of PLTD-ALPHA is evaluated and experiment results show that PLTD-ALPHA can greatly improve the data collection performance and decoding efficiency, while data persistence is not notably affected. PMID:23235451

Protocol vulnerability detection based on network traffic analysis and binary reverse engineering.

PubMed

Wen, Shameng; Meng, Qingkun; Feng, Chao; Tang, Chaojing

2017-01-01

Network protocol vulnerability detection plays an important role in many domains, including protocol security analysis, application security, and network intrusion detection. In this study, by analyzing the general fuzzing method of network protocols, we propose a novel approach that combines network traffic analysis with the binary reverse engineering method. For network traffic analysis, the block-based protocol description language is introduced to construct test scripts, while the binary reverse engineering method employs the genetic algorithm with a fitness function designed to focus on code coverage. This combination leads to a substantial improvement in fuzz testing for network protocols. We build a prototype system and use it to test several real-world network protocol implementations. The experimental results show that the proposed approach detects vulnerabilities more efficiently and effectively than general fuzzing methods such as SPIKE.

An Adaptive Data Gathering Scheme for Multi-Hop Wireless Sensor Networks Based on Compressed Sensing and Network Coding.

PubMed

Yin, Jun; Yang, Yuwang; Wang, Lei

2016-04-01

Joint design of compressed sensing (CS) and network coding (NC) has been demonstrated to provide a new data gathering paradigm for multi-hop wireless sensor networks (WSNs). By exploiting the correlation of the network sensed data, a variety of data gathering schemes based on NC and CS (Compressed Data Gathering--CDG) have been proposed. However, these schemes assume that the sparsity of the network sensed data is constant and the value of the sparsity is known before starting each data gathering epoch, thus they ignore the variation of the data observed by the WSNs which are deployed in practical circumstances. In this paper, we present a complete design of the feedback CDG scheme where the sink node adaptively queries those interested nodes to acquire an appropriate number of measurements. The adaptive measurement-formation procedure and its termination rules are proposed and analyzed in detail. Moreover, in order to minimize the number of overall transmissions in the formation procedure of each measurement, we have developed a NP-complete model (Maximum Leaf Nodes Minimum Steiner Nodes--MLMS) and realized a scalable greedy algorithm to solve the problem. Experimental results show that the proposed measurement-formation method outperforms previous schemes, and experiments on both datasets from ocean temperature and practical network deployment also prove the effectiveness of our proposed feedback CDG scheme.

Ontological function annotation of long non-coding RNAs through hierarchical multi-label classification.

PubMed

Zhang, Jingpu; Zhang, Zuping; Wang, Zixiang; Liu, Yuting; Deng, Lei

2018-05-15

Long non-coding RNAs (lncRNAs) are an enormous collection of functional non-coding RNAs. Over the past decades, a large number of novel lncRNA genes have been identified. However, most of the lncRNAs remain function uncharacterized at present. Computational approaches provide a new insight to understand the potential functional implications of lncRNAs. Considering that each lncRNA may have multiple functions and a function may be further specialized into sub-functions, here we describe NeuraNetL2GO, a computational ontological function prediction approach for lncRNAs using hierarchical multi-label classification strategy based on multiple neural networks. The neural networks are incrementally trained level by level, each performing the prediction of gene ontology (GO) terms belonging to a given level. In NeuraNetL2GO, we use topological features of the lncRNA similarity network as the input of the neural networks and employ the output results to annotate the lncRNAs. We show that NeuraNetL2GO achieves the best performance and the overall advantage in maximum F-measure and coverage on the manually annotated lncRNA2GO-55 dataset compared to other state-of-the-art methods. The source code and data are available at http://denglab.org/NeuraNetL2GO/. leideng@csu.edu.cn. Supplementary data are available at Bioinformatics online.

Learning vector quantization neural networks improve accuracy of transcranial color-coded duplex sonography in detection of middle cerebral artery spasm--preliminary report.

PubMed

Swiercz, Miroslaw; Kochanowicz, Jan; Weigele, John; Hurst, Robert; Liebeskind, David S; Mariak, Zenon; Melhem, Elias R; Krejza, Jaroslaw

2008-01-01

To determine the performance of an artificial neural network in transcranial color-coded duplex sonography (TCCS) diagnosis of middle cerebral artery (MCA) spasm. TCCS was prospectively acquired within 2 h prior to routine cerebral angiography in 100 consecutive patients (54M:46F, median age 50 years). Angiographic MCA vasospasm was classified as mild (<25% of vessel caliber reduction), moderate (25-50%), or severe (>50%). A Learning Vector Quantization neural network classified MCA spasm based on TCCS peak-systolic, mean, and end-diastolic velocity data. During a four-class discrimination task, accurate classification by the network ranged from 64.9% to 72.3%, depending on the number of neurons in the Kohonen layer. Accurate classification of vasospasm ranged from 79.6% to 87.6%, with an accuracy of 84.7% to 92.1% for the detection of moderate-to-severe vasospasm. An artificial neural network may increase the accuracy of TCCS in diagnosis of MCA spasm.

Evaluation of in-network adaptation of scalable high efficiency video coding (SHVC) in mobile environments

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos; Goma, Sergio

2014-02-01

High Efficiency Video Coding (HEVC), the latest video compression standard (also known as H.265), can deliver video streams of comparable quality to the current H.264 Advanced Video Coding (H.264/AVC) standard with a 50% reduction in bandwidth. Research into SHVC, the scalable extension to the HEVC standard, is still in its infancy. One important area for investigation is whether, given the greater compression ratio of HEVC (and SHVC), the loss of packets containing video content will have a greater impact on the quality of delivered video than is the case with H.264/AVC or its scalable extension H.264/SVC. In this work we empirically evaluate the layer-based, in-network adaptation of video streams encoded using SHVC in situations where dynamically changing bandwidths and datagram loss ratios require the real-time adaptation of video streams. Through the use of extensive experimentation, we establish a comprehensive set of benchmarks for SHVC-based highdefinition video streaming in loss prone network environments such as those commonly found in mobile networks. Among other results, we highlight that packet losses of only 1% can lead to a substantial reduction in PSNR of over 3dB and error propagation in over 130 pictures following the one in which the loss occurred. This work would be one of the earliest studies in this cutting-edge area that reports benchmark evaluation results for the effects of datagram loss on SHVC picture quality and offers empirical and analytical insights into SHVC adaptation to lossy, mobile networking conditions.

Software-codec-based full motion video conferencing on the PC using visual pattern image sequence coding

NASA Astrophysics Data System (ADS)

Barnett, Barry S.; Bovik, Alan C.

1995-04-01

This paper presents a real time full motion video conferencing system based on the Visual Pattern Image Sequence Coding (VPISC) software codec. The prototype system hardware is comprised of two personal computers, two camcorders, two frame grabbers, and an ethernet connection. The prototype system software has a simple structure. It runs under the Disk Operating System, and includes a user interface, a video I/O interface, an event driven network interface, and a free running or frame synchronous video codec that also acts as the controller for the video and network interfaces. Two video coders have been tested in this system. Simple implementations of Visual Pattern Image Coding and VPISC have both proven to support full motion video conferencing with good visual quality. Future work will concentrate on expanding this prototype to support the motion compensated version of VPISC, as well as encompassing point-to-point modem I/O and multiple network protocols. The application will be ported to multiple hardware platforms and operating systems. The motivation for developing this prototype system is to demonstrate the practicality of software based real time video codecs. Furthermore, software video codecs are not only cheaper, but are more flexible system solutions because they enable different computer platforms to exchange encoded video information without requiring on-board protocol compatible video codex hardware. Software based solutions enable true low cost video conferencing that fits the `open systems' model of interoperability that is so important for building portable hardware and software applications.

Minimal Increase Network Coding for Dynamic Networks.

PubMed

Zhang, Guoyin; Fan, Xu; Wu, Yanxia

2016-01-01

Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery.

Minimal Increase Network Coding for Dynamic Networks

PubMed Central

Wu, Yanxia

2016-01-01

Because of the mobility, computing power and changeable topology of dynamic networks, it is difficult for random linear network coding (RLNC) in static networks to satisfy the requirements of dynamic networks. To alleviate this problem, a minimal increase network coding (MINC) algorithm is proposed. By identifying the nonzero elements of an encoding vector, it selects blocks to be encoded on the basis of relationship between the nonzero elements that the controls changes in the degrees of the blocks; then, the encoding time is shortened in a dynamic network. The results of simulations show that, compared with existing encoding algorithms, the MINC algorithm provides reduced computational complexity of encoding and an increased probability of delivery. PMID:26867211

Neural network decoder for quantum error correcting codes

NASA Astrophysics Data System (ADS)

Krastanov, Stefan; Jiang, Liang

Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.

In-network Coding for Resilient Sensor Data Storage and Efficient Data Mule Collection

NASA Astrophysics Data System (ADS)

Albano, Michele; Gao, Jie

In a sensor network of n nodes in which k of them have sensed interesting data, we perform in-network erasure coding such that each node stores a linear combination of all the network data with random coefficients. This scheme greatly improves data resilience to node failures: as long as there are k nodes that survive an attack, all the data produced in the sensor network can be recovered with high probability. The in-network coding storage scheme also improves data collection rate by mobile mules and allows for easy scheduling of data mules.

Network Coding on Heterogeneous Multi-Core Processors for Wireless Sensor Networks

PubMed Central

Kim, Deokho; Park, Karam; Ro, Won W.

2011-01-01

While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine. PMID:22164053

Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model

NASA Astrophysics Data System (ADS)

Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu

2018-01-01

We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

PubMed Central

Shlizerman, Eli; Riffell, Jeffrey A.; Kutz, J. Nathan

2014-01-01

The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns. PMID:25165442

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

PubMed Central

Mozumdar, Mohammad; Song, Zhen Yu; Lavagno, Luciano; Sangiovanni-Vincentelli, Alberto L.

2014-01-01

The Model Based Design (MBD) approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs) are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL) simulation. PMID:24960083

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

PubMed

Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

2016-06-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

Recent advances in coding theory for near error-free communications

NASA Technical Reports Server (NTRS)

Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.

1991-01-01

Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.

Reliable Wireless Broadcast with Linear Network Coding for Multipoint-to-Multipoint Real-Time Communications

NASA Astrophysics Data System (ADS)

Kondo, Yoshihisa; Yomo, Hiroyuki; Yamaguchi, Shinji; Davis, Peter; Miura, Ryu; Obana, Sadao; Sampei, Seiichi

This paper proposes multipoint-to-multipoint (MPtoMP) real-time broadcast transmission using network coding for ad-hoc networks like video game networks. We aim to achieve highly reliable MPtoMP broadcasting using IEEE 802.11 media access control (MAC) that does not include a retransmission mechanism. When each node detects packets from the other nodes in a sequence, the correctly detected packets are network-encoded, and the encoded packet is broadcasted in the next sequence as a piggy-back for its native packet. To prevent increase of overhead in each packet due to piggy-back packet transmission, network coding vector for each node is exchanged between all nodes in the negotiation phase. Each user keeps using the same coding vector generated in the negotiation phase, and only coding information that represents which user signal is included in the network coding process is transmitted along with the piggy-back packet. Our simulation results show that the proposed method can provide higher reliability than other schemes using multi point relay (MPR) or redundant transmissions such as forward error correction (FEC). We also implement the proposed method in a wireless testbed, and show that the proposed method achieves high reliability in a real-world environment with a practical degree of complexity when installed on current wireless devices.

Computer Code for Transportation Network Design and Analysis

DOT National Transportation Integrated Search

1977-01-01

This document describes the results of research into the application of the mathematical programming technique of decomposition to practical transportation network problems. A computer code called Catnap (for Control Analysis Transportation Network A...

Diffusion and Equilibrium Swelling of Macromolecular Networks by Their Linear Homologs.

DTIC Science & Technology

1982-10-01

C/ . 29 OYN 6/81 DISTRIBUTION LIST No. Copies No. Copies Dr. L.V. Schmtdt 1 Dr. F. Roberto 1 Assistant Secretary of the Navy Code AFRPL MKPA (RE, and...Scientific Advisor Directorate of Aerospace Sciences Commandant of the Marine Corps Bolling Air Force Base Code RD-1 Washington, D.C. 20332 Washington...Directorate of Chemical Sciences Arlington VA 22217 Bolling Air Force Base t VWashington, D.C. 20332 Mr. David Siegel Office of Naval Research Dr. John S

Time-Reversal Based Range Extension Technique for Ultra-Wideband (UWB) Sensors and Applications in Tactical Communications and Networking

DTIC Science & Technology

2007-07-16

issue to find a proper acquisition strategy and to optimize the algorithm. So far a two-stage acquisition algorithm based on the optical orthogonal...vol.5, May 11-15, 2003, pp. 3530-3534. [23] M. Weisenhorn and W. Hirt, "Robust noncoherent receiver exploiting UWB channel properties," in Proc. IEEE...PRF) and data rate, are programmable. I Depending on the propagation environments, either the Barker code or the optical orthogonal codes (OOC) [53

Finding meaning in social media: content-based social network analysis of QuitNet to identify new opportunities for health promotion.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2013-01-01

Unhealthy behaviors increase individual health risks and are a socioeconomic burden. Harnessing social influence is perceived as fundamental for interventions to influence health-related behaviors. However, the mechanisms through which social influence occurs are poorly understood. Online social networks provide the opportunity to understand these mechanisms as they digitally archive communication between members. In this paper, we present a methodology for content-based social network analysis, combining qualitative coding, automated text analysis, and formal network analysis such that network structure is determined by the content of messages exchanged between members. We apply this approach to characterize the communication between members of QuitNet, an online social network for smoking cessation. Results indicate that the method identifies meaningful theme-based social sub-networks. Modeling social network data using this method can provide us with theme-specific insights such as the identities of opinion leaders and sub-community clusters. Implications for design of targeted social interventions are discussed.

Apply network coding for H.264/SVC multicasting

NASA Astrophysics Data System (ADS)

Wang, Hui; Kuo, C.-C. Jay

2008-08-01

In a packet erasure network environment, video streaming benefits from error control in two ways to achieve graceful degradation. The first approach is application-level (or the link-level) forward error-correction (FEC) to provide erasure protection. The second error control approach is error concealment at the decoder end to compensate lost packets. A large amount of research work has been done in the above two areas. More recently, network coding (NC) techniques have been proposed for efficient data multicast over networks. It was shown in our previous work that multicast video streaming benefits from NC for its throughput improvement. An algebraic model is given to analyze the performance in this work. By exploiting the linear combination of video packets along nodes in a network and the SVC video format, the system achieves path diversity automatically and enables efficient video delivery to heterogeneous receivers in packet erasure channels. The application of network coding can protect video packets against the erasure network environment. However, the rank defficiency problem of random linear network coding makes the error concealment inefficiently. It is shown by computer simulation that the proposed NC video multicast scheme enables heterogenous receiving according to their capacity constraints. But it needs special designing to improve the video transmission performance when applying network coding.

Implementing MANETS in Android based environment using Wi-Fi direct

NASA Astrophysics Data System (ADS)

Waqas, Muhammad; Babar, Mohammad Inayatullah Khan; Zafar, Mohammad Haseeb

2015-05-01

Packet loss occurs in real-time voice transmission over wireless broadcast Ad-hoc network which creates disruptions in sound. Basic objective of this research is to design a wireless Ad-hoc network based on two Android devices by using the Wireless Fidelity (WIFI) Direct Application Programming Interface (API) and apply the Network Codec, Reed Solomon Code. The network codec is used to encode the data of a music wav file and recover the lost packets if any, packets are dropped using a loss module at the transmitter device to analyze the performance with the objective of retrieving the original file at the receiver device using the network codec. This resulted in faster transmission of the files despite dropped packets. In the end both files had the original formatted music files with complete performance analysis based on the transmission delay.

Error-correcting codes on scale-free networks

NASA Astrophysics Data System (ADS)

Kim, Jung-Hoon; Ko, Young-Jo

2004-06-01

We investigate the potential of scale-free networks as error-correcting codes. We find that irregular low-density parity-check codes with the highest performance known to date have degree distributions well fitted by a power-law function p (k) ˜ k-γ with γ close to 2, which suggests that codes built on scale-free networks with appropriate power exponents can be good error-correcting codes, with a performance possibly approaching the Shannon limit. We demonstrate for an erasure channel that codes with a power-law degree distribution of the form p (k) = C (k+α)-γ , with k⩾2 and suitable selection of the parameters α and γ , indeed have very good error-correction capabilities.

Programmed optoelectronic time-pulse coded relational processor as base element for sorting neural networks

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Bardachenko, Vitaliy F.; Nikolsky, Alexander I.; Lazarev, Alexander A.

2007-04-01

In the paper we show that the biologically motivated conception of the use of time-pulse encoding gives the row of advantages (single methodological basis, universality, simplicity of tuning, training and programming et al) at creation and designing of sensor systems with parallel input-output and processing, 2D-structures of hybrid and neuro-fuzzy neurocomputers of next generations. We show principles of construction of programmable relational optoelectronic time-pulse coded processors, continuous logic, order logic and temporal waves processes, that lie in basis of the creation. We consider structure that executes extraction of analog signal of the set grade (order), sorting of analog and time-pulse coded variables. We offer optoelectronic realization of such base relational elements of order logic, which consists of time-pulse coded phototransformers (pulse-width and pulse-phase modulators) with direct and complementary outputs, sorting network on logical elements and programmable commutations blocks. We make estimations of basic technical parameters of such base devices and processors on their basis by simulation and experimental research: power of optical input signals - 0.200-20 μW, processing time - microseconds, supply voltage - 1.5-10 V, consumption power - hundreds of microwatts per element, extended functional possibilities, training possibilities. We discuss some aspects of possible rules and principles of training and programmable tuning on the required function, relational operation and realization of hardware blocks for modifications of such processors. We show as on the basis of such quasiuniversal hardware simple block and flexible programmable tuning it is possible to create sorting machines, neural networks and hybrid data-processing systems with the untraditional numerical systems and pictures operands.

User's manual for a material transport code on the Octopus Computer Network

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

Naymik, T.G.; Mendez, G.D.

1978-09-15

A code to simulate material transport through porous media was developed at Oak Ridge National Laboratory. This code has been modified and adapted for use at Lawrence Livermore Laboratory. This manual, in conjunction with report ORNL-4928, explains the input, output, and execution of the code on the Octopus Computer Network.

Coded Cooperation for Multiway Relaying in Wireless Sensor Networks †

PubMed Central

Si, Zhongwei; Ma, Junyang; Thobaben, Ragnar

2015-01-01

Wireless sensor networks have been considered as an enabling technology for constructing smart cities. One important feature of wireless sensor networks is that the sensor nodes collaborate in some manner for communications. In this manuscript, we focus on the model of multiway relaying with full data exchange where each user wants to transmit and receive data to and from all other users in the network. We derive the capacity region for this specific model and propose a coding strategy through coset encoding. To obtain good performance with practical codes, we choose spatially-coupled LDPC (SC-LDPC) codes for the coded cooperation. In particular, for the message broadcasting from the relay, we construct multi-edge-type (MET) SC-LDPC codes by repeatedly applying coset encoding. Due to the capacity-achieving property of the SC-LDPC codes, we prove that the capacity region can theoretically be achieved by the proposed MET SC-LDPC codes. Numerical results with finite node degrees are provided, which show that the achievable rates approach the boundary of the capacity region in both binary erasure channels and additive white Gaussian channels. PMID:26131675

Coded Cooperation for Multiway Relaying in Wireless Sensor Networks.

PubMed

Si, Zhongwei; Ma, Junyang; Thobaben, Ragnar

2015-06-29

Wireless sensor networks have been considered as an enabling technology for constructing smart cities. One important feature of wireless sensor networks is that the sensor nodes collaborate in some manner for communications. In this manuscript, we focus on the model of multiway relaying with full data exchange where each user wants to transmit and receive data to and from all other users in the network. We derive the capacity region for this specific model and propose a coding strategy through coset encoding. To obtain good performance with practical codes, we choose spatially-coupled LDPC (SC-LDPC) codes for the coded cooperation. In particular, for the message broadcasting from the relay, we construct multi-edge-type (MET) SC-LDPC codes by repeatedly applying coset encoding. Due to the capacity-achieving property of the SC-LDPC codes, we prove that the capacity region can theoretically be achieved by the proposed MET SC-LDPC codes. Numerical results with finite node degrees are provided, which show that the achievable rates approach the boundary of the capacity region in both binary erasure channels and additive white Gaussian channels.

Digital video technologies and their network requirements

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

R. P. Tsang; H. Y. Chen; J. M. Brandt

1999-11-01

Coded digital video signals are considered to be one of the most difficult data types to transport due to their real-time requirements and high bit rate variability. In this study, the authors discuss the coding mechanisms incorporated by the major compression standards bodies, i.e., JPEG and MPEG, as well as more advanced coding mechanisms such as wavelet and fractal techniques. The relationship between the applications which use these coding schemes and their network requirements are the major focus of this study. Specifically, the authors relate network latency, channel transmission reliability, random access speed, buffering and network bandwidth with the variousmore » coding techniques as a function of the applications which use them. Such applications include High-Definition Television, Video Conferencing, Computer-Supported Collaborative Work (CSCW), and Medical Imaging.« less

Automated Construction of Node Software Using Attributes in a Ubiquitous Sensor Network Environment

PubMed Central

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric—the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment. PMID:22163678

Automated construction of node software using attributes in a ubiquitous sensor network environment.

PubMed

Lee, Woojin; Kim, Juil; Kang, JangMook

2010-01-01

In sensor networks, nodes must often operate in a demanding environment facing restrictions such as restricted computing resources, unreliable wireless communication and power shortages. Such factors make the development of ubiquitous sensor network (USN) applications challenging. To help developers construct a large amount of node software for sensor network applications easily and rapidly, this paper proposes an approach to the automated construction of node software for USN applications using attributes. In the proposed technique, application construction proceeds by first developing a model for the sensor network and then designing node software by setting the values of the predefined attributes. After that, the sensor network model and the design of node software are verified. The final source codes of the node software are automatically generated from the sensor network model. We illustrate the efficiency of the proposed technique by using a gas/light monitoring application through a case study of a Gas and Light Monitoring System based on the Nano-Qplus operating system. We evaluate the technique using a quantitative metric-the memory size of execution code for node software. Using the proposed approach, developers are able to easily construct sensor network applications and rapidly generate a large number of node softwares at a time in a ubiquitous sensor network environment.

Spike Code Flow in Cultured Neuronal Networks.

PubMed

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Single-wavelength based Thai jasmine rice identification with polynomial fitting function and neural network analysis

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2013-06-01

We previously showed that a combination of image thresholding, chain coding, elliptic Fourier descriptors, and artificial neural network analysis provided a low false acceptance rate (FAR) and a false rejection rate (FRR) of 11.0% and 19.0%, respectively, in identify Thai jasmine rice from three unwanted rice varieties. In this work, we highlight that only a polynomial function fitting on the determined chain code and the neural network analysis are highly sufficient in obtaining a very low FAR of < 3.0% and a very low 0.3% FRR for the separation of Thai jasmine rice from Chainat 1 (CNT1), Prathumtani 1 (PTT1), and Hom-Pitsanulok (HPSL) rice varieties. With this proposed approach, the analytical time is tremendously suppressed from 4,250 seconds down to 2 seconds, implying extremely high potential in practical deployment.

Coding Local and Global Binary Visual Features Extracted From Video Sequences.

PubMed

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the bag-of-visual word model. Several applications, including, for example, visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget while attaining a target level of efficiency. In this paper, we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can conveniently be adopted to support the analyze-then-compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs the visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the compress-then-analyze (CTA) paradigm. In this paper, we experimentally compare the ATC and the CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: 1) homography estimation and 2) content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with the CTA, especially in bandwidth limited scenarios.

Coding Local and Global Binary Visual Features Extracted From Video Sequences

NASA Astrophysics Data System (ADS)

Baroffio, Luca; Canclini, Antonio; Cesana, Matteo; Redondi, Alessandro; Tagliasacchi, Marco; Tubaro, Stefano

2015-11-01

Binary local features represent an effective alternative to real-valued descriptors, leading to comparable results for many visual analysis tasks, while being characterized by significantly lower computational complexity and memory requirements. When dealing with large collections, a more compact representation based on global features is often preferred, which can be obtained from local features by means of, e.g., the Bag-of-Visual-Word (BoVW) model. Several applications, including for example visual sensor networks and mobile augmented reality, require visual features to be transmitted over a bandwidth-limited network, thus calling for coding techniques that aim at reducing the required bit budget, while attaining a target level of efficiency. In this paper we investigate a coding scheme tailored to both local and global binary features, which aims at exploiting both spatial and temporal redundancy by means of intra- and inter-frame coding. In this respect, the proposed coding scheme can be conveniently adopted to support the Analyze-Then-Compress (ATC) paradigm. That is, visual features are extracted from the acquired content, encoded at remote nodes, and finally transmitted to a central controller that performs visual analysis. This is in contrast with the traditional approach, in which visual content is acquired at a node, compressed and then sent to a central unit for further processing, according to the Compress-Then-Analyze (CTA) paradigm. In this paper we experimentally compare ATC and CTA by means of rate-efficiency curves in the context of two different visual analysis tasks: homography estimation and content-based retrieval. Our results show that the novel ATC paradigm based on the proposed coding primitives can be competitive with CTA, especially in bandwidth limited scenarios.

Soft-Input Soft-Output Modules for the Construction and Distributed Iterative Decoding of Code Networks

NASA Technical Reports Server (NTRS)

Benedetto, S.; Divsalar, D.; Montorsi, G.; Pollara, F.

1998-01-01

Soft-input soft-output building blocks (modules) are presented to construct and iteratively decode in a distributed fashion code networks, a new concept that includes, and generalizes, various forms of concatenated coding schemes.

Predictive Coding of Dynamical Variables in Balanced Spiking Networks

PubMed Central

Boerlin, Martin; Machens, Christian K.; Denève, Sophie

2013-01-01

Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated. PMID:24244113

Clustering of neural code words revealed by a first-order phase transition

NASA Astrophysics Data System (ADS)

Huang, Haiping; Toyoizumi, Taro

2016-06-01

A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

Systematic network coding for two-hop lossy transmissions

NASA Astrophysics Data System (ADS)

Li, Ye; Blostein, Steven; Chan, Wai-Yip

2015-12-01

In this paper, we consider network transmissions over a single or multiple parallel two-hop lossy paths. These scenarios occur in applications such as sensor networks or WiFi offloading. Random linear network coding (RLNC), where previously received packets are re-encoded at intermediate nodes and forwarded, is known to be a capacity-achieving approach for these networks. However, a major drawback of RLNC is its high encoding and decoding complexity. In this work, a systematic network coding method is proposed. We show through both analysis and simulation that the proposed method achieves higher end-to-end rate as well as lower computational cost than RLNC for finite field sizes and finite-sized packet transmissions.

Design and simulation of programmable relational optoelectronic time-pulse coded processors as base elements for sorting neural networks

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Lazareva, Maria V.

2010-05-01

In the paper we show that the biologically motivated conception of time-pulse encoding usage gives a set of advantages (single methodological basis, universality, tuning simplicity, learning and programming et al) at creation and design of sensor systems with parallel input-output and processing for 2D structures hybrid and next generations neuro-fuzzy neurocomputers. We show design principles of programmable relational optoelectronic time-pulse encoded processors on the base of continuous logic, order logic and temporal waves processes. We consider a structure that execute analog signal extraction, analog and time-pulse coded variables sorting. We offer optoelectronic realization of such base relational order logic element, that consists of time-pulse coded photoconverters (pulse-width and pulse-phase modulators) with direct and complementary outputs, sorting network on logical elements and programmable commutation blocks. We make technical parameters estimations of devices and processors on such base elements by simulation and experimental research: optical input signals power 0.2 - 20 uW, processing time 1 - 10 us, supply voltage 1 - 3 V, consumption power 10 - 100 uW, extended functional possibilities, learning possibilities. We discuss some aspects of possible rules and principles of learning and programmable tuning on required function, relational operation and realization of hardware blocks for modifications of such processors. We show that it is possible to create sorting machines, neural networks and hybrid data-processing systems with untraditional numerical systems and pictures operands on the basis of such quasiuniversal hardware simple blocks with flexible programmable tuning.

BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

PubMed

Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

2009-02-15

BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

[Measurement and performance analysis of functional neural network].

PubMed

Li, Shan; Liu, Xinyu; Chen, Yan; Wan, Hong

2018-04-01

The measurement of network is one of the important researches in resolving neuronal population information processing mechanism using complex network theory. For the quantitative measurement problem of functional neural network, the relation between the measure indexes, i.e. the clustering coefficient, the global efficiency, the characteristic path length and the transitivity, and the network topology was analyzed. Then, the spike-based functional neural network was established and the simulation results showed that the measured network could represent the original neural connections among neurons. On the basis of the former work, the coding of functional neural network in nidopallium caudolaterale (NCL) about pigeon's motion behaviors was studied. We found that the NCL functional neural network effectively encoded the motion behaviors of the pigeon, and there were significant differences in four indexes among the left-turning, the forward and the right-turning. Overall, the establishment method of spike-based functional neural network is available and it is an effective tool to parse the brain information processing mechanism.

Technology Infusion of CodeSonar into the Space Network Ground Segment

NASA Technical Reports Server (NTRS)

Benson, Markland J.

2009-01-01

This slide presentation reviews the applicability of CodeSonar to the Space Network software. CodeSonar is a commercial off the shelf system that analyzes programs written in C, C++ or Ada for defects in the code. Software engineers use CodeSonar results as an input to the existing source code inspection process. The study is focused on large scale software developed using formal processes. The systems studied are mission critical in nature but some use commodity computer systems.

On Delay and Security in Network Coding

ERIC Educational Resources Information Center

Dikaliotis, Theodoros K.

2013-01-01

In this thesis, delay and security issues in network coding are considered. First, we study the delay incurred in the transmission of a fixed number of packets through acyclic networks comprised of erasure links. The two transmission schemes studied are routing with hop-by-hop retransmissions, where every node in the network simply stores and…

An Architecture for Coexistence with Multiple Users in Frequency Hopping Cognitive Radio Networks

DTIC Science & Technology

2013-03-01

the base WARP system, a custom IP core written in VHDL , and the Virtex IV’s embedded PowerPC core with C code to implement the radio and hopset...shown in Appendix C as Figure C.2. All VHDL code necessary to implement this IP core is included in Appendix G. 69 Figure 3.19: FPGA bus structure...subsystem functionality. A total of 1,430 lines of VHDL code were implemented for this research. 1 library ieee; 2 use ieee.std logic 1164.all; 3 use

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

DTIC Science & Technology

2011-03-01

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

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

PubMed Central

Thibodeau, Asa; Márquez, Eladio J.; Luo, Oscar; Ruan, Yijun; Shin, Dong-Guk; Stitzel, Michael L.; Ucar, Duygu

2016-01-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. AVAILABILITY: QuIN’s web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/. PMID:27336171

GLOBECOM '88 - IEEE Global Telecommunications Conference and Exhibition, Hollywood, FL, Nov. 28-Dec. 1, 1988, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Various papers on communications for the information age are presented. Among the general topics considered are: telematic services and terminals, satellite communications, telecommunications mangaement network, control of integrated broadband networks, advances in digital radio systems, the intelligent network, broadband networks and services deployment, future switch architectures, performance analysis of computer networks, advances in spread spectrum, optical high-speed LANs, and broadband switching and networks. Also addressed are: multiple access protocols, video coding techniques, modulation and coding, photonic switching, SONET terminals and applications, standards for video coding, digital switching, progress in MANs, mobile and portable radio, software design for improved maintainability, multipath propagation and advanced countermeasure, data communication, network control and management, fiber in the loop, network algorithm and protocols, and advances in computer communications.

Non-binary LDPC-coded modulation for high-speed optical metro networks with backpropagation

NASA Astrophysics Data System (ADS)

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

2010-01-01

To simultaneously mitigate the linear and nonlinear channel impairments in high-speed optical communications, we propose the use of non-binary low-density-parity-check-coded modulation in combination with a coarse backpropagation method. By employing backpropagation, we reduce the memory in the channel and in return obtain significant reductions in the complexity of the channel equalizer which is exponentially proportional to the channel memory. We then compensate for the remaining channel distortions using forward error correction based on non-binary LDPC codes. We propose non-binary-LDPC-coded modulation scheme because, compared to bit-interleaved binary-LDPC-coded modulation scheme employing turbo equalization, the proposed scheme lowers the computational complexity and latency of the overall system while providing impressively larger coding gains.

Time-Reversal Based Range Extension Technique for Ultra-wideband (UWB) Sensors and Applications in Tactical Communications and Networking

DTIC Science & Technology

2007-10-16

ABSTRACT c. THIS PAGE ABSTRACT OF Francis Otuonye P U UU24 19b. TELEPHONE NUMBER (Include area code ) 24 931-372-3374 Standard Form 298 (Rev. 8/98...modulation pulse wavefom--sotware defined or cognitive. From a information-theoretical viewpoint, the two parts as a whole form so-called "pre- coding ". I...The time domain system Fig. 2.3(b) is based on digital sampling oscilloscope (DSO), Textronix TDS 7000E3. The time domain sounder has the capability

pyNBS: A Python implementation for network-based stratification of tumor mutations.

PubMed

Huang, Justin K; Jia, Tongqiu; Carlin, Daniel E; Ideker, Trey

2018-03-28

We present pyNBS: a modularized Python 2.7 implementation of the network-based stratification (NBS) algorithm for stratifying tumor somatic mutation profiles into molecularly and clinically relevant subtypes. In addition to release of the software, we benchmark its key parameters and provide a compact cancer reference network that increases the significance of tumor stratification using the NBS algorithm. The structure of the code exposes key steps of the algorithm to foster further collaborative development. The package, along with examples and data, can be downloaded and installed from the URL http://www.github.com/huangger/pyNBS/. jkh013@ucsd.edu.

CFD Code Development for Combustor Flows

NASA Technical Reports Server (NTRS)

Norris, Andrew

2003-01-01

During the lifetime of this grant, work has been performed in the areas of model development, code development, code validation and code application. For model development, this has included the PDF combustion module, chemical kinetics based on thermodynamics, neural network storage of chemical kinetics, ILDM chemical kinetics and assumed PDF work. Many of these models were then implemented in the code, and in addition many improvements were made to the code, including the addition of new chemistry integrators, property evaluation schemes, new chemistry models and turbulence-chemistry interaction methodology. Validation of all new models and code improvements were also performed, while application of the code to the ZCET program and also the NPSS GEW combustor program were also performed. Several important items remain under development, including the NOx post processing, assumed PDF model development and chemical kinetic development. It is expected that this work will continue under the new grant.

Ad-Hoc Networks and the Mobile Application Security System (MASS)

DTIC Science & Technology

2006-01-01

solution to this problem that addresses critical aspects of security in ad-hoc mobile application networks. This approach involves preventing unauthorized...modification of a mobile application , both by other applications and by hosts, and ensuring that mobile code is authentic and authorized. These...capabilities constitute the Mobile Application Security System (MASS). The MASS applies effective, robust security to mobile application -based systems

Deep generative learning of location-invariant visual word recognition.

PubMed

Di Bono, Maria Grazia; Zorzi, Marco

2013-01-01

It is widely believed that orthographic processing implies an approximate, flexible coding of letter position, as shown by relative-position and transposition priming effects in visual word recognition. These findings have inspired alternative proposals about the representation of letter position, ranging from noisy coding across the ordinal positions to relative position coding based on open bigrams. This debate can be cast within the broader problem of learning location-invariant representations of written words, that is, a coding scheme abstracting the identity and position of letters (and combinations of letters) from their eye-centered (i.e., retinal) locations. We asked whether location-invariance would emerge from deep unsupervised learning on letter strings and what type of intermediate coding would emerge in the resulting hierarchical generative model. We trained a deep network with three hidden layers on an artificial dataset of letter strings presented at five possible retinal locations. Though word-level information (i.e., word identity) was never provided to the network during training, linear decoding from the activity of the deepest hidden layer yielded near-perfect accuracy in location-invariant word recognition. Conversely, decoding from lower layers yielded a large number of transposition errors. Analyses of emergent internal representations showed that word selectivity and location invariance increased as a function of layer depth. Word-tuning and location-invariance were found at the level of single neurons, but there was no evidence for bigram coding. Finally, the distributed internal representation of words at the deepest layer showed higher similarity to the representation elicited by the two exterior letters than by other combinations of two contiguous letters, in agreement with the hypothesis that word edges have special status. These results reveal that the efficient coding of written words-which was the model's learning objective-is largely based on letter-level information.

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2004-01-01

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

All-optical OFDM network coding scheme for all-optical virtual private communication in PON

NASA Astrophysics Data System (ADS)

Li, Lijun; Gu, Rentao; Ji, Yuefeng; Bai, Lin; Huang, Zhitong

2014-03-01

A novel optical orthogonal frequency division multiplexing (OFDM) network coding scheme is proposed over passive optical network (PON) system. The proposed scheme for all-optical virtual private network (VPN) does not only improve transmission efficiency, but also realize full-duplex communication mode in a single fiber. Compared with the traditional all-optical VPN architectures, the all-optical OFDM network coding scheme can support higher speed, more flexible bandwidth allocation, and higher spectrum efficiency. In order to reduce the difficulty of alignment for encoding operation between inter-communication traffic, the width of OFDM subcarrier pulse is stretched in our proposed scheme. The feasibility of all-optical OFDM network coding scheme for VPN is verified, and the relevant simulation results show that the full-duplex inter-communication traffic stream can be transmitted successfully. Furthermore, the tolerance of misalignment existing in inter-ONUs traffic is investigated and analyzed for all-optical encoding operation, and the difficulty of pulse alignment is proved to be lower.

MHEG Based Distance Learning System on Information Superhighway.

ERIC Educational Resources Information Center

Lee, SeiHoon; Yoon, KyungSeob; Wang, ChangJong

As the need for distance education grows, requirements for the development of high-speed network-based real-time distance learning systems increases. MHEG-5 is the fifth part of the MHEG (Multimedia and Hypermedia information coding Experts Group) standard, and it defines a final-form representation for application interchange. This paper…

Evaluating the effectiveness of SW-only video coding for real-time video transmission over low-rate wireless networks

NASA Astrophysics Data System (ADS)

Bartolini, Franco; Pasquini, Cristina; Piva, Alessandro

2001-04-01

The recent development of video compression algorithms allowed the diffusion of systems for the transmission of video sequences over data networks. However, the transmission over error prone mobile communication channels is yet an open issue. In this paper, a system developed for the real time transmission of H263 video coded sequences over TETRA mobile networks is presented. TETRA is an open digital trunked radio standard defined by the European Telecommunications Standardization Institute developed for professional mobile radio users, providing full integration of voice and data services. Experimental tests demonstrate that, in spite of the low frame rate allowed by the SW only implementation of the decoder and by the low channel rate a video compression technique such as that complying with the H263 standard, is still preferable to a simpler but less effective frame based compression system.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

PubMed

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-06-02

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems

PubMed Central

González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G.; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

2017-01-01

Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named “CARMEN” are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances. PMID:28574426

Interference-Assisted Techniques for Transmission and Multiple Access in Optical Communications

NASA Astrophysics Data System (ADS)

Guan, Xun

Optical communications can be in wired or wireless form. Fiber optics communication (FOC) connects transmitters and receivers with optical fiber. Benefiting from its high bandwidth, low cost per volume and stability, it gains a significant market share in long-haul networks, access networks and data centers. Meanwhile, optical wireless communication (OWC) is also emerging as a crucial player in the communication market. In OWC, free-space optical communication (FSO) and visible light communication (VLC) are being studied and commercially deployed extensively. Interference is a common phenomenon in multi-user communication systems. In both FOC and OWC, interference has long been treated as a detrimental effect. However, it could also be beneficial to system applications. The effort of harnessing interference has spurred numerous innovations. Interesting examples are physical-layer network coding (PNC) and non-orthogonal multiple access (NOMA). The first part of this thesis in on the topic of PNC. PNC was firstly proposed in wireless communication to improve the throughput of a two-way relay network (TWRN). As a variation of network coding (NC), PNC turns the common channel interference (CCI) as a natural network coding operation. In this thesis, PNC is introduced into optical communication. Three schemes are proposed in different scenarios. Firstly, PNC is applied to a coherent optical orthogonal frequency division multiplexing (CO-OFDM) system so as to improve the throughput of the multicast network. The optical signal to noise ratio (OSNR) penalty is quite low. Secondly, we investigate the application of PNC in an OFDM passive optical network (OFDM-PON) supporting heterogeneous services. It is found that only minor receiver power penalties are observed to realize PNC-based virtual private networks (VPN), both in the wired service part and the wireless service part in an OFDM-PON with heterogeneous services. Thirdly, we innovate relay-based visible light communication (VLC) by adopting PNC, with a newly proposed phase-aligning method. PNC could improve the throughput at the bottlenecking relay node in a VLC system, and the proposed phase aligning method can improve the BER performance. The second part of this thesis discusses another interference-assisted technology in communication, that is, non-orthogonal multiple access (NOMA). NOMA multiplexes signals from multiple users in another dimension: power domain, with a non-orthogonal multiplexing in other dimensions such as time, frequency and code. Three schemes are proposed in this part. The first and the second schemes both realize NOMA in VLC, with different multiuser detection (MUD) techniques and a proposed phase pre-distortion method. Although both can decrease the system BER compared to conventional NOMA, the scheme using joint detection (JD) outperforms the one using successive interference cancellation (SIC). The third scheme investigated in this part is a combination of NOMA and a multicarrier precoding (MP) technology based on an orthogonal circulant transform matrix (OCT). This combination can avoid the complicated adaptive bit loading or electronic equalization, making NOMA more attractive in a practical system.

Population coding in sparsely connected networks of noisy neurons.

PubMed

Tripp, Bryan P; Orchard, Jeff

2012-01-01

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

14 CFR 1215.108 - Defining user service requirements.

Code of Federal Regulations, 2010 CFR

2010-01-01

... to NASA Headquarters, Code OX, Space Network Division, Washington, DC 20546. Upon review and... submitted in writing to both NASA Headquarters, Code OX, Space Network Division, and GSFC, Code 501.... Request for services within priority groups shall be negotiated with non-NASA users on a first come, first...

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

PubMed

Soltic, Snjezana; Kasabov, Nikola

2010-12-01

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

NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples.

PubMed

Yu, Hua; Jiao, Bingke; Lu, Lu; Wang, Pengfei; Chen, Shuangcheng; Liang, Chengzhi; Liu, Wei

2018-01-01

Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

Mobile Router Developed and Tested

NASA Technical Reports Server (NTRS)

Ivancic, William D.

2002-01-01

The NASA Glenn Research Center, under a NASA Space Act Agreement with Cisco Systems, has been performing joint networking research to apply Internet-based technologies and protocols to space-based communications. As a result of this research, NASA performed stringent performance testing of the mobile router, including the interaction of routing and the transport-level protocol. In addition, Cisco Systems developed the mobile router for both commercial and Government markets. The code has become part of the Cisco Systems Internetworking Operating System (IOS) as of release 12.2 (4) T--which will make this capability available to the community at large. The mobile router is software code that resides in a network router and enables entire networks to roam while maintaining connectivity to the Internet. This router code is pertinent to a myriad of applications for both Government and commercial sectors, including the "wireless battlefield." NASA and the Department of Defense will utilize this technology for near-planetary observation and sensing spacecraft. It is also a key enabling technology for aviation-based information applications. Mobile routing will make it possible for information such as weather, air traffic control, voice, and video to be transmitted to aircraft using Internet-based protocols. This technology shows great promise in reducing congested airways and mitigating aviation disasters due to bad weather. The mobile router can also be incorporated into emergency vehicles (such as ambulances and life-flight aircraft) to provide real-time connectivity back to the hospital and health-care experts, enabling the timely application of emergency care. Commercial applications include entertainment services, Internet protocol (IP) telephone, and Internet connectivity for cruise ships, commercial shipping, tour buses, aircraft, and eventually cars. A mobile router, which is based on mobile IP, allows hosts (mobile nodes) to seamlessly "roam" among various IP subnetworks. This is essential in many wireless networks. A mobile router, unlike a mobile IP node, allows entire networks to roam. Hence, a device connected to the mobile router does not need to be a mobile node because the mobile router provides the roaming capabilities. There are three basic elements in the mobile IP: the home agent, the foreign agent, and the mobile node. The home agent is a router on a mobile node's home network that tunnels datagrams for delivery to the mobile node when it is away from home. The foreign agent is a router on a remote network that provides routing services to a registered mobile node. The mobile node is a host or router that changes its point of attachment from one network or subnetwork to another. In mobile routing, virtual communications are maintained by the home agent, which forwards all packets for the mobile networks to the foreign agent. The foreign agent passes the packets to the mobile router, which then forwards the packets to the devices on its networks. As the mobile router moves, it will register with its home agent on its whereabouts via the foreign agent to assure continuous connectivity.

Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

PubMed

Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

2018-07-01

Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

Monitoring biomedical literature for post-market safety purposes by analyzing networks of text-based coded information.

PubMed

Botsis, Taxiarchis; Foster, Matthew; Kreimeyer, Kory; Pandey, Abhishek; Forshee, Richard

2017-01-01

Literature review is critical but time-consuming in the post-market surveillance of medical products. We focused on the safety signal of intussusception after the vaccination of infants with the Rotashield Vaccine in 1999 and retrieved all PubMed abstracts for rotavirus vaccines published after January 1, 1998. We used the Event-based Text-mining of Health Electronic Records system, the MetaMap tool, and the National Center for Biomedical Ontologies Annotator to process the abstracts and generate coded terms stamped with the date of publication. Data were analyzed in the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment to evaluate the intussusception-related findings before and after the release of the new rotavirus vaccines in 2006. The tight connection of intussusception with the historical signal in the first period and the absence of any safety concern for the new vaccines in the second period were verified. We demonstrated the feasibility for semi-automated solutions that may assist medical reviewers in monitoring biomedical literature.

Assessment of Microphysical Models in the National Combustion Code (NCC) for Aircraft Particulate Emissions: Particle Loss in Sampling Lines

NASA Technical Reports Server (NTRS)

Wey, Thomas; Liu, Nan-Suey

2008-01-01

This paper at first describes the fluid network approach recently implemented into the National Combustion Code (NCC) for the simulation of transport of aerosols (volatile particles and soot) in the particulate sampling systems. This network-based approach complements the other two approaches already in the NCC, namely, the lower-order temporal approach and the CFD-based approach. The accuracy and the computational costs of these three approaches are then investigated in terms of their application to the prediction of particle losses through sample transmission and distribution lines. Their predictive capabilities are assessed by comparing the computed results with the experimental data. The present work will help establish standard methodologies for measuring the size and concentration of particles in high-temperature, high-velocity jet engine exhaust. Furthermore, the present work also represents the first step of a long term effort of validating physics-based tools for the prediction of aircraft particulate emissions.

MPEG-compliant joint source/channel coding using discrete cosine transform and substream scheduling for visual communication over packet networks

NASA Astrophysics Data System (ADS)

Kim, Seong-Whan; Suthaharan, Shan; Lee, Heung-Kyu; Rao, K. R.

2001-01-01

Quality of Service (QoS)-guarantee in real-time communication for multimedia applications is significantly important. An architectural framework for multimedia networks based on substreams or flows is effectively exploited for combining source and channel coding for multimedia data. But the existing frame by frame approach which includes Moving Pictures Expert Group (MPEG) cannot be neglected because it is a standard. In this paper, first, we designed an MPEG transcoder which converts an MPEG coded stream into variable rate packet sequences to be used for our joint source/channel coding (JSCC) scheme. Second, we designed a classification scheme to partition the packet stream into multiple substreams which have their own QoS requirements. Finally, we designed a management (reservation and scheduling) scheme for substreams to support better perceptual video quality such as the bound of end-to-end jitter. We have shown that our JSCC scheme is better than two other two popular techniques by simulation and real video experiments on the TCP/IP environment.

Optimal lightpath placement on a metropolitan-area network linked with optical CDMA local nets

NASA Astrophysics Data System (ADS)

Wang, Yih-Fuh; Huang, Jen-Fa

2008-01-01

A flexible optical metropolitan-area network (OMAN) [J.F. Huang, Y.F. Wang, C.Y. Yeh, Optimal configuration of OCDMA-based MAN with multimedia services, in: 23rd Biennial Symposium on Communications, Queen's University, Kingston, Canada, May 29-June 2, 2006, pp. 144-148] structured with OCDMA linkage is proposed to support multimedia services with multi-rate or various qualities of service. To prioritize transmissions in OCDMA, the orthogonal variable spreading factor (OVSF) codes widely used in wireless CDMA are adopted. In addition, for feasible multiplexing, unipolar OCDMA modulation [L. Nguyen, B. Aazhang, J.F. Young, All-optical CDMA with bipolar codes, IEEE Electron. Lett. 31 (6) (1995) 469-470] is used to generate the code selector of multi-rate OMAN, and a flexible fiber-grating-based system is used for the equipment on OCDMA-OVSF code. These enable an OMAN to assign suitable OVSF codes when creating different-rate lightpaths. How to optimally configure a multi-rate OMAN is a challenge because of displaced lightpaths. In this paper, a genetically modified genetic algorithm (GMGA) [L.R. Chen, Flexible fiber Bragg grating encoder/decoder for hybrid wavelength-time optical CDMA, IEEE Photon. Technol. Lett. 13 (11) (2001) 1233-1235] is used to preplan lightpaths in order to optimally configure an OMAN. To evaluate the performance of the GMGA, we compared it with different preplanning optimization algorithms. Simulation results revealed that the GMGA very efficiently solved the problem.

Wilson and Domainwall Kernels on Oakforest-PACS

NASA Astrophysics Data System (ADS)

Kanamori, Issaku; Matsufuru, Hideo

2018-03-01

We report the performance of Wilson and Domainwall Kernels on a new Intel Xeon Phi Knights Landing based machine named Oakforest-PACS, which is co-hosted by University of Tokyo and Tsukuba University and is currently fastest in Japan. This machine uses Intel Omni-Path for the internode network. We compare performance with several types of implementation including that makes use of the Grid library. The code is incorporated with the code set Bridge++.

Compressive Sensing for Radar and Radar Sensor Networks

DTIC Science & Technology

2013-12-02

Zero Correlation Zone Sequence Pair Sets for MIMO Radar Inspired by recent advances in MIMO radar, we apply orthogonal phase coded waveforms to MIMO ...radar system in order to gain better range resolution and target direction finding performance [2]. We provide and investigate a generalized MIMO radar...ZCZ) sequence-Pair Set (ZCZPS). We also study the MIMO radar ambiguity function of the system using phase coded waveforms, based on which we analyze

Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

PubMed

Carpenter, Gail A.

1997-11-01

A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network.

A qualitative evaluation of a Local Professional Network programme "Baby Teeth DO Matter".

PubMed

Brocklehurst, P; Bridgman, C; Davies, G

2013-12-01

The objective of this study was to use a qualitative approach to examine the perceptions of dentists who led a health promotion programme entitled "Baby Teeth DO Matter". Semi-structured interviews were undertaken with a variety of participants in a health promotional programme facilitated by a shadow Local Professional Network. These were then recorded and transcribed verbatim. The transcripts were line numbered and subjected to thematic analysis to develop a coding frame. Overarching themes were developed from the coded transcripts by organising them into clusters based on the similarity of their meaning and checked against the coded extracts and the raw data. General Dental Practice. General Dental Practitioners. A Greater Manchester-wide prevention programme entitled "Baby teeth DO Matter". To determine the perceptions of involved clinicians and whether "clinically owned and clinically led" services add value. Eight codes were generated: "Success of the project", "Down-stream to up-stream", "Importance of clinically led and clinically owned", "Keeping the approach simple", "Importance of networking", "Importance of Dental Public Health", "Importance of task and finish" and "Threats to the future of the Local Professional Network". These were organised into three over-arching themes. "Clinically Led and Clinically Owned" projects appear to empower local practitioners and add value. They encourage community-facing practitioners, build capacity and develop personal skills;--all in accordance with the fundamental principles of the Ottawa Charter. Distributed leadership was seen to be effective and Dental Public Health input, "Task and Finishing", resources and clarity of communication were all considered to be of critical importance.

The effect of habitat modification on plant-pollinator network

NASA Astrophysics Data System (ADS)

Aminatun, Tien; Putra, Nugroho Susetya

2017-08-01

The research aimed to determine; (1) the mutualism interaction pattern of plant-pollinator on several habitat modifications; and (2) the habitat modification which showed the most stable pattern of interaction. The study was conducted in one planting season with 20 plots which each plot had 2x2 m2 width and 2 m spacing among plots, and each plot was planted with the same variety of tomato plants, i.e. "intan". Nitrogen manipulation treatment was conducted with four kinds of fertilizers, i.e. NPK (code PU), compost (code PKM), vermicompost (code PC), and manure (code PK). Each treatment had 5 plot replications. We observed the growth of tomato plants, weed and arthropod populationstwo weekly while pollinator visitation twice a week during tomato plant flowering with counting population and visitation frequence of each pollinator on each sample of tomato plants. The nectar of tomato plant flower of each treatment was tested in laboratory to see its reducing sugar and sucrose. Oganic matter and nitrogen of the soil samples of each treatment were tested in laboratory in the beginning and the end of this research. We analized the plant-pollinator network with bipartite program in R-statistics, and the abiotic and other biotic factors with descriptive analysis. The results of the research were; (1) the mutualism interaction pattern of plant-pollinator network of four treatments were varied, and (2) The pattern of plant-pollinator network of NPK fertilizer treatment showed the more stable interaction based on analysis of interaction evenness, Shannon diversity, frequency and longevity of pollinator visitation.

Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction

PubMed Central

Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

2018-01-01

The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research. PMID:29599739

Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.

PubMed

Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

2018-01-01

The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

ERIC Educational Resources Information Center

Yu, Chao

2013-01-01

In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

Mechanism on brain information processing: Energy coding

NASA Astrophysics Data System (ADS)

Wang, Rubin; Zhang, Zhikang; Jiao, Xianfa

2006-09-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, the authors present a brand new scientific theory that offers a unique mechanism for brain information processing. They demonstrate that the neural coding produced by the activity of the brain is well described by the theory of energy coding. Due to the energy coding model's ability to reveal mechanisms of brain information processing based upon known biophysical properties, they cannot only reproduce various experimental results of neuroelectrophysiology but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, they estimate that the theory has very important consequences for quantitative research of cognitive function.

A Holistic Approach to Networked Information Systems Design and Analysis

DTIC Science & Technology

2016-04-15

attain quite substantial savings. 11. Optimal algorithms for energy harvesting in wireless networks. We use a Markov- decision-process (MDP) based...approach to obtain optimal policies for transmissions . The key advantage of our approach is that it holistically considers information and energy in a...Coding technique to minimize delays and the number of transmissions in Wireless Systems. As we approach an era of ubiquitous computing with information

SOMM: A New Service Oriented Middleware for Generic Wireless Multimedia Sensor Networks Based on Code Mobility

PubMed Central

Faghih, Mohammad Mehdi; Moghaddam, Mohsen Ebrahimi

2011-01-01

Although much research in the area of Wireless Multimedia Sensor Networks (WMSNs) has been done in recent years, the programming of sensor nodes is still time-consuming and tedious. It requires expertise in low-level programming, mainly because of the use of resource constrained hardware and also the low level API provided by current operating systems. The code of the resulting systems has typically no clear separation between application and system logic. This minimizes the possibility of reusing code and often leads to the necessity of major changes when the underlying platform is changed. In this paper, we present a service oriented middleware named SOMM to support application development for WMSNs. The main goal of SOMM is to enable the development of modifiable and scalable WMSN applications. A network which uses the SOMM is capable of providing multiple services to multiple clients at the same time with the specified Quality of Service (QoS). SOMM uses a virtual machine with the ability to support mobile agents. Services in SOMM are provided by mobile agents and SOMM also provides a t space on each node which agents can use to communicate with each other. PMID:22346646

SOMM: A new service oriented middleware for generic wireless multimedia sensor networks based on code mobility.

PubMed

Faghih, Mohammad Mehdi; Moghaddam, Mohsen Ebrahimi

2011-01-01

Although much research in the area of Wireless Multimedia Sensor Networks (WMSNs) has been done in recent years, the programming of sensor nodes is still time-consuming and tedious. It requires expertise in low-level programming, mainly because of the use of resource constrained hardware and also the low level API provided by current operating systems. The code of the resulting systems has typically no clear separation between application and system logic. This minimizes the possibility of reusing code and often leads to the necessity of major changes when the underlying platform is changed. In this paper, we present a service oriented middleware named SOMM to support application development for WMSNs. The main goal of SOMM is to enable the development of modifiable and scalable WMSN applications. A network which uses the SOMM is capable of providing multiple services to multiple clients at the same time with the specified Quality of Service (QoS). SOMM uses a virtual machine with the ability to support mobile agents. Services in SOMM are provided by mobile agents and SOMM also provides a t space on each node which agents can use to communicate with each other.

Comprehensive Reconstruction and Visualization of Non-Coding Regulatory Networks in Human

PubMed Central

Bonnici, Vincenzo; Russo, Francesco; Bombieri, Nicola; Pulvirenti, Alfredo; Giugno, Rosalba

2014-01-01

Research attention has been powered to understand the functional roles of non-coding RNAs (ncRNAs). Many studies have demonstrated their deregulation in cancer and other human disorders. ncRNAs are also present in extracellular human body fluids such as serum and plasma, giving them a great potential as non-invasive biomarkers. However, non-coding RNAs have been relatively recently discovered and a comprehensive database including all of them is still missing. Reconstructing and visualizing the network of ncRNAs interactions are important steps to understand their regulatory mechanism in complex systems. This work presents ncRNA-DB, a NoSQL database that integrates ncRNAs data interactions from a large number of well established on-line repositories. The interactions involve RNA, DNA, proteins, and diseases. ncRNA-DB is available at http://ncrnadb.scienze.univr.it/ncrnadb/. It is equipped with three interfaces: web based, command-line, and a Cytoscape app called ncINetView. By accessing only one resource, users can search for ncRNAs and their interactions, build a network annotated with all known ncRNAs and associated diseases, and use all visual and mining features available in Cytoscape. PMID:25540777

Comprehensive reconstruction and visualization of non-coding regulatory networks in human.

PubMed

Bonnici, Vincenzo; Russo, Francesco; Bombieri, Nicola; Pulvirenti, Alfredo; Giugno, Rosalba

2014-01-01

Research attention has been powered to understand the functional roles of non-coding RNAs (ncRNAs). Many studies have demonstrated their deregulation in cancer and other human disorders. ncRNAs are also present in extracellular human body fluids such as serum and plasma, giving them a great potential as non-invasive biomarkers. However, non-coding RNAs have been relatively recently discovered and a comprehensive database including all of them is still missing. Reconstructing and visualizing the network of ncRNAs interactions are important steps to understand their regulatory mechanism in complex systems. This work presents ncRNA-DB, a NoSQL database that integrates ncRNAs data interactions from a large number of well established on-line repositories. The interactions involve RNA, DNA, proteins, and diseases. ncRNA-DB is available at http://ncrnadb.scienze.univr.it/ncrnadb/. It is equipped with three interfaces: web based, command-line, and a Cytoscape app called ncINetView. By accessing only one resource, users can search for ncRNAs and their interactions, build a network annotated with all known ncRNAs and associated diseases, and use all visual and mining features available in Cytoscape.

Network analysis of human diseases using Korean nationwide claims data.

PubMed

Kim, Jin Hee; Son, Ki Young; Shin, Dong Wook; Kim, Sang Hyuk; Yun, Jae Won; Shin, Jung Hyun; Kang, Mi So; Chung, Eui Heon; Yoo, Kyoung Hun; Yun, Jae Moon

2016-06-01

To investigate disease-disease associations by conducting a network analysis using Korean nationwide claims data. We used the claims data from the Health Insurance Review and Assessment Service-National Patient Sample for the year 2011. Among the 2049 disease codes in the claims data, 1154 specific disease codes were used and combined into 795 representative disease codes. We analyzed for 381 representative codes, which had a prevalence of >0.1%. For disease code pairs of a combination of 381 representative disease codes, P values were calculated by using the χ(2) test and the degrees of associations were expressed as odds ratios (ORs). For 5515 (7.62%) statistically significant disease-disease associations with a large effect size (OR>5), we constructed a human disease network consisting of 369 nodes and 5515 edges. The human disease network shows the distribution of diseases in the disease network and the relationships between diseases or disease groups, demonstrating that diseases are associated with each other, forming a complex disease network. We reviewed 5515 disease-disease associations and classified them according to underlying mechanisms. Several disease-disease associations were identified, but the evidence of these associations is not sufficient and the mechanisms underlying these associations have not been clarified yet. Further research studies are needed to investigate these associations and their underlying mechanisms. Human disease network analysis using claims data enriches the understanding of human diseases and provides new insights into disease-disease associations that can be useful in future research. Copyright © 2016 Elsevier Inc. All rights reserved.

Coding/decoding and reversibility of droplet trains in microfluidic networks.

PubMed

Fuerstman, Michael J; Garstecki, Piotr; Whitesides, George M

2007-02-09

Droplets of one liquid suspended in a second, immiscible liquid move through a microfluidic device in which a channel splits into two branches that reconnect downstream. The droplets choose a path based on the number of droplets that occupy each branch. The interaction among droplets in the channels results in complex sequences of path selection. The linearity of the flow through the microchannels, however, ensures that the behavior of the system can be reversed. This reversibility makes it possible to encrypt and decrypt signals coded in the intervals between droplets. The encoding/decoding device is a functional microfluidic system that requires droplets to navigate a network in a precise manner without the use of valves, switches, or other means of external control.

Comprehensive analysis of coding-lncRNA gene co-expression network uncovers conserved functional lncRNAs in zebrafish.

PubMed

Chen, Wen; Zhang, Xuan; Li, Jing; Huang, Shulan; Xiang, Shuanglin; Hu, Xiang; Liu, Changning

2018-05-09

Zebrafish is a full-developed model system for studying development processes and human disease. Recent studies of deep sequencing had discovered a large number of long non-coding RNAs (lncRNAs) in zebrafish. However, only few of them had been functionally characterized. Therefore, how to take advantage of the mature zebrafish system to deeply investigate the lncRNAs' function and conservation is really intriguing. We systematically collected and analyzed a series of zebrafish RNA-seq data, then combined them with resources from known database and literatures. As a result, we obtained by far the most complete dataset of zebrafish lncRNAs, containing 13,604 lncRNA genes (21,128 transcripts) in total. Based on that, a co-expression network upon zebrafish coding and lncRNA genes was constructed and analyzed, and used to predict the Gene Ontology (GO) and the KEGG annotation of lncRNA. Meanwhile, we made a conservation analysis on zebrafish lncRNA, identifying 1828 conserved zebrafish lncRNA genes (1890 transcripts) that have their putative mammalian orthologs. We also found that zebrafish lncRNAs play important roles in regulation of the development and function of nervous system; these conserved lncRNAs present a significant sequential and functional conservation, with their mammalian counterparts. By integrative data analysis and construction of coding-lncRNA gene co-expression network, we gained the most comprehensive dataset of zebrafish lncRNAs up to present, as well as their systematic annotations and comprehensive analyses on function and conservation. Our study provides a reliable zebrafish-based platform to deeply explore lncRNA function and mechanism, as well as the lncRNA commonality between zebrafish and human.

Coding and transmission of subband coded images on the Internet

NASA Astrophysics Data System (ADS)

Wah, Benjamin W.; Su, Xiao

2001-09-01

Subband-coded images can be transmitted in the Internet using either the TCP or the UDP protocol. Delivery by TCP gives superior decoding quality but with very long delays when the network is unreliable, whereas delivery by UDP has negligible delays but with degraded quality when packets are lost. Although images are delivered currently over the Internet by TCP, we study in this paper the use of UDP to deliver multi-description reconstruction-based subband-coded images. First, in order to facilitate recovery from UDP packet losses, we propose a joint sender-receiver approach for designing optimized reconstruction-based subband transform (ORB-ST) in multi-description coding (MDC). Second, we carefully evaluate the delay-quality trade-offs between the TCP delivery of SDC images and the UDP and combined TCP/UDP delivery of MDC images. Experimental results show that our proposed ORB-ST performs well in real Internet tests, and UDP and combined TCP/UDP delivery of MDC images provide a range of attractive alternatives to TCP delivery.

Decoding the genome beyond sequencing: the new phase of genomic research.

PubMed

Heng, Henry H Q; Liu, Guo; Stevens, Joshua B; Bremer, Steven W; Ye, Karen J; Abdallah, Batoul Y; Horne, Steven D; Ye, Christine J

2011-10-01

While our understanding of gene-based biology has greatly improved, it is clear that the function of the genome and most diseases cannot be fully explained by genes and other regulatory elements. Genes and the genome represent distinct levels of genetic organization with their own coding systems; Genes code parts like protein and RNA, but the genome codes the structure of genetic networks, which are defined by the whole set of genes, chromosomes and their topological interactions within a cell. Accordingly, the genetic code of DNA offers limited understanding of genome functions. In this perspective, we introduce the genome theory which calls for the departure of gene-centric genomic research. To make this transition for the next phase of genomic research, it is essential to acknowledge the importance of new genome-based biological concepts and to establish new technology platforms to decode the genome beyond sequencing. Copyright © 2011 Elsevier Inc. All rights reserved.

Network Coding Opportunities for Wireless Grids Formed by Mobile Devices

NASA Astrophysics Data System (ADS)

Nielsen, Karsten Fyhn; Madsen, Tatiana K.; Fitzek, Frank H. P.

Wireless grids have potential in sharing communication, computa-tional and storage resources making these networks more powerful, more robust, and less cost intensive. However, to enjoy the benefits of cooperative resource sharing, a number of issues should be addressed and the cost of the wireless link should be taken into account. We focus on the question how nodes can efficiently communicate and distribute data in a wireless grid. We show the potential of a network coding approach when nodes have the possibility to combine packets thus increasing the amount of information per transmission. Our implementation demonstrates the feasibility of network coding for wireless grids formed by mobile devices.

ANNarchy: a code generation approach to neural simulations on parallel hardware

PubMed Central

Vitay, Julien; Dinkelbach, Helge Ü.; Hamker, Fred H.

2015-01-01

Many modern neural simulators focus on the simulation of networks of spiking neurons on parallel hardware. Another important framework in computational neuroscience, rate-coded neural networks, is mostly difficult or impossible to implement using these simulators. We present here the ANNarchy (Artificial Neural Networks architect) neural simulator, which allows to easily define and simulate rate-coded and spiking networks, as well as combinations of both. The interface in Python has been designed to be close to the PyNN interface, while the definition of neuron and synapse models can be specified using an equation-oriented mathematical description similar to the Brian neural simulator. This information is used to generate C++ code that will efficiently perform the simulation on the chosen parallel hardware (multi-core system or graphical processing unit). Several numerical methods are available to transform ordinary differential equations into an efficient C++code. We compare the parallel performance of the simulator to existing solutions. PMID:26283957

A contourlet transform based algorithm for real-time video encoding

NASA Astrophysics Data System (ADS)

Katsigiannis, Stamos; Papaioannou, Georgios; Maroulis, Dimitris

2012-06-01

In recent years, real-time video communication over the internet has been widely utilized for applications like video conferencing. Streaming live video over heterogeneous IP networks, including wireless networks, requires video coding algorithms that can support various levels of quality in order to adapt to the network end-to-end bandwidth and transmitter/receiver resources. In this work, a scalable video coding and compression algorithm based on the Contourlet Transform is proposed. The algorithm allows for multiple levels of detail, without re-encoding the video frames, by just dropping the encoded information referring to higher resolution than needed. Compression is achieved by means of lossy and lossless methods, as well as variable bit rate encoding schemes. Furthermore, due to the transformation utilized, it does not suffer from blocking artifacts that occur with many widely adopted compression algorithms. Another highly advantageous characteristic of the algorithm is the suppression of noise induced by low-quality sensors usually encountered in web-cameras, due to the manipulation of the transform coefficients at the compression stage. The proposed algorithm is designed to introduce minimal coding delay, thus achieving real-time performance. Performance is enhanced by utilizing the vast computational capabilities of modern GPUs, providing satisfactory encoding and decoding times at relatively low cost. These characteristics make this method suitable for applications like video-conferencing that demand real-time performance, along with the highest visual quality possible for each user. Through the presented performance and quality evaluation of the algorithm, experimental results show that the proposed algorithm achieves better or comparable visual quality relative to other compression and encoding methods tested, while maintaining a satisfactory compression ratio. Especially at low bitrates, it provides more human-eye friendly images compared to algorithms utilizing block-based coding, like the MPEG family, as it introduces fuzziness and blurring instead of artificial block artifacts.

Enabling Optical Network Test Bed for 5G Tests

NASA Astrophysics Data System (ADS)

Giuntini, Marco; Grazioso, Paolo; Matera, Francesco; Valenti, Alessandro; Attanasio, Vincenzo; Di Bartolo, Silvia; Nastri, Emanuele

2017-03-01

In this work, we show some experimental approaches concerning optical network design dedicated to 5G infrastructures. In particular, we show some implementations of network slicing based on Carrier Ethernet forwarding, which will be very suitable in the context of 5G heterogeneous networks, especially looking at services for vertical enterprises. We also show how to adopt a central unit (orchestrator) to automatically manage such logical paths according to quality-of-service requirements, which can be monitored at the user location. We also illustrate how novel all-optical processes, such as the ones based on all-optical wavelength conversion, can be used for multicasting, enabling development of TV broadcasting based on 4G-5G terminals. These managing and forwarding techniques, operating on optical links, are tested in a wireless environment on Wi-Fi cells and emulating LTE and WiMAX systems by means of the NS-3 code.

Application of artificial neural networks to the design optimization of aerospace structural components

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Patnaik, Surya N.; Murthy, Pappu L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated by using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network with the code NETS. Optimum designs for new design conditions were predicted by using the trained network. Neural net prediction of optimum designs was found to be satisfactory for most of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Optimum Design of Aerospace Structural Components Using Neural Networks

NASA Technical Reports Server (NTRS)

Berke, L.; Patnaik, S. N.; Murthy, P. L. N.

1993-01-01

The application of artificial neural networks to capture structural design expertise is demonstrated. The principal advantage of a trained neural network is that it requires a trivial computational effort to produce an acceptable new design. For the class of problems addressed, the development of a conventional expert system would be extremely difficult. In the present effort, a structural optimization code with multiple nonlinear programming algorithms and an artificial neural network code NETS were used. A set of optimum designs for a ring and two aircraft wings for static and dynamic constraints were generated using the optimization codes. The optimum design data were processed to obtain input and output pairs, which were used to develop a trained artificial neural network using the code NETS. Optimum designs for new design conditions were predicted using the trained network. Neural net prediction of optimum designs was found to be satisfactory for the majority of the output design parameters. However, results from the present study indicate that caution must be exercised to ensure that all design variables are within selected error bounds.

Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

PubMed

Le, Duc-Hau; Dao, Lan T M

2018-05-23

Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has been characterized; however, our understanding of their underlying molecular mechanisms related to disease is still limited. To overcome the limitation in experimentally identifying disease-lncRNA associations, computational methods have been proposed as a powerful tool to predict such associations. These methods are usually based on the similarities between diseases or lncRNAs since it was reported that similar diseases are associated with functionally similar lncRNAs. Therefore, prediction performance is highly dependent on how well the similarities can be captured. Previous studies have calculated the similarity between two diseases by mapping exactly each disease to a single Disease Ontology (DO) term, and then use a semantic similarity measure to calculate the similarity between them. However, the problem of this approach is that a disease can be described by more than one DO terms. Until now, there is no annotation database of DO terms for diseases except for genes. In contrast, Human Phenotype Ontology (HPO) is designed to fully annotate human disease phenotypes. Therefore, in this study, we constructed disease similarity networks/matrices using HPO instead of DO. Then, we used these networks/matrices as inputs of two representative machine learning-based and network-based ranking algorithms, that is, regularized least square and heterogeneous graph-based inference, respectively. The results showed that the prediction performance of the two algorithms on HPO-based is better than that on DO-based networks/matrices. In addition, our method can predict 11 novel cancer-associated lncRNAs, which are supported by literature evidence. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Wideband Satcom Based Avionics Network with CDMA Uplink and TDM Downlink

NASA Technical Reports Server (NTRS)

Agrawal, D.; Johnson, B. S.; Madhow, U.; Ramchandran, K.; Chun, K. S.

2000-01-01

The purpose of this paper is to describe some key technical ideas behind our vision of a future satcom based digital communication network for avionics applications The key features of our design are as follows: (a) Packetized transmission to permit efficient use of system resources for multimedia traffic; (b) A time division multiplexed (TDM) satellite downlink whose physical layer is designed to operate the satellite link at maximum power efficiency. We show how powerful turbo codes (invented originally for linear modulation) can be used with nonlinear constant envelope modulation, thus permitting the satellite amplifier to operate in a power efficient nonlinear regime; (c) A code division multiple access (CDMA) satellite uplink, which permits efficient access to the satellite from multiple asynchronous users. Closed loop power control is difficult for bursty packetized traffic, especially given the large round trip delay to the satellite. We show how adaptive interference suppression techniques can be used to deal with the ensuing near-far problem; (d) Joint source-channel coding techniques are required both at the physical and the data transport layer to optimize the end-to-end performance. We describe a novel approach to multiple description image encoding at the data transport layer in this paper.

The RNA world in the 21st century-a systems approach to finding non-coding keys to clinical questions.

PubMed

Schmitz, Ulf; Naderi-Meshkin, Hojjat; Gupta, Shailendra K; Wolkenhauer, Olaf; Vera, Julio

2016-05-01

There was evidence that RNAs are a functionally rich class of molecules not only since the arrival of the next-generation sequencing technology. Non-coding RNAs (ncRNA) could be the key to accelerated diagnosis and enhanced prediction of disease and therapy outcomes as well as the design of advanced therapeutic strategies to overcome yet unsatisfactory approaches.In this review, we discuss the state of the art in RNA systems biology with focus on the application in the systems biomedicine field. We propose guidelines for analysing the role of microRNAs and long non-coding RNAs in human pathologies. We introduce RNA expression profiling and network approaches for the identification of stable and effective RNomics-based biomarkers, providing insights into the role of ncRNAs in disease regulation. Towards this, we discuss ways to model the dynamics of gene regulatory networks and signalling pathways that involve ncRNAs. We also describe data resources and computational methods for finding putative mechanisms of action of ncRNAs. Finally, we discuss avenues for the computer-aided design of novel RNA-based therapeutics. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

SoyNet: a database of co-functional networks for soybean Glycine max.

PubMed

Kim, Eiru; Hwang, Sohyun; Lee, Insuk

2017-01-04

Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

NASA Astrophysics Data System (ADS)

Xia, Weiwei; Shen, Lianfeng

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Unfolding the neutron spectrum of a NE213 scintillator using artificial neural networks.

PubMed

Sharghi Ido, A; Bonyadi, M R; Etaati, G R; Shahriari, M

2009-10-01

Artificial neural networks technology has been applied to unfold the neutron spectra from the pulse height distribution measured with NE213 liquid scintillator. Here, both the single and multi-layer perceptron neural network models have been implemented to unfold the neutron spectrum from an Am-Be neutron source. The activation function and the connectivity of the neurons have been investigated and the results have been analyzed in terms of the network's performance. The simulation results show that the neural network that utilizes the Satlins transfer function has the best performance. In addition, omitting the bias connection of the neurons improve the performance of the network. Also, the SCINFUL code is used for generating the response functions in the training phase of the process. Finally, the results of the neural network simulation have been compared with those of the FORIST unfolding code for both (241)Am-Be and (252)Cf neutron sources. The results of neural network are in good agreement with FORIST code.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Matched Filtering and Convolutional Neural Network.

PubMed

Chen, Shuo; Luo, Chenggao; Wang, Hongqiang; Deng, Bin; Cheng, Yongqiang; Zhuang, Zhaowen

2018-04-26

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. However, there are still two problems in three-dimensional (3D) TCAI. Firstly, the large-scale reference-signal matrix based on meshing the 3D imaging area creates a heavy computational burden, thus leading to unsatisfactory efficiency. Secondly, it is difficult to resolve the target under low signal-to-noise ratio (SNR). In this paper, we propose a 3D imaging method based on matched filtering (MF) and convolutional neural network (CNN), which can reduce the computational burden and achieve high-resolution imaging for low SNR targets. In terms of the frequency-hopping (FH) signal, the original echo is processed with MF. By extracting the processed echo in different spike pulses separately, targets in different imaging planes are reconstructed simultaneously to decompose the global computational complexity, and then are synthesized together to reconstruct the 3D target. Based on the conventional TCAI model, we deduce and build a new TCAI model based on MF. Furthermore, the convolutional neural network (CNN) is designed to teach the MF-TCAI how to reconstruct the low SNR target better. The experimental results demonstrate that the MF-TCAI achieves impressive performance on imaging ability and efficiency under low SNR. Moreover, the MF-TCAI has learned to better resolve the low-SNR 3D target with the help of CNN. In summary, the proposed 3D TCAI can achieve: (1) low-SNR high-resolution imaging by using MF; (2) efficient 3D imaging by downsizing the large-scale reference-signal matrix; and (3) intelligent imaging with CNN. Therefore, the TCAI based on MF and CNN has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

Implementing controlled-unitary operations over the butterfly network

NASA Astrophysics Data System (ADS)

Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.; Murao, Mio

2014-12-01

We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

Implementing controlled-unitary operations over the butterfly network

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

Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S.

2014-12-04

We introduce a multiparty quantum computation task over a network in a situation where the capacities of both the quantum and classical communication channels of the network are limited and a bottleneck occurs. Using a resource setting introduced by Hayashi [1], we present an efficient protocol for performing controlled-unitary operations between two input nodes and two output nodes over the butterfly network, one of the most fundamental networks exhibiting the bottleneck problem. This result opens the possibility of developing a theory of quantum network coding for multiparty quantum computation, whereas the conventional network coding only treats multiparty quantum communication.

Burst mode PCS of EPON

NASA Astrophysics Data System (ADS)

Du, Xiao

2005-02-01

Normal GIGA ETHERNET continuously transmits or receives 8B/10B codes including data codes, idle codes or configuration information. In ETHERNET network, one computer links one port of switch through CAT5 and that is OK. But for EPON, it is different. All ONUs share one fiber in upstream, if we inherit the GIGA ETHERNET PHY, then collision will occur. All ONUs always transmit 8B/10B codes, and the optical signal will overlay. The OLT will receive the fault information. So we need a novel EPON PHY instead of ETHERNET PHY. But its major function is compatible with ETHERNET"s. In this article, first, the function of PCS sub layer is discussed and a novel PCS module is given that can be used in not only EPON system but also in GIGA ETHERNET system. The design of PCS is based on 1000BASE-X PCS technology. And the function of 1000BASE-X PCS should be accomplished first. Next we modify the design in order to meet the requirements of EPON system. In the new design, the auto negotiation and synchronization is the same to the 1000 BASE-X technology.

Physical-Layer Network Coding for VPN in TDM-PON

NASA Astrophysics Data System (ADS)

Wang, Qike; Tse, Kam-Hon; Chen, Lian-Kuan; Liew, Soung-Chang

2012-12-01

We experimentally demonstrate a novel optical physical-layer network coding (PNC) scheme over time-division multiplexing (TDM) passive optical network (PON). Full-duplex error-free communications between optical network units (ONUs) at 2.5 Gb/s are shown for all-optical virtual private network (VPN) applications. Compared to the conventional half-duplex communications set-up, our scheme can increase the capacity by 100% with power penalty smaller than 3 dB. Synchronization of two ONUs is not required for the proposed VPN scheme

Optical protocols for terabit networks

NASA Technical Reports Server (NTRS)

Chua, P. L.; Lambert, J. L.; Morookian, J. M.; Bergman, L. A.

1991-01-01

This paper describes a new fiber-optic local area network technology providing 100X improvement over current technology, has full crossbar funtionality, and inherent data security. Based on optical code-division multiple access (CDMA), using spectral phase encoding/decoding of optical pulses, networking protocols are implemented entirely in the optical domain and thus conventional networking bottlenecks are avoided. Component and system issues for a proof-of-concept demonstration are discussed, as well as issues for a more practical and commercially exploitable system. Possible terrestrial and aerospace applications of this technology, and its impact on other technologies are explored. Some initial results toward realization of this concept are also included.

A computational geometry approach to pore network construction for granular packings

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Sufian, Adnan; Narsilio, Guillermo A.; Russell, Adrian R.; Tordesillas, Antoinette

2018-03-01

Pore network construction provides the ability to characterize and study the pore space of inhomogeneous and geometrically complex granular media in a range of scientific and engineering applications. Various approaches to the construction have been proposed, however subtle implementational details are frequently omitted, open access to source code is limited, and few studies compare multiple algorithms in the context of a specific application. This study presents, in detail, a new pore network construction algorithm, and provides a comprehensive comparison with two other, well-established Delaunay triangulation-based pore network construction methods. Source code is provided to encourage further development. The proposed algorithm avoids the expensive non-linear optimization procedure in existing Delaunay approaches, and is robust in the presence of polydispersity. Algorithms are compared in terms of structural, geometrical and advanced connectivity parameters, focusing on the application of fluid flow characteristics. Sensitivity of the various networks to permeability is assessed through network (Stokes) simulations and finite-element (Navier-Stokes) simulations. Results highlight strong dependencies of pore volume, pore connectivity, throat geometry and fluid conductance on the degree of tetrahedra merging and the specific characteristics of the throats targeted by the merging algorithm. The paper concludes with practical recommendations on the applicability of the three investigated algorithms.

Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network

PubMed Central

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. Summary We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding. PMID:29773979

Efficient Coding and Energy Efficiency Are Promoted by Balanced Excitatory and Inhibitory Synaptic Currents in Neuronal Network.

PubMed

Yu, Lianchun; Shen, Zhou; Wang, Chen; Yu, Yuguo

2018-01-01

Selective pressure may drive neural systems to process as much information as possible with the lowest energy cost. Recent experiment evidence revealed that the ratio between synaptic excitation and inhibition (E/I) in local cortex is generally maintained at a certain value which may influence the efficiency of energy consumption and information transmission of neural networks. To understand this issue deeply, we constructed a typical recurrent Hodgkin-Huxley network model and studied the general principles that governs the relationship among the E/I synaptic current ratio, the energy cost and total amount of information transmission. We observed in such a network that there exists an optimal E/I synaptic current ratio in the network by which the information transmission achieves the maximum with relatively low energy cost. The coding energy efficiency which is defined as the mutual information divided by the energy cost, achieved the maximum with the balanced synaptic current. Although background noise degrades information transmission and imposes an additional energy cost, we find an optimal noise intensity that yields the largest information transmission and energy efficiency at this optimal E/I synaptic transmission ratio. The maximization of energy efficiency also requires a certain part of energy cost associated with spontaneous spiking and synaptic activities. We further proved this finding with analytical solution based on the response function of bistable neurons, and demonstrated that optimal net synaptic currents are capable of maximizing both the mutual information and energy efficiency. These results revealed that the development of E/I synaptic current balance could lead a cortical network to operate at a highly efficient information transmission rate at a relatively low energy cost. The generality of neuronal models and the recurrent network configuration used here suggest that the existence of an optimal E/I cell ratio for highly efficient energy costs and information maximization is a potential principle for cortical circuit networks. We conducted numerical simulations and mathematical analysis to examine the energy efficiency of neural information transmission in a recurrent network as a function of the ratio of excitatory and inhibitory synaptic connections. We obtained a general solution showing that there exists an optimal E/I synaptic ratio in a recurrent network at which the information transmission as well as the energy efficiency of this network achieves a global maximum. These results reflect general mechanisms for sensory coding processes, which may give insight into the energy efficiency of neural communication and coding.

Integrating non-coding RNAs in JAK-STAT regulatory networks

PubMed Central

Witte, Steven; Muljo, Stefan A

2014-01-01

Being a well-characterized pathway, JAK-STAT signaling serves as a valuable paradigm for studying the architecture of gene regulatory networks. The discovery of untranslated or non-coding RNAs, namely microRNAs and long non-coding RNAs, provides an opportunity to elucidate their roles in such networks. In principle, these regulatory RNAs can act as downstream effectors of the JAK-STAT pathway and/or affect signaling by regulating the expression of JAK-STAT components. Examples of interactions between signaling pathways and non-coding RNAs have already emerged in basic cell biology and human diseases such as cancer, and can potentially guide the identification of novel biomarkers or drug targets for medicine. PMID:24778925

Implementation of Phased Array Antenna Technology Providing a Wireless Local Area Network to Enhance Port Security and Maritime Interdiction Operations

DTIC Science & Technology

2009-09-01

boarding team, COTS, WLAN, smart antenna, OpenVPN application, wireless base station, OFDM, latency, point-to-point wireless link. 16. PRICE CODE 17...16 c. SSL/TLS .................................17 2. OpenVPN ......................................17 III. EXPERIMENT METHODOLOGY...network frame at Layer 2 has already been secured by encryption at a higher level. 2. OpenVPN OpenVPN is open source software that provides a VPN

Anatomical and functional organization of the human substantia nigra and its connections

PubMed Central

Zhang, Yu; Larcher, Kevin Michel-Herve; Misic, Bratislav

2017-01-01

We investigated the anatomical and functional organization of the human substantia nigra (SN) using diffusion and functional MRI data from the Human Connectome Project. We identified a tripartite connectivity-based parcellation of SN with a limbic, cognitive, motor arrangement. The medial SN connects with limbic striatal and cortical regions and encodes value (greater response to monetary wins than losses during fMRI), while the ventral SN connects with associative regions of cortex and striatum and encodes salience (equal response to wins and losses). The lateral SN connects with somatomotor regions of striatum and cortex and also encodes salience. Behavioral measures from delay discounting and flanker tasks supported a role for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventral SN network was associated with motor impulsivity. In sum, there is anatomical and functional heterogeneity of human SN, which underpins value versus salience coding, and impulsive choice versus impulsive action. PMID:28826495

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2012-01-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Neural network-based brain tissue segmentation in MR images using extracted features from intraframe coding in H.264

NASA Astrophysics Data System (ADS)

Jafari, Mehdi; Kasaei, Shohreh

2011-12-01

Automatic brain tissue segmentation is a crucial task in diagnosis and treatment of medical images. This paper presents a new algorithm to segment different brain tissues, such as white matter (WM), gray matter (GM), cerebral spinal fluid (CSF), background (BKG), and tumor tissues. The proposed technique uses the modified intraframe coding yielded from H.264/(AVC), for feature extraction. Extracted features are then imposed to an artificial back propagation neural network (BPN) classifier to assign each block to its appropriate class. Since the newest coding standard, H.264/AVC, has the highest compression ratio, it decreases the dimension of extracted features and thus yields to a more accurate classifier with low computational complexity. The performance of the BPN classifier is evaluated using the classification accuracy and computational complexity terms. The results show that the proposed technique is more robust and effective with low computational complexity compared to other recent works.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Short-Block Protograph-Based LDPC Codes

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Samuel; Jones, Christopher

2010-01-01

Short-block low-density parity-check (LDPC) codes of a special type are intended to be especially well suited for potential applications that include transmission of command and control data, cellular telephony, data communications in wireless local area networks, and satellite data communications. [In general, LDPC codes belong to a class of error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels.] The codes of the present special type exhibit low error floors, low bit and frame error rates, and low latency (in comparison with related prior codes). These codes also achieve low maximum rate of undetected errors over all signal-to-noise ratios, without requiring the use of cyclic redundancy checks, which would significantly increase the overhead for short blocks. These codes have protograph representations; this is advantageous in that, for reasons that exceed the scope of this article, the applicability of protograph representations makes it possible to design highspeed iterative decoders that utilize belief- propagation algorithms.

Calculations of dose distributions using a neural network model

NASA Astrophysics Data System (ADS)

Mathieu, R.; Martin, E.; Gschwind, R.; Makovicka, L.; Contassot-Vivier, S.; Bahi, J.

2005-03-01

The main goal of external beam radiotherapy is the treatment of tumours, while sparing, as much as possible, surrounding healthy tissues. In order to master and optimize the dose distribution within the patient, dosimetric planning has to be carried out. Thus, for determining the most accurate dose distribution during treatment planning, a compromise must be found between the precision and the speed of calculation. Current techniques, using analytic methods, models and databases, are rapid but lack precision. Enhanced precision can be achieved by using calculation codes based, for example, on Monte Carlo methods. However, in spite of all efforts to optimize speed (methods and computer improvements), Monte Carlo based methods remain painfully slow. A newer way to handle all of these problems is to use a new approach in dosimetric calculation by employing neural networks. Neural networks (Wu and Zhu 2000 Phys. Med. Biol. 45 913-22) provide the advantages of those various approaches while avoiding their main inconveniences, i.e., time-consumption calculations. This permits us to obtain quick and accurate results during clinical treatment planning. Currently, results obtained for a single depth-dose calculation using a Monte Carlo based code (such as BEAM (Rogers et al 2003 NRCC Report PIRS-0509(A) rev G)) require hours of computing. By contrast, the practical use of neural networks (Mathieu et al 2003 Proceedings Journées Scientifiques Francophones, SFRP) provides almost instant results and quite low errors (less than 2%) for a two-dimensional dosimetric map.

Calculations of dose distributions using a neural network model.

PubMed

Mathieu, R; Martin, E; Gschwind, R; Makovicka, L; Contassot-Vivier, S; Bahi, J

2005-03-07

The main goal of external beam radiotherapy is the treatment of tumours, while sparing, as much as possible, surrounding healthy tissues. In order to master and optimize the dose distribution within the patient, dosimetric planning has to be carried out. Thus, for determining the most accurate dose distribution during treatment planning, a compromise must be found between the precision and the speed of calculation. Current techniques, using analytic methods, models and databases, are rapid but lack precision. Enhanced precision can be achieved by using calculation codes based, for example, on Monte Carlo methods. However, in spite of all efforts to optimize speed (methods and computer improvements), Monte Carlo based methods remain painfully slow. A newer way to handle all of these problems is to use a new approach in dosimetric calculation by employing neural networks. Neural networks (Wu and Zhu 2000 Phys. Med. Biol. 45 913-22) provide the advantages of those various approaches while avoiding their main inconveniences, i.e., time-consumption calculations. This permits us to obtain quick and accurate results during clinical treatment planning. Currently, results obtained for a single depth-dose calculation using a Monte Carlo based code (such as BEAM (Rogers et al 2003 NRCC Report PIRS-0509(A) rev G)) require hours of computing. By contrast, the practical use of neural networks (Mathieu et al 2003 Proceedings Journees Scientifiques Francophones, SFRP) provides almost instant results and quite low errors (less than 2%) for a two-dimensional dosimetric map.

Alignment-free protein interaction network comparison

PubMed Central

Ali, Waqar; Rito, Tiago; Reinert, Gesine; Sun, Fengzhu; Deane, Charlotte M.

2014-01-01

Motivation: Biological network comparison software largely relies on the concept of alignment where close matches between the nodes of two or more networks are sought. These node matches are based on sequence similarity and/or interaction patterns. However, because of the incomplete and error-prone datasets currently available, such methods have had limited success. Moreover, the results of network alignment are in general not amenable for distance-based evolutionary analysis of sets of networks. In this article, we describe Netdis, a topology-based distance measure between networks, which offers the possibility of network phylogeny reconstruction. Results: We first demonstrate that Netdis is able to correctly separate different random graph model types independent of network size and density. The biological applicability of the method is then shown by its ability to build the correct phylogenetic tree of species based solely on the topology of current protein interaction networks. Our results provide new evidence that the topology of protein interaction networks contains information about evolutionary processes, despite the lack of conservation of individual interactions. As Netdis is applicable to all networks because of its speed and simplicity, we apply it to a large collection of biological and non-biological networks where it clusters diverse networks by type. Availability and implementation: The source code of the program is freely available at http://www.stats.ox.ac.uk/research/proteins/resources. Contact: w.ali@stats.ox.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25161230

MILCOM '85 - Military Communications Conference, Boston, MA, October 20-23, 1985, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

The present conference on the development status of communications systems in the context of electronic warfare gives attention to topics in spread spectrum code acquisition, digital speech technology, fiber-optics communications, free space optical communications, the networking of HF systems, and applications and evaluation methods for digital speech. Also treated are issues in local area network system design, coding techniques and applications, technology applications for HF systems, receiver technologies, software development status, channel simultion/prediction methods, C3 networking spread spectrum networks, the improvement of communication efficiency and reliability through technical control methods, mobile radio systems, and adaptive antenna arrays. Finally, communications system cost analyses, spread spectrum performance, voice and image coding, switched networks, and microwave GaAs ICs, are considered.

Towards Breaking the Histone Code – Bayesian Graphical Models for Histone Modifications

PubMed Central

Mitra, Riten; Müller, Peter; Liang, Shoudan; Xu, Yanxun; Ji, Yuan

2013-01-01

Background Histones are proteins that wrap DNA around in small spherical structures called nucleosomes. Histone modifications (HMs) refer to the post-translational modifications to the histone tails. At a particular genomic locus, each of these HMs can either be present or absent, and the combinatory patterns of the presence or absence of multiple HMs, or the ‘histone codes,’ are believed to co-regulate important biological processes. We aim to use raw data on HM markers at different genomic loci to (1) decode the complex biological network of HMs in a single region and (2) demonstrate how the HM networks differ in different regulatory regions. We suggest that these differences in network attributes form a significant link between histones and genomic functions. Methods and Results We develop a powerful graphical model under Bayesian paradigm. Posterior inference is fully probabilistic, allowing us to compute the probabilities of distinct dependence patterns of the HMs using graphs. Furthermore, our model-based framework allows for easy but important extensions for inference on differential networks under various conditions, such as the different annotations of the genomic locations (e.g., promoters versus insulators). We applied these models to ChIP-Seq data based on CD4+ T lymphocytes. The results confirmed many existing findings and provided a unified tool to generate various promising hypotheses. Differential network analyses revealed new insights on co-regulation of HMs of transcriptional activities in different genomic regions. Conclusions The use of Bayesian graphical models and borrowing strength across different conditions provide high power to infer histone networks and their differences. PMID:23748248

Systems for the Intermodal Routing of Spent Nuclear Fuel

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

Peterson, Steven K; Liu, Cheng

The safe and secure movement of spent nuclear fuel from shutdown and active reactor facilities to intermediate or long term storage sites may, in some instances, require the use of several modes of transportation to accomplish the move. To that end, a fully operable multi-modal routing system is being developed within Oak Ridge National Laboratory s (ORNL) WebTRAGIS (Transportation Routing Analysis Geographic Information System). This study aims to provide an overview of multi-modal routing, the existing state of the TRAGIS networks, the source data needs, and the requirements for developing structural relationships between various modes to create a suitable systemmore » for modeling the transport of spent nuclear fuel via a multimodal network. Modern transportation systems are comprised of interconnected, yet separate, modal networks. Efficient transportation networks rely upon the smooth transfer of cargoes at junction points that serve as connectors between modes. A key logistical impediment to the shipment of spent nuclear fuel is the absence of identified or designated transfer locations between transport modes. Understanding the potential network impacts on intermodal transportation of spent nuclear fuel is vital for planning transportation routes from origin to destination. By identifying key locations where modes intersect, routing decisions can be made to prioritize cost savings, optimize transport times and minimize potential risks to the population and environment. In order to facilitate such a process, ORNL began the development of a base intermodal network and associated routing code. The network was developed using previous intermodal networks and information from publicly available data sources to construct a database of potential intermodal transfer locations with likely capability to handle spent nuclear fuel casks. The coding development focused on modifying the existing WebTRAGIS routing code to accommodate intermodal transfers and the selection of prioritization constraints and modifiers to determine route selection. The limitations of the current model and future directions for development are discussed, including the current state of information on possible intermodal transfer locations for spent fuel.« less

Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †

PubMed Central

Murdani, Muhammad Harist; Hong, Bonghee

2018-01-01

In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes (Ad-Hoc) and neighborhood proximity (Top-K). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space. PMID:29587366

Efficient Proximity Computation Techniques Using ZIP Code Data for Smart Cities †.

PubMed

Murdani, Muhammad Harist; Kwon, Joonho; Choi, Yoon-Ho; Hong, Bonghee

2018-03-24

In this paper, we are interested in computing ZIP code proximity from two perspectives, proximity between two ZIP codes ( Ad-Hoc ) and neighborhood proximity ( Top-K ). Such a computation can be used for ZIP code-based target marketing as one of the smart city applications. A naïve approach to this computation is the usage of the distance between ZIP codes. We redefine a distance metric combining the centroid distance with the intersecting road network between ZIP codes by using a weighted sum method. Furthermore, we prove that the results of our combined approach conform to the characteristics of distance measurement. We have proposed a general and heuristic approach for computing Ad-Hoc proximity, while for computing Top-K proximity, we have proposed a general approach only. Our experimental results indicate that our approaches are verifiable and effective in reducing the execution time and search space.

Inter-synaptic learning of combination rules in a cortical network model

PubMed Central

Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

2014-01-01

Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

Exact and heuristic algorithms for Space Information Flow.

PubMed

Uwitonze, Alfred; Huang, Jiaqing; Ye, Yuanqing; Cheng, Wenqing; Li, Zongpeng

2018-01-01

Space Information Flow (SIF) is a new promising research area that studies network coding in geometric space, such as Euclidean space. The design of algorithms that compute the optimal SIF solutions remains one of the key open problems in SIF. This work proposes the first exact SIF algorithm and a heuristic SIF algorithm that compute min-cost multicast network coding for N (N ≥ 3) given terminal nodes in 2-D Euclidean space. Furthermore, we find that the Butterfly network in Euclidean space is the second example besides the Pentagram network where SIF is strictly better than Euclidean Steiner minimal tree. The exact algorithm design is based on two key techniques: Delaunay triangulation and linear programming. Delaunay triangulation technique helps to find practically good candidate relay nodes, after which a min-cost multicast linear programming model is solved over the terminal nodes and the candidate relay nodes, to compute the optimal multicast network topology, including the optimal relay nodes selected by linear programming from all the candidate relay nodes and the flow rates on the connection links. The heuristic algorithm design is also based on Delaunay triangulation and linear programming techniques. The exact algorithm can achieve the optimal SIF solution with an exponential computational complexity, while the heuristic algorithm can achieve the sub-optimal SIF solution with a polynomial computational complexity. We prove the correctness of the exact SIF algorithm. The simulation results show the effectiveness of the heuristic SIF algorithm.

Zero-forcing pre-coding for MIMO WiMAX transceivers: Performance analysis and implementation issues

NASA Astrophysics Data System (ADS)

Cattoni, A. F.; Le Moullec, Y.; Sacchi, C.

Next generation wireless communication networks are expected to achieve ever increasing data rates. Multi-User Multiple-Input-Multiple-Output (MU-MIMO) is a key technique to obtain the expected performance, because such a technique combines the high capacity achievable using MIMO channel with the benefits of space division multiple access. In MU-MIMO systems, the base stations transmit signals to two or more users over the same channel, for this reason every user can experience inter-user interference. This paper provides a capacity analysis of an online, interference-based pre-coding algorithm able to mitigate the multi-user interference of the MU-MIMO systems in the context of a realistic WiMAX application scenario. Simulation results show that pre-coding can significantly increase the channel capacity. Furthermore, the paper presents several feasibility considerations for implementation of the analyzed technique in a possible FPGA-based software defined radio.

Ricebase - a resource for rice breeding

USDA-ARS?s Scientific Manuscript database

Ricebase combines accessions, traits, markers, and genes with genome-scale datasets to empower rice breeders and geneticists to explore big-data resources. The underlying code and schema are shared with CassavaBase and the Sol Genomics Network (SGN) databases. Ricebase was launched specifically to m...

Neural Decoder for Topological Codes

NASA Astrophysics Data System (ADS)

Torlai, Giacomo; Melko, Roger G.

2017-07-01

We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.

Linear-time general decoding algorithm for the surface code

NASA Astrophysics Data System (ADS)

Darmawan, Andrew S.; Poulin, David

2018-05-01

A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.

Superdense Coding over Optical Fiber Links with Complete Bell-State Measurements

NASA Astrophysics Data System (ADS)

Williams, Brian P.; Sadlier, Ronald J.; Humble, Travis S.

2017-02-01

Adopting quantum communication to modern networking requires transmitting quantum information through a fiber-based infrastructure. We report the first demonstration of superdense coding over optical fiber links, taking advantage of a complete Bell-state measurement enabled by time-polarization hyperentanglement, linear optics, and common single-photon detectors. We demonstrate the highest single-qubit channel capacity to date utilizing linear optics, 1.665 ±0.018 , and we provide a full experimental implementation of a hybrid, quantum-classical communication protocol for image transfer.

Invocation oriented architecture for agile code and agile data

NASA Astrophysics Data System (ADS)

Verma, Dinesh; Chan, Kevin; Leung, Kin; Gkelias, Athanasios

2017-05-01

In order to address the unique requirements of sensor information fusion in a tactical coalition environment, we are proposing a new architecture - one based on the concept of invocations. An invocation is a combination of a software code and a piece of data, both managed using techniques from Information Centric networking. This paper will discuss limitations of current approaches, present the architecture for an invocation oriented architecture, illustrate how it works with an example scenario, and provide reasons for its suitability in a coalition environment.

Design and Implementation of Secure and Reliable Communication using Optical Wireless Communication

NASA Astrophysics Data System (ADS)

Saadi, Muhammad; Bajpai, Ambar; Zhao, Yan; Sangwongngam, Paramin; Wuttisittikulkij, Lunchakorn

2014-11-01

Wireless networking intensify the tractability in the home and office environment to connect the internet without wires but at the cost of risks associated with stealing the data or threat of loading malicious code with the intention of harming the network. In this paper, we proposed a novel method of establishing a secure and reliable communication link using optical wireless communication (OWC). For security, spatial diversity based transmission using two optical transmitters is used and the reliability in the link is achieved by a newly proposed method for the construction of structured parity check matrix for binary Low Density Parity Check (LDPC) codes. Experimental results show that a successful secure and reliable link between the transmitter and the receiver can be achieved by using the proposed novel technique.

High efficiency video coding for ultrasound video communication in m-health systems.

PubMed

Panayides, A; Antoniou, Z; Pattichis, M S; Pattichis, C S; Constantinides, A G

2012-01-01

Emerging high efficiency video compression methods and wider availability of wireless network infrastructure will significantly advance existing m-health applications. For medical video communications, the emerging video compression and network standards support low-delay and high-resolution video transmission, at the clinically acquired resolution and frame rates. Such advances are expected to further promote the adoption of m-health systems for remote diagnosis and emergency incidents in daily clinical practice. This paper compares the performance of the emerging high efficiency video coding (HEVC) standard to the current state-of-the-art H.264/AVC standard. The experimental evaluation, based on five atherosclerotic plaque ultrasound videos encoded at QCIF, CIF, and 4CIF resolutions demonstrates that 50% reductions in bitrate requirements is possible for equivalent clinical quality.

PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems

PubMed Central

Stefanini, Fabio; Neftci, Emre O.; Sheik, Sadique; Indiveri, Giacomo

2014-01-01

Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS. PMID:25232314

PyNCS: a microkernel for high-level definition and configuration of neuromorphic electronic systems.

PubMed

Stefanini, Fabio; Neftci, Emre O; Sheik, Sadique; Indiveri, Giacomo

2014-01-01

Neuromorphic hardware offers an electronic substrate for the realization of asynchronous event-based sensory-motor systems and large-scale spiking neural network architectures. In order to characterize these systems, configure them, and carry out modeling experiments, it is often necessary to interface them to workstations. The software used for this purpose typically consists of a large monolithic block of code which is highly specific to the hardware setup used. While this approach can lead to highly integrated hardware/software systems, it hampers the development of modular and reconfigurable infrastructures thus preventing a rapid evolution of such systems. To alleviate this problem, we propose PyNCS, an open-source front-end for the definition of neural network models that is interfaced to the hardware through a set of Python Application Programming Interfaces (APIs). The design of PyNCS promotes modularity, portability and expandability and separates implementation from hardware description. The high-level front-end that comes with PyNCS includes tools to define neural network models as well as to create, monitor and analyze spiking data. Here we report the design philosophy behind the PyNCS framework and describe its implementation. We demonstrate its functionality with two representative case studies, one using an event-based neuromorphic vision sensor, and one using a set of multi-neuron devices for carrying out a cognitive decision-making task involving state-dependent computation. PyNCS, already applicable to a wide range of existing spike-based neuromorphic setups, will accelerate the development of hybrid software/hardware neuromorphic systems, thanks to its code flexibility. The code is open-source and available online at https://github.com/inincs/pyNCS.

Understanding network concepts in modules

PubMed Central

2007-01-01

Background Network concepts are increasingly used in biology and genetics. For example, the clustering coefficient has been used to understand network architecture; the connectivity (also known as degree) has been used to screen for cancer targets; and the topological overlap matrix has been used to define modules and to annotate genes. Dozens of potentially useful network concepts are known from graph theory. Results Here we study network concepts in special types of networks, which we refer to as approximately factorizable networks. In these networks, the pairwise connection strength (adjacency) between 2 network nodes can be factored into node specific contributions, named node 'conformity'. The node conformity turns out to be highly related to the connectivity. To provide a formalism for relating network concepts to each other, we define three types of network concepts: fundamental-, conformity-based-, and approximate conformity-based concepts. Fundamental concepts include the standard definitions of connectivity, density, centralization, heterogeneity, clustering coefficient, and topological overlap. The approximate conformity-based analogs of fundamental network concepts have several theoretical advantages. First, they allow one to derive simple relationships between seemingly disparate networks concepts. For example, we derive simple relationships between the clustering coefficient, the heterogeneity, the density, the centralization, and the topological overlap. The second advantage of approximate conformity-based network concepts is that they allow one to show that fundamental network concepts can be approximated by simple functions of the connectivity in module networks. Conclusion Using protein-protein interaction, gene co-expression, and simulated data, we show that a) many networks comprised of module nodes are approximately factorizable and b) in these types of networks, simple relationships exist between seemingly disparate network concepts. Our results are implemented in freely available R software code, which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/ModuleConformity/ModuleNetworks PMID:17547772

Combating QR-Code-Based Compromised Accounts in Mobile Social Networks.

PubMed

Guo, Dong; Cao, Jian; Wang, Xiaoqi; Fu, Qiang; Li, Qiang

2016-09-20

Cyber Physical Social Sensing makes mobile social networks (MSNs) popular with users. However, such attacks are rampant as malicious URLs are spread covertly through quick response (QR) codes to control compromised accounts in MSNs to propagate malicious messages. Currently, there are generally two types of methods to identify compromised accounts in MSNs: one type is to analyze the potential threats on wireless access points and the potential threats on handheld devices' operation systems so as to stop compromised accounts from spreading malicious messages; the other type is to apply the method of detecting compromised accounts in online social networks to MSNs. The above types of methods above focus neither on the problems of MSNs themselves nor on the interaction of sensors' messages, which leads to the restrictiveness of platforms and the simplification of methods. In order to stop the spreading of compromised accounts in MSNs effectively, the attacks have to be traced to their sources first. Through sensors, users exchange information in MSNs and acquire information by scanning QR codes. Therefore, analyzing the traces of sensor-related information helps to identify the compromised accounts in MSNs. This paper analyzes the diversity of information sending modes of compromised accounts and normal accounts, analyzes the regularity of GPS (Global Positioning System)-based location information, and introduces the concepts of entropy and conditional entropy so as to construct an entropy-based model based on machine learning strategies. To achieve the goal, about 500,000 accounts of Sina Weibo and about 100 million corresponding messages are collected. Through the validation, the accuracy rate of the model is proved to be as high as 87.6%, and the false positive rate is only 3.7%. Meanwhile, the comparative experiments of the feature sets prove that sensor-based location information can be applied to detect the compromised accounts in MSNs.

Combating QR-Code-Based Compromised Accounts in Mobile Social Networks

PubMed Central

Guo, Dong; Cao, Jian; Wang, Xiaoqi; Fu, Qiang; Li, Qiang

2016-01-01

Cyber Physical Social Sensing makes mobile social networks (MSNs) popular with users. However, such attacks are rampant as malicious URLs are spread covertly through quick response (QR) codes to control compromised accounts in MSNs to propagate malicious messages. Currently, there are generally two types of methods to identify compromised accounts in MSNs: one type is to analyze the potential threats on wireless access points and the potential threats on handheld devices’ operation systems so as to stop compromised accounts from spreading malicious messages; the other type is to apply the method of detecting compromised accounts in online social networks to MSNs. The above types of methods above focus neither on the problems of MSNs themselves nor on the interaction of sensors’ messages, which leads to the restrictiveness of platforms and the simplification of methods. In order to stop the spreading of compromised accounts in MSNs effectively, the attacks have to be traced to their sources first. Through sensors, users exchange information in MSNs and acquire information by scanning QR codes. Therefore, analyzing the traces of sensor-related information helps to identify the compromised accounts in MSNs. This paper analyzes the diversity of information sending modes of compromised accounts and normal accounts, analyzes the regularity of GPS (Global Positioning System)-based location information, and introduces the concepts of entropy and conditional entropy so as to construct an entropy-based model based on machine learning strategies. To achieve the goal, about 500,000 accounts of Sina Weibo and about 100 million corresponding messages are collected. Through the validation, the accuracy rate of the model is proved to be as high as 87.6%, and the false positive rate is only 3.7%. Meanwhile, the comparative experiments of the feature sets prove that sensor-based location information can be applied to detect the compromised accounts in MSNs. PMID:27657071

Autosophy information theory provides lossless data and video compression based on the data content

NASA Astrophysics Data System (ADS)

Holtz, Klaus E.; Holtz, Eric S.; Holtz, Diana

1996-09-01

A new autosophy information theory provides an alternative to the classical Shannon information theory. Using the new theory in communication networks provides both a high degree of lossless compression and virtually unbreakable encryption codes for network security. The bandwidth in a conventional Shannon communication is determined only by the data volume and the hardware parameters, such as image size; resolution; or frame rates in television. The data content, or what is shown on the screen, is irrelevant. In contrast, the bandwidth in autosophy communication is determined only by data content, such as novelty and movement in television images. It is the data volume and hardware parameters that become irrelevant. Basically, the new communication methods use prior 'knowledge' of the data, stored in a library, to encode subsequent transmissions. The more 'knowledge' stored in the libraries, the higher the potential compression ratio. 'Information' is redefined as that which is not already known by the receiver. Everything already known is redundant and need not be re-transmitted. In a perfect communication each transmission code, called a 'tip,' creates a new 'engram' of knowledge in the library in which each tip transmission can represent any amount of data. Autosophy theories provide six separate learning modes, or omni dimensional networks, all of which can be used for data compression. The new information theory reveals the theoretical flaws of other data compression methods, including: the Huffman; Ziv Lempel; LZW codes and commercial compression codes such as V.42bis and MPEG-2.

Sophia Daemon Version 12

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

2012-08-09

Sophia Daemon Version 12 contains the code that is exclusively used by the ‘sophiad’ application. It runs as a service on a Linux host and analyzes network traffic obtained from libpcap and produces a network fingerprint based on hosts and channels. Sophia Daemon Version 12 can, if desired by the user, produce alerts when its fingerprint changes. Sophia Daemon Version 12 can receive data from another Sophia Daemon or raw packet data. It can output data to another Sophia Daemon Version 12, OglNet Version 12 or MySQL. Sophia Daemon Version 12 runs in a passive real-time manner that allows itmore » to be used on a SCADA network. Its network fingerprint is designed to be applicable to SCADA networks rather than general IT networks.« less

Physical-layer network coding for passive optical interconnect in datacenter networks.

PubMed

Lin, Rui; Cheng, Yuxin; Guan, Xun; Tang, Ming; Liu, Deming; Chan, Chun-Kit; Chen, Jiajia

2017-07-24

We introduce physical-layer network coding (PLNC) technique in a passive optical interconnect (POI) architecture for datacenter networks. The implementation of the PLNC in the POI at 2.5 Gb/s and 10Gb/s have been experimentally validated while the gains in terms of network layer performances have been investigated by simulation. The results reveal that in order to realize negligible packet drop, the wavelengths usage can be reduced by half while a significant improvement in packet delay especially under high traffic load can be achieved by employing PLNC over POI.

High-speed all-optical DNA local sequence alignment based on a three-dimensional artificial neural network.

PubMed

Maleki, Ehsan; Babashah, Hossein; Koohi, Somayyeh; Kavehvash, Zahra

2017-07-01

This paper presents an optical processing approach for exploring a large number of genome sequences. Specifically, we propose an optical correlator for global alignment and an extended moiré matching technique for local analysis of spatially coded DNA, whose output is fed to a novel three-dimensional artificial neural network for local DNA alignment. All-optical implementation of the proposed 3D artificial neural network is developed and its accuracy is verified in Zemax. Thanks to its parallel processing capability, the proposed structure performs local alignment of 4 million sequences of 150 base pairs in a few seconds, which is much faster than its electrical counterparts, such as the basic local alignment search tool.

Statistical parsimony networks and species assemblages in Cephalotrichid nemerteans (nemertea).

PubMed

Chen, Haixia; Strand, Malin; Norenburg, Jon L; Sun, Shichun; Kajihara, Hiroshi; Chernyshev, Alexey V; Maslakova, Svetlana A; Sundberg, Per

2010-09-21

It has been suggested that statistical parsimony network analysis could be used to get an indication of species represented in a set of nucleotide data, and the approach has been used to discuss species boundaries in some taxa. Based on 635 base pairs of the mitochondrial protein-coding gene cytochrome c oxidase I (COI), we analyzed 152 nemertean specimens using statistical parsimony network analysis with the connection probability set to 95%. The analysis revealed 15 distinct networks together with seven singletons. Statistical parsimony yielded three networks supporting the species status of Cephalothrix rufifrons, C. major and C. spiralis as they currently have been delineated by morphological characters and geographical location. Many other networks contained haplotypes from nearby geographical locations. Cladistic structure by maximum likelihood analysis overall supported the network analysis, but indicated a false positive result where subnetworks should have been connected into one network/species. This probably is caused by undersampling of the intraspecific haplotype diversity. Statistical parsimony network analysis provides a rapid and useful tool for detecting possible undescribed/cryptic species among cephalotrichid nemerteans based on COI gene. It should be combined with phylogenetic analysis to get indications of false positive results, i.e., subnetworks that would have been connected with more extensive haplotype sampling.

Research on performance of three-layer MG-OXC system based on MLAG and OCDM

NASA Astrophysics Data System (ADS)

Wang, Yubao; Ren, Yanfei; Meng, Ying; Bai, Jian

2017-10-01

At present, as traffic volume which optical transport networks convey and species of traffic grooming methods increase rapidly, optical switching techniques are faced with a series of issues, such as more requests for the number of wavelengths and complicated structure management and implementation. This work introduces optical code switching based on wavelength switching, constructs the three layers multi-granularity optical cross connection (MG-OXC) system on the basis of optical code division multiplexing (OCDM) and presents a new traffic grooming algorithm. The proposed architecture can improve the flexibility of traffic grooming, reduce the amount of used wavelengths and save the number of consumed ports, hence, it can simplify routing device and enhance the performance of the system significantly. Through analyzing the network model of switching structure on multicast layered auxiliary graph (MLAG) and the establishment of traffic grooming links, and the simulation of blocking probability and throughput, this paper shows the excellent performance of this mentioned architecture.

Optical multiple access techniques for on-board routing

NASA Technical Reports Server (NTRS)

Mendez, Antonio J.; Park, Eugene; Gagliardi, Robert M.

1992-01-01

The purpose of this research contract was to design and analyze an optical multiple access system, based on Code Division Multiple Access (CDMA) techniques, for on board routing applications on a future communication satellite. The optical multiple access system was to effect the functions of a circuit switch under the control of an autonomous network controller and to serve eight (8) concurrent users at a point to point (port to port) data rate of 180 Mb/s. (At the start of this program, the bit error rate requirement (BER) was undefined, so it was treated as a design variable during the contract effort.) CDMA was selected over other multiple access techniques because it lends itself to bursty, asynchronous, concurrent communication and potentially can be implemented with off the shelf, reliable optical transceivers compatible with long term unattended operations. Temporal, temporal/spatial hybrids and single pulse per row (SPR, sometimes termed 'sonar matrices') matrix types of CDMA designs were considered. The design, analysis, and trade offs required by the statement of work selected a temporal/spatial CDMA scheme which has SPR properties as the preferred solution. This selected design can be implemented for feasibility demonstration with off the shelf components (which are identified in the bill of materials of the contract Final Report). The photonic network architecture of the selected design is based on M(8,4,4) matrix codes. The network requires eight multimode laser transmitters with laser pulses of 0.93 ns operating at 180 Mb/s and 9-13 dBm peak power, and 8 PIN diode receivers with sensitivity of -27 dBm for the 0.93 ns pulses. The wavelength is not critical, but 830 nm technology readily meets the requirements. The passive optical components of the photonic network are all multimode and off the shelf. Bit error rate (BER) computations, based on both electronic noise and intercode crosstalk, predict a raw BER of (10 exp -3) when all eight users are communicating concurrently. If better BER performance is required, then error correction codes (ECC) using near term electronic technology can be used. For example, the M(8,4,4) optical code together with Reed-Solomon (54,38,8) encoding provides a BER of better than (10 exp -11). The optical transceiver must then operate at 256 Mb/s with pulses of 0.65 ns because the 'bits' are now channel symbols.

Predictive and Neural Predictive Control of Uncertain Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

Overview of codes and tools for nuclear engineering education

NASA Astrophysics Data System (ADS)

Yakovlev, D.; Pryakhin, A.; Medvedeva, L.

2017-01-01

The recent world trends in nuclear education have been developed in the direction of social education, networking, virtual tools and codes. MEPhI as a global leader on the world education market implements new advanced technologies for the distance and online learning and for student research work. MEPhI produced special codes, tools and web resources based on the internet platform to support education in the field of nuclear technology. At the same time, MEPhI actively uses codes and tools from the third parties. Several types of the tools are considered: calculation codes, nuclear data visualization tools, virtual labs, PC-based educational simulators for nuclear power plants (NPP), CLP4NET, education web-platforms, distance courses (MOOCs and controlled and managed content systems). The university pays special attention to integrated products such as CLP4NET, which is not a learning course, but serves to automate the process of learning through distance technologies. CLP4NET organizes all tools in the same information space. Up to now, MEPhI has achieved significant results in the field of distance education and online system implementation.

Communication devices for network-hopping communications and methods of network-hopping communications

DOEpatents

Buttles, John W [Idaho Falls, ID

2011-12-20

Wireless communication devices include a software-defined radio coupled to processing circuitry. The processing circuitry is configured to execute computer programming code. Storage media is coupled to the processing circuitry and includes computer programming code configured to cause the processing circuitry to configure and reconfigure the software-defined radio to operate on each of a plurality of communication networks according to a selected sequence. Methods for communicating with a wireless device and methods of wireless network-hopping are also disclosed.

Communication devices for network-hopping communications and methods of network-hopping communications

DOEpatents

Buttles, John W

2013-04-23

Wireless communication devices include a software-defined radio coupled to processing circuitry. The system controller is configured to execute computer programming code. Storage media is coupled to the system controller and includes computer programming code configured to cause the system controller to configure and reconfigure the software-defined radio to operate on each of a plurality of communication networks according to a selected sequence. Methods for communicating with a wireless device and methods of wireless network-hopping are also disclosed.

SEQUOIA: significance enhanced network querying through context-sensitive random walk and minimization of network conductance.

PubMed

Jeong, Hyundoo; Yoon, Byung-Jun

2017-03-14

Network querying algorithms provide computational means to identify conserved network modules in large-scale biological networks that are similar to known functional modules, such as pathways or molecular complexes. Two main challenges for network querying algorithms are the high computational complexity of detecting potential isomorphism between the query and the target graphs and ensuring the biological significance of the query results. In this paper, we propose SEQUOIA, a novel network querying algorithm that effectively addresses these issues by utilizing a context-sensitive random walk (CSRW) model for network comparison and minimizing the network conductance of potential matches in the target network. The CSRW model, inspired by the pair hidden Markov model (pair-HMM) that has been widely used for sequence comparison and alignment, can accurately assess the node-to-node correspondence between different graphs by accounting for node insertions and deletions. The proposed algorithm identifies high-scoring network regions based on the CSRW scores, which are subsequently extended by maximally reducing the network conductance of the identified subnetworks. Performance assessment based on real PPI networks and known molecular complexes show that SEQUOIA outperforms existing methods and clearly enhances the biological significance of the query results. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/SEQUOIA .

System for loading executable code into volatile memory in a downhole tool

DOEpatents

Hall, David R.; Bartholomew, David B.; Johnson, Monte L.

2007-09-25

A system for loading an executable code into volatile memory in a downhole tool string component comprises a surface control unit comprising executable code. An integrated downhole network comprises data transmission elements in communication with the surface control unit and the volatile memory. The executable code, stored in the surface control unit, is not permanently stored in the downhole tool string component. In a preferred embodiment of the present invention, the downhole tool string component comprises boot memory. In another embodiment, the executable code is an operating system executable code. Preferably, the volatile memory comprises random access memory (RAM). A method for loading executable code to volatile memory in a downhole tool string component comprises sending the code from the surface control unit to a processor in the downhole tool string component over the network. A central processing unit writes the executable code in the volatile memory.

Monitor Network Traffic with Packet Capture (pcap) on an Android Device

DTIC Science & Technology

2015-09-01

administrative privileges . Under the current design Android development requirement, an Android Graphical User Interface (GUI) application cannot directly...build an Android application to monitor network traffic using open source packet capture (pcap) libraries. 15. SUBJECT TERMS ELIDe, Android , pcap 16...Building Application with Native Codes 5 8.1 Calling Native Codes Using JNI 5 8.2 Calling Native Codes from an Android Application 8 9. Retrieve Live

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks

PubMed Central

Guo, Kehua; Zhang, Ping; Ma, Jianhua

2016-01-01

Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

"Looking out for each other": a qualitative study on the role of social network interactions in asthma management among adult Latino patients presenting to an emergency department.

PubMed

Pai, Sucheta; Boutin-Foster, Carla; Mancuso, Carol A; Loganathan, Raghu; Basir, Riyad; Kanna, Balavenkatesh

2014-09-01

The objective of this study was to identify the types of interactions between asthma patients and their social networks such as close family and friends that influence the management of asthma. Participants were Latino adults presenting for a repeat visit to the emergency department for asthma treatment. Qualitative interviews were conducted with 76 participants. They were asked to describe the experiences of their social networks that have asthma and how interactions with these individuals influenced their own asthma management. Responses were transcribed and analyzed using Grounded Theory as a qualitative analytic approach. Responses were assigned codes; similar codes were grouped into concepts and then categorized to form overarching themes. Four themes emerged: (1) Perceptions of severity of asthma may be based on the experiences of social networks; (2) Economic factors may contribute to the sharing and borrowing of asthma medications between patients and their social networks; (3) Economic factors may contribute to using home remedies instead of prescribed medications; (4) Social network members may be unaware of the factors that trigger asthma and therefore, contribute to asthma exacerbations. This study identified important social network interactions that may impact asthma management in Latino adults. These results can be used to broaden the current focus of asthma self-management programs to incorporate discussions on the role of social networks. A focus on social network interactions addresses the social epidemiology of asthma and advances our understanding of root causes that may underlie the high prevalence of asthma in many Latino communities.

Interface Control Document for the EMPACT Module that Estimates Electric Power Transmission System Response to EMP-Caused Damage

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

Werley, Kenneth Alan; Mccown, Andrew William

The EPREP code is designed to evaluate the effects of an Electro-Magnetic Pulse (EMP) on the electric power transmission system. The EPREP code embodies an umbrella framework that allows a user to set up analysis conditions and to examine analysis results. The code links to three major physics/engineering modules. The first module describes the EM wave in space and time. The second module evaluates the damage caused by the wave on specific electric power (EP) transmission system components. The third module evaluates the consequence of the damaged network on its (reduced) ability to provide electric power to meet demand. Thismore » third module is the focus of the present paper. The EMPACT code serves as the third module. The EMPACT name denotes EMP effects on Alternating Current Transmission systems. The EMPACT algorithms compute electric power transmission network flow solutions under severely damaged network conditions. Initial solutions are often characterized by unacceptible network conditions including line overloads and bad voltages. The EMPACT code contains algorithms to adjust optimally network parameters to eliminate network problems while minimizing outages. System adjustments include automatically adjusting control equipment (generator V control, variable transformers, and variable shunts), as well as non-automatic control of generator power settings and minimal load shedding. The goal is to evaluate the minimal loss of customer load under equilibrium (steady-state) conditions during peak demand.« less

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

PubMed

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation.

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator

PubMed Central

Hahne, Jan; Dahmen, David; Schuecker, Jannis; Frommer, Andreas; Bolten, Matthias; Helias, Moritz; Diesmann, Markus

2017-01-01

Contemporary modeling approaches to the dynamics of neural networks include two important classes of models: biologically grounded spiking neuron models and functionally inspired rate-based units. We present a unified simulation framework that supports the combination of the two for multi-scale modeling, enables the quantitative validation of mean-field approaches by spiking network simulations, and provides an increase in reliability by usage of the same simulation code and the same network model specifications for both model classes. While most spiking simulations rely on the communication of discrete events, rate models require time-continuous interactions between neurons. Exploiting the conceptual similarity to the inclusion of gap junctions in spiking network simulations, we arrive at a reference implementation of instantaneous and delayed interactions between rate-based models in a spiking network simulator. The separation of rate dynamics from the general connection and communication infrastructure ensures flexibility of the framework. In addition to the standard implementation we present an iterative approach based on waveform-relaxation techniques to reduce communication and increase performance for large-scale simulations of rate-based models with instantaneous interactions. Finally we demonstrate the broad applicability of the framework by considering various examples from the literature, ranging from random networks to neural-field models. The study provides the prerequisite for interactions between rate-based and spiking models in a joint simulation. PMID:28596730

Adaptive software-defined coded modulation for ultra-high-speed optical transport

NASA Astrophysics Data System (ADS)

Djordjevic, Ivan B.; Zhang, Yequn

2013-10-01

In optically-routed networks, different wavelength channels carrying the traffic to different destinations can have quite different optical signal-to-noise ratios (OSNRs) and signal is differently impacted by various channel impairments. Regardless of the data destination, an optical transport system (OTS) must provide the target bit-error rate (BER) performance. To provide target BER regardless of the data destination we adjust the forward error correction (FEC) strength. Depending on the information obtained from the monitoring channels, we select the appropriate code rate matching to the OSNR range that current channel OSNR falls into. To avoid frame synchronization issues, we keep the codeword length fixed independent of the FEC code being employed. The common denominator is the employment of quasi-cyclic (QC-) LDPC codes in FEC. For high-speed implementation, low-complexity LDPC decoding algorithms are needed, and some of them will be described in this invited paper. Instead of conventional QAM based modulation schemes, we employ the signal constellations obtained by optimum signal constellation design (OSCD) algorithm. To improve the spectral efficiency, we perform the simultaneous rate adaptation and signal constellation size selection so that the product of number of bits per symbol × code rate is closest to the channel capacity. Further, we describe the advantages of using 4D signaling instead of polarization-division multiplexed (PDM) QAM, by using the 4D MAP detection, combined with LDPC coding, in a turbo equalization fashion. Finally, to solve the problems related to the limited bandwidth of information infrastructure, high energy consumption, and heterogeneity of optical networks, we describe an adaptive energy-efficient hybrid coded-modulation scheme, which in addition to amplitude, phase, and polarization state employs the spatial modes as additional basis functions for multidimensional coded-modulation.

Kinetic models of gene expression including non-coding RNAs

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2011-03-01

In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

Neuronal network-based mathematical modeling of perceived verticality in acute unilateral vestibular lesions: from nerve to thalamus and cortex.

PubMed

Glasauer, S; Dieterich, M; Brandt, T

2018-05-29

Acute unilateral lesions of vestibular graviceptive pathways from the otolith organs and semicircular canals via vestibular nuclei and the thalamus to the parieto-insular vestibular cortex regularly cause deviations of perceived verticality in the frontal roll plane. These tilts are ipsilateral in peripheral and in ponto-medullary lesions and contralateral in ponto-mesencephalic lesions. Unilateral lesions of the vestibular thalamus or cortex cause smaller tilts of the perceived vertical, which may be either ipsilateral or contralateral. Using a neural network model, we previously explained why unilateral vestibular midbrain lesions rarely manifest with rotational vertigo. We here extend this approach, focussing on the direction-specific deviations of perceived verticality in the roll plane caused by acute unilateral vestibular lesions from the labyrinth to the cortex. Traditionally, the effect of unilateral peripheral lesions on perceived verticality has been attributed to a lesion-based bias of the otolith system. We here suggest, on the basis of a comparison of model simulations with patient data, that perceived visual tilt after peripheral lesions is caused by the effect of a torsional semicircular canal bias on the central gravity estimator. We further argue that the change of gravity coding from a peripheral/brainstem vectorial representation in otolith coordinates to a distributed population coding at thalamic and cortical levels can explain why unilateral thalamic and cortical lesions have a variable effect on perceived verticality. Finally, we propose how the population-coding network for gravity direction might implement the elements required for the well-known perceptual underestimation of the subjective visual vertical in tilted body positions.

Model-based design of RNA hybridization networks implemented in living cells

PubMed Central

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter

2017-01-01

Abstract Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. PMID:28934501

Digital watermarking for secure and adaptive teleconferencing

NASA Astrophysics Data System (ADS)

Vorbrueggen, Jan C.; Thorwirth, Niels

2002-04-01

The EC-sponsored project ANDROID aims to develop a management system for secure active networks. Active network means allowing the network's customers to execute code (Java-based so-called proxylets) on parts of the network infrastructure. Secure means that the network operator nonetheless retains full control over the network and its resources, and that proxylets use ANDROID-developed facilities to provide secure applications. Management is based on policies and allows autonomous, distributed decisions and actions to be taken. Proxylets interface with the system via policies; among actions they can take is controlling execution of other proxylets or redirection of network traffic. Secure teleconferencing is used as the application to demonstrate the approach's advantages. A way to control a teleconference's data streams is to use digital watermarking of the video, audio and/or shared-whiteboard streams, providing an imperceptible and inseparable side channel that delivers information from originating or intermediate stations to downstream stations. Depending on the information carried by the watermark, these stations can take many different actions. Examples are forwarding decisions based on security classifications (possibly time-varying) at security boundaries, set-up and tear-down of virtual private networks, intelligent and adaptive transcoding, recorder or playback control (e.g., speaking off the record), copyright protection, and sender authentication.

Effect of synapse dilution on the memory retrieval in structured attractor neural networks

NASA Astrophysics Data System (ADS)

Brunel, N.

1993-08-01

We investigate a simple model of structured attractor neural network (ANN). In this network a module codes for the category of the stored information, while another group of neurons codes for the remaining information. The probability distribution of stabilities of the patterns and the prototypes of the categories are calculated, for two different synaptic structures. The stability of the prototypes is shown to increase when the fraction of neurons coding for the category goes down. Then the effect of synapse destruction on the retrieval is studied in two opposite situations : first analytically in sparsely connected networks, then numerically in completely connected ones. In both cases the behaviour of the structured network and that of the usual homogeneous networks are compared. When lesions increase, two transitions are shown to appear in the behaviour of the structured network when one of the patterns is presented to the network. After the first transition the network recognizes the category of the pattern but not the individual pattern. After the second transition the network recognizes nothing. These effects are similar to syndromes caused by lesions in the central visual system, namely prosopagnosia and agnosia. In both types of networks (structured or homogeneous) the stability of the prototype is greater than the stability of individual patterns, however the first transition, for completely connected networks, occurs only when the network is structured.

Hierarchical surface code for network quantum computing with modules of arbitrary size

NASA Astrophysics Data System (ADS)

Li, Ying; Benjamin, Simon C.

2016-10-01

The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

Construction of a pulse-coupled dipole network capable of fear-like and relief-like responses

NASA Astrophysics Data System (ADS)

Lungsi Sharma, B.

2016-07-01

The challenge for neuroscience as an interdisciplinary programme is the integration of ideas among the disciplines to achieve a common goal. This paper deals with the problem of deriving a pulse-coupled neural network that is capable of demonstrating behavioural responses (fear-like and relief-like). Current pulse-coupled neural networks are designed mostly for engineering applications, particularly image processing. The discovered neural network was constructed using the method of minimal anatomies approach. The behavioural response of a level-coded activity-based model was used as a reference. Although the spiking-based model and the activity-based model are of different scales, the use of model-reference principle means that the characteristics that is referenced is its functional properties. It is demonstrated that this strategy of dissection and systematic construction is effective in the functional design of pulse-coupled neural network system with nonlinear signalling. The differential equations for the elastic weights in the reference model are replicated in the pulse-coupled network geometrically. The network reflects a possible solution to the problem of punishment and avoidance. The network developed in this work is a new network topology for pulse-coupled neural networks. Therefore, the model-reference principle is a powerful tool in connecting neuroscience disciplines. The continuity of concepts and phenomena is further maintained by systematic construction using methods like the method of minimal anatomies.

Optical Properties and Radiation-Enhanced Evaporation of Nanofluid Fuels Containing Carbon-Based Nanostructures

DTIC Science & Technology

2012-05-29

of the large aspect ratio, the SWCNTs tend to entangle with one another and form network structures. Single and isolated SWCNTs are fewer. The...separated and show much fewer network structures because of entanglement . Also, the length of the MWCNTs is about 100 nm, significantly shorter than that...processed by a self-developed MATLAB code to derive the droplet evaporation rate. A type K thermocouple with a thickness of 76 μm was used to suspend the

Supervised Multi-Authority Scheme with Blind Signature for IoT with Attribute Based Encryption

NASA Astrophysics Data System (ADS)

Nissenbaum, O. V.; Ponomarov, K. Y.; Zaharov, A. A.

2018-04-01

This article proposes a three-side cryptographic scheme for verifying device attributes with a Supervisor and a Certification Authority (CA) for attribute-based encryption. Two options are suggested: using a message authentication code and using a digital signature. The first version is suitable for networks with one CA, and the second one for networks with several CAs, including dynamic systems. Also, the addition of this scheme with a blind signature is proposed to preserve the confidentiality of the device attributes from the CA. The introduction gives a definition and a brief historical overview of attribute-based encryption (ABE), addresses the use of ABE in the Internet of Things.

Temporal coding in a silicon network of integrate-and-fire neurons.

PubMed

Liu, Shih-Chii; Douglas, Rodney

2004-09-01

Spatio-temporal processing of spike trains by neuronal networks depends on a variety of mechanisms distributed across synapses, dendrites, and somata. In natural systems, the spike trains and the processing mechanisms cohere though their common physical instantiation. This coherence is lost when the natural system is encoded for simulation on a general purpose computer. By contrast, analog VLSI circuits are, like neurons, inherently related by their real-time physics, and so, could provide a useful substrate for exploring neuronlike event-based processing. Here, we describe a hybrid analog-digital VLSI chip comprising a set of integrate-and-fire neurons and short-term dynamical synapses that can be configured into simple network architectures with some properties of neocortical neuronal circuits. We show that, despite considerable fabrication variance in the properties of individual neurons, the chip offers a viable substrate for exploring real-time spike-based processing in networks of neurons.

Motion-related resource allocation in dynamic wireless visual sensor network environments.

PubMed

Katsenou, Angeliki V; Kondi, Lisimachos P; Parsopoulos, Konstantinos E

2014-01-01

This paper investigates quality-driven cross-layer optimization for resource allocation in direct sequence code division multiple access wireless visual sensor networks. We consider a single-hop network topology, where each sensor transmits directly to a centralized control unit (CCU) that manages the available network resources. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each node, under four different quality-driven criteria that take into consideration the varying motion characteristics of each recorded video. For this purpose, we studied two approaches with a different tradeoff of quality and complexity. The first one allocates the resources individually for each sensor, whereas the second clusters them according to the recorded level of motion. In order to address the dynamic nature of the recorded scenery and re-allocate the resources whenever it is dictated by the changes in the amount of motion in the scenery, we propose a mechanism based on the particle swarm optimization algorithm, combined with two restarting schemes that either exploit the previously determined resource allocation or conduct a rough estimation of it. Experimental simulations demonstrate the efficiency of the proposed approaches.

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis.

PubMed

Gao, Bo; Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-Hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including "immune response" as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma.

Read-Write-Codes: An Erasure Resilient Encoding System for Flexible Reading and Writing in Storage Networks

NASA Astrophysics Data System (ADS)

Mense, Mario; Schindelhauer, Christian

We introduce the Read-Write-Coding-System (RWC) - a very flexible class of linear block codes that generate efficient and flexible erasure codes for storage networks. In particular, given a message x of k symbols and a codeword y of n symbols, an RW code defines additional parameters k ≤ r,w ≤ n that offer enhanced possibilities to adjust the fault-tolerance capability of the code. More precisely, an RWC provides linear left(n,k,dright)-codes that have (a) minimum distance d = n - r + 1 for any two codewords, and (b) for each codeword there exists a codeword for each other message with distance of at most w. Furthermore, depending on the values r,w and the code alphabet, different block codes such as parity codes (e.g. RAID 4/5) or Reed-Solomon (RS) codes (if r = k and thus, w = n) can be generated. In storage networks in which I/O accesses are very costly and redundancy is crucial, this flexibility has considerable advantages as r and w can optimally be adapted to read or write intensive applications; only w symbols must be updated if the message x changes completely, what is different from other codes which always need to rewrite y completely as x changes. In this paper, we first state a tight lower bound and basic conditions for all RW codes. Furthermore, we introduce special RW codes in which all mentioned parameters are adjustable even online, that is, those RW codes are adaptive to changing demands. At last, we point out some useful properties regarding safety and security of the stored data.

MOSES: A Matlab-based open-source stochastic epidemic simulator.

PubMed

Varol, Huseyin Atakan

2016-08-01

This paper presents an open-source stochastic epidemic simulator. Discrete Time Markov Chain based simulator is implemented in Matlab. The simulator capable of simulating SEQIJR (susceptible, exposed, quarantined, infected, isolated and recovered) model can be reduced to simpler models by setting some of the parameters (transition probabilities) to zero. Similarly, it can be extended to more complicated models by editing the source code. It is designed to be used for testing different control algorithms to contain epidemics. The simulator is also designed to be compatible with a network based epidemic simulator and can be used in the network based scheme for the simulation of a node. Simulations show the capability of reproducing different epidemic model behaviors successfully in a computationally efficient manner.

Qualitative analysis of social network influences on quitting smoking among individuals with serious mental illness.

PubMed

Aschbrenner, Kelly A; Naslund, John A; Gill, Lydia; Hughes, Terence; O'Malley, Alistair J; Bartels, Stephen J; Brunette, Mary F

2017-07-04

The prevalence of cigarette smoking among adults with serious mental illness (SMI) remains high in the United States despite the availability of effective smoking cessation treatment. Identifying social influences on smoking and smoking cessation may help enhance intervention strategies to help smokers with SMI quit. The objective of this qualitative study was to explore social network influences on efforts to quit smoking among adults with SMI enrolled in a cessation treatment program. Participants were 41 individuals with SMI enrolled in a Medicaid Demonstration Project of smoking cessation at community mental health centers. A convenience sampling strategy was used to recruit participants for social network interviews exploring the influence of family, friends, peers, and significant others on quitting smoking. A team-based analysis of qualitative data involved descriptive coding, grouping coded data into categories, and identifying themes across the data. Social barriers to quitting smoking included pro-smoking social norms, attitudes, and behaviors of social network members, and negative interactions with network members, either specific to smoking or that triggered smoking. Social facilitators to quitting included quitting with network members, having cessation role models, and social support for quitting from network members. Similar to the general population, social factors appear to influence efforts to quit smoking among individuals with SMI enrolled in cessation treatment. Interventions that leverage positive social influences on smoking cessation have the potential to enhance strategies to help individuals with SMI quit smoking.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Applying a rateless code in content delivery networks

NASA Astrophysics Data System (ADS)

Suherman; Zarlis, Muhammad; Parulian Sitorus, Sahat; Al-Akaidi, Marwan

2017-09-01

Content delivery network (CDN) allows internet providers to locate their services, to map their coverage into networks without necessarily to own them. CDN is part of the current internet infrastructures, supporting multi server applications especially social media. Various works have been proposed to improve CDN performances. Since accesses on social media servers tend to be short but frequent, providing redundant to the transmitted packets to ensure lost packets not degrade the information integrity may improve service performances. This paper examines the implementation of rateless code in the CDN infrastructure. The NS-2 evaluations show that rateless code is able to reduce packet loss up to 50%.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Exploring a QoS Driven Scheduling Approach for Peer-to-Peer Live Streaming Systems with Network Coding

PubMed Central

Cui, Laizhong; Lu, Nan; Chen, Fu

2014-01-01

Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968

Joint physical and numerical modeling of water distribution networks.

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

Zimmerman, Adam; O'Hern, Timothy John; Orear, Leslie Jr.

2009-01-01

This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in somemore » cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.« less

An interactive graphics program for manipulation and display of panel method geometry

NASA Technical Reports Server (NTRS)

Hall, J. F.; Neuhart, D. H.; Walkley, K. B.

1983-01-01

Modern aerodynamic panel methods that handle large, complex geometries have made evident the need to interactively manipulate, modify, and view such configurations. With this purpose in mind, the GEOM program was developed. It is a menu driven, interactive program that uses the Tektronix PLOT 10 graphics software to display geometry configurations which are characterized by an abutting set of networks. These networks are composed of quadrilateral panels which are described by the coordinates of their corners. GEOM is divided into fourteen executive controlled functions. These functions are used to build configurations, scale and rotate networks, transpose networks defining M and N lines, graphically display selected networks, join and split networks, create wake networks, produce symmetric images of networks, repanel and rename networks, display configuration cross sections, and output network geometry in two formats. A data base management system is used to facilitate data transfers in this program. A sample session illustrating various capabilities of the code is included as a guide to program operation.

Fractal Viscous Fingering in Fracture Networks

NASA Astrophysics Data System (ADS)

Boyle, E.; Sams, W.; Ferer, M.; Smith, D. H.

2007-12-01

We have used two very different physical models and computer codes to study miscible injection of a low- viscosity fluid into a simple fracture network, where it displaces a much-more viscous "defending" fluid through "rock" that is otherwise impermeable. The one code (NETfLow) is a standard pore level model, originally intended to treat laboratory-scale experiments; it assumes negligible mixing of the two fluids. The other code (NFFLOW) was written to treat reservoir-scale engineering problems; It explicitly treats the flow through the fractures and allows for significant mixing of the fluids at the interface. Both codes treat the fractures as parallel plates, of different effective apertures. Results are presented for the composition profiles from both codes. Independent of the degree of fluid-mixing, the profiles from both models have a functional form identical to that for fractal viscous fingering (i.e., diffusion limited aggregation, DLA). The two codes that solve the equations for different models gave similar results; together they suggest that the injection of a low-viscosity fluid into large- scale fracture networks may be much more significantly affected by fractal fingering than previously illustrated.

Automatic Web-based Calibration of Network-Capable Shipboard Sensors

DTIC Science & Technology

2007-09-01

Server, Java , Applet, and Servlet . 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY CLASSIFICATION OF THIS PAGE...49 b. Sensor Applet...........................................................................49 3. Java Servlet ...Table 1. Required System Environment Variables for Java Servlet Development. ......25 Table 2. Payload Data Format of the POST Requests from

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

Superdense Coding over Optical Fiber Links with Complete Bell-State Measurements

DOE PAGES

Williams, Brian P.; Sadlier, Ronald J.; Humble, Travis S.

2017-02-01

Adopting quantum communication to modern networking requires transmitting quantum information through a fiber-based infrastructure. In this paper, we report the first demonstration of superdense coding over optical fiber links, taking advantage of a complete Bell-state measurement enabled by time-polarization hyperentanglement, linear optics, and common single-photon detectors. Finally, we demonstrate the highest single-qubit channel capacity to date utilizing linear optics, 1.665 ± 0.018, and we provide a full experimental implementation of a hybrid, quantum-classical communication protocol for image transfer.

GLOBECOM '89 - IEEE Global Telecommunications Conference and Exhibition, Dallas, TX, Nov. 27-30, 1989, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

The present conference discusses topics in multiwavelength network technology and its applications, advanced digital radio systems in their propagation environment, mobile radio communications, switching programmability, advancements in computer communications, integrated-network management and security, HDTV and image processing in communications, basic exchange communications radio advancements in digital switching, intelligent network evolution, speech coding for telecommunications, and multiple access communications. Also discussed are network designs for quality assurance, recent progress in coherent optical systems, digital radio applications, advanced communications technologies for mobile users, communication software for switching systems, AI and expert systems in network management, intelligent multiplexing nodes, video and image coding, network protocols and performance, system methods in quality and reliability, the design and simulation of lightwave systems, local radio networks, mobile satellite communications systems, fiber networks restoration, packet video networks, human interfaces for future networks, and lightwave networking.

Design of Intelligent Cross-Layer Routing Protocols for Airborne Wireless Networks Under Dynamic Spectrum Access Paradigm

DTIC Science & Technology

2011-05-01

rate convolutional codes or the prioritized Rate - Compatible Punctured ...Quality of service RCPC Rate - compatible and punctured convolutional codes SNR Signal to noise ratio SSIM... Convolutional (RCPC) codes . The RCPC codes achieve UEP by puncturing off different amounts of coded bits of the parent code . The

Joint-layer encoder optimization for HEVC scalable extensions

NASA Astrophysics Data System (ADS)

Tsai, Chia-Ming; He, Yuwen; Dong, Jie; Ye, Yan; Xiu, Xiaoyu; He, Yong

2014-09-01

Scalable video coding provides an efficient solution to support video playback on heterogeneous devices with various channel conditions in heterogeneous networks. SHVC is the latest scalable video coding standard based on the HEVC standard. To improve enhancement layer coding efficiency, inter-layer prediction including texture and motion information generated from the base layer is used for enhancement layer coding. However, the overall performance of the SHVC reference encoder is not fully optimized because rate-distortion optimization (RDO) processes in the base and enhancement layers are independently considered. It is difficult to directly extend the existing joint-layer optimization methods to SHVC due to the complicated coding tree block splitting decisions and in-loop filtering process (e.g., deblocking and sample adaptive offset (SAO) filtering) in HEVC. To solve those problems, a joint-layer optimization method is proposed by adjusting the quantization parameter (QP) to optimally allocate the bit resource between layers. Furthermore, to make more proper resource allocation, the proposed method also considers the viewing probability of base and enhancement layers according to packet loss rate. Based on the viewing probability, a novel joint-layer RD cost function is proposed for joint-layer RDO encoding. The QP values of those coding tree units (CTUs) belonging to lower layers referenced by higher layers are decreased accordingly, and the QP values of those remaining CTUs are increased to keep total bits unchanged. Finally the QP values with minimal joint-layer RD cost are selected to match the viewing probability. The proposed method was applied to the third temporal level (TL-3) pictures in the Random Access configuration. Simulation results demonstrate that the proposed joint-layer optimization method can improve coding performance by 1.3% for these TL-3 pictures compared to the SHVC reference encoder without joint-layer optimization.

ACTS TDMA network control. [Advanced Communication Technology Satellite

NASA Technical Reports Server (NTRS)

Inukai, T.; Campanella, S. J.

1984-01-01

This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

NASA Astrophysics Data System (ADS)

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security.

PubMed

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-06-03

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks.

Resistance and Security Index of Networks: Structural Information Perspective of Network Security

PubMed Central

Li, Angsheng; Hu, Qifu; Liu, Jun; Pan, Yicheng

2016-01-01

Recently, Li and Pan defined the metric of the K-dimensional structure entropy of a structured noisy dataset G to be the information that controls the formation of the K-dimensional structure of G that is evolved by the rules, order and laws of G, excluding the random variations that occur in G. Here, we propose the notion of resistance of networks based on the one- and two-dimensional structural information of graphs. Given a graph G, we define the resistance of G, written , as the greatest overall number of bits required to determine the code of the module that is accessible via random walks with stationary distribution in G, from which the random walks cannot escape. We show that the resistance of networks follows the resistance law of networks, that is, for a network G, the resistance of G is , where and are the one- and two-dimensional structure entropies of G, respectively. Based on the resistance law, we define the security index of a network G to be the normalised resistance of G, that is, . We show that the resistance and security index are both well-defined measures for the security of the networks. PMID:27255783

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

PubMed Central

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

PubMed

Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

2009-01-01

The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures.

PubMed

Imran, Noreen; Seet, Boon-Chong; Fong, A C M

2015-01-01

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian-Wolf and Wyner-Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs.

Distributed reservation-based code division multiple access

NASA Astrophysics Data System (ADS)

Wieselthier, J. E.; Ephremides, A.

1984-11-01

The use of spread spectrum signaling, motivated primarily by its antijamming capabilities in military applications, leads naturally to the use of Code Division Multiple Access (CDMA) techniques that permit the successful simultaneous transmission by a number of users over a wideband channel. In this paper we address some of the major issues that are associated with the design of multiple access protocols for spread spectrum networks. We then propose, analyze, and evaluate a distributed reservation-based multiple access protocol that does in fact exploit CDMA properties. Especially significant is the fact that no acknowledgment or feedback information from the destination is required (thus facilitating communication with a radio-silent mode), nor is any form of coordination among the users necessary.

A New Network Modeling Tool for the Ground-based Nuclear Explosion Monitoring Community

NASA Astrophysics Data System (ADS)

Merchant, B. J.; Chael, E. P.; Young, C. J.

2013-12-01

Network simulations have long been used to assess the performance of monitoring networks to detect events for such purposes as planning station deployments and network resilience to outages. The standard tool has been the SAIC-developed NetSim package. With correct parameters, NetSim can produce useful simulations; however, the package has several shortcomings: an older language (FORTRAN), an emphasis on seismic monitoring with limited support for other technologies, limited documentation, and a limited parameter set. Thus, we are developing NetMOD (Network Monitoring for Optimal Detection), a Java-based tool designed to assess the performance of ground-based networks. NetMOD's advantages include: coded in a modern language that is multi-platform, utilizes modern computing performance (e.g. multi-core processors), incorporates monitoring technologies other than seismic, and includes a well-validated default parameter set for the IMS stations. NetMOD is designed to be extendable through a plugin infrastructure, so new phenomenological models can be added. Development of the Seismic Detection Plugin is being pursued first. Seismic location and infrasound and hydroacoustic detection plugins will follow. By making NetMOD an open-release package, it can hopefully provide a common tool that the monitoring community can use to produce assessments of monitoring networks and to verify assessments made by others.

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2011-01-01

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding

PubMed Central

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule’s error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism. PMID:27532262

Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.

PubMed

Gardner, Brian; Grüning, André

2016-01-01

Precise spike timing as a means to encode information in neural networks is biologically supported, and is advantageous over frequency-based codes by processing input features on a much shorter time-scale. For these reasons, much recent attention has been focused on the development of supervised learning rules for spiking neural networks that utilise a temporal coding scheme. However, despite significant progress in this area, there still lack rules that have a theoretical basis, and yet can be considered biologically relevant. Here we examine the general conditions under which synaptic plasticity most effectively takes place to support the supervised learning of a precise temporal code. As part of our analysis we examine two spike-based learning methods: one of which relies on an instantaneous error signal to modify synaptic weights in a network (INST rule), and the other one relying on a filtered error signal for smoother synaptic weight modifications (FILT rule). We test the accuracy of the solutions provided by each rule with respect to their temporal encoding precision, and then measure the maximum number of input patterns they can learn to memorise using the precise timings of individual spikes as an indication of their storage capacity. Our results demonstrate the high performance of the FILT rule in most cases, underpinned by the rule's error-filtering mechanism, which is predicted to provide smooth convergence towards a desired solution during learning. We also find the FILT rule to be most efficient at performing input pattern memorisations, and most noticeably when patterns are identified using spikes with sub-millisecond temporal precision. In comparison with existing work, we determine the performance of the FILT rule to be consistent with that of the highly efficient E-learning Chronotron rule, but with the distinct advantage that our FILT rule is also implementable as an online method for increased biological realism.

STDP-based spiking deep convolutional neural networks for object recognition.

PubMed

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Waveguide-type optical circuits for recognition of optical 8QAM-coded label

NASA Astrophysics Data System (ADS)

Surenkhorol, Tumendemberel; Kishikawa, Hiroki; Goto, Nobuo; Gonchigsumlaa, Khishigjargal

2017-10-01

Optical signal processing is expected to be applied in network nodes. In photonic routers, label recognition is one of the important functions. We have studied different kinds of label recognition methods so far for on-off keying, binary phase-shift keying, quadrature phase-shift keying, and 16 quadrature amplitude modulation-coded labels. We propose a method based on waveguide circuits to recognize an optical eight quadrature amplitude modulation (8QAM)-coded label by simple passive optical signal processing. The recognition of the proposed method is theoretically analyzed and numerically simulated by the finite difference beam propagation method. The noise tolerance is discussed, and bit-error rate against optical signal-to-noise ratio is evaluated. The scalability of the proposed method is also discussed theoretically for two-symbol length 8QAM-coded labels.

Programmable multi-node quantum network design and simulation

NASA Astrophysics Data System (ADS)

Dasari, Venkat R.; Sadlier, Ronald J.; Prout, Ryan; Williams, Brian P.; Humble, Travis S.

2016-05-01

Software-defined networking offers a device-agnostic programmable framework to encode new network functions. Externally centralized control plane intelligence allows programmers to write network applications and to build functional network designs. OpenFlow is a key protocol widely adopted to build programmable networks because of its programmability, flexibility and ability to interconnect heterogeneous network devices. We simulate the functional topology of a multi-node quantum network that uses programmable network principles to manage quantum metadata for protocols such as teleportation, superdense coding, and quantum key distribution. We first show how the OpenFlow protocol can manage the quantum metadata needed to control the quantum channel. We then use numerical simulation to demonstrate robust programmability of a quantum switch via the OpenFlow network controller while executing an application of superdense coding. We describe the software framework implemented to carry out these simulations and we discuss near-term efforts to realize these applications.

Seluge++: A Secure Over-the-Air Programming Scheme in Wireless Sensor Networks

PubMed Central

Doroodgar, Farzan; Razzaque, Mohammad Abdur; Isnin, Ismail Fauzi

2014-01-01

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge. PMID:24618781

Seluge++: a secure over-the-air programming scheme in wireless sensor networks.

PubMed

Doroodgar, Farzan; Abdur Razzaque, Mohammad; Isnin, Ismail Fauzi

2014-03-11

Over-the-air dissemination of code updates in wireless sensor networks have been researchers' point of interest in the last few years, and, more importantly, security challenges toward the remote propagation of code updating have occupied the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strength, having their concentration on the constrained nature of wireless sensor network (WSN) nodes. For authentication purposes, most of them have used a Merkle hash tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be at a standard level. Therefore, they have not investigated the tree structure for mission-critical situations in which security has to be at the maximum possible level (e.g., military applications, healthcare). Considering this, we investigate existing security models used in over-the-air dissemination of code updates for possible vulnerabilities, and then, we provide a set of countermeasures, correspondingly named Security Model Requirements. Based on the investigation, we concentrate on Seluge, one of the existing over-the-air programming schemes, and we propose an improved version of it, named Seluge++, which complies with the Security Model Requirements and replaces the use of the inefficient Merkle tree with a novel method. Analytical and simulation results show the improvements in Seluge++ compared to Seluge.

TOUGH-RBSN simulator for hydraulic fracture propagation within fractured media: Model validations against laboratory experiments

NASA Astrophysics Data System (ADS)

Kim, Kunhwi; Rutqvist, Jonny; Nakagawa, Seiji; Birkholzer, Jens

2017-11-01

This paper presents coupled hydro-mechanical modeling of hydraulic fracturing processes in complex fractured media using a discrete fracture network (DFN) approach. The individual physical processes in the fracture propagation are represented by separate program modules: the TOUGH2 code for multiphase flow and mass transport based on the finite volume approach; and the rigid-body-spring network (RBSN) model for mechanical and fracture-damage behavior, which are coupled with each other. Fractures are modeled as discrete features, of which the hydrological properties are evaluated from the fracture deformation and aperture change. The verification of the TOUGH-RBSN code is performed against a 2D analytical model for single hydraulic fracture propagation. Subsequently, modeling capabilities for hydraulic fracturing are demonstrated through simulations of laboratory experiments conducted on rock-analogue (soda-lime glass) samples containing a designed network of pre-existing fractures. Sensitivity analyses are also conducted by changing the modeling parameters, such as viscosity of injected fluid, strength of pre-existing fractures, and confining stress conditions. The hydraulic fracturing characteristics attributed to the modeling parameters are investigated through comparisons of the simulation results.

A novel coherent optical en/decoder for optical label processing of OCDM-based optical packets switching networks

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Qiu, Kun

2007-11-01

A coherent optical en/decoder based on photonic crystal (PhC) for optical code-division-multiple (OCDM)-based optical label (OCDM-OL) optical packets switching (OPS) networks is proposed in this paper. In this scheme, the optical pulse phase and time delay can be flexibly controlled by the photonic crystal phase shifter and delayer using the appropriate design of fabrication. In this design, the combination calculation of the impurity and normal period layers is applied, according to the PhC transmission matrix theorem. The design and theoretical analysis of the PhC-based optical coherent en/decoder is mainly focused. In addition, the performances of the PhC-based optical en/decoders are analyzed in detail. The reflection, the transmission, delay characteristic and the optical spectrum of pulse en/decoded are studied for the waves tuned in the photonic band-gap by the numerical calculation, taking into account 1-Dimension (1D) PhC. Theoretical analysis and numerical results show that optical pulse is achieved to properly phase modulation and time delay by the proposed scheme, optical label based on OCDM is rewrote successfully by new code for OCDM-based OPS (OCDM-OPS), and an over 8.5 dB ration of auto- and cross-correlation is gained, which demonstrates the applicability of true pulse phase modulation in a number of applications.

Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis

PubMed Central

Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-hua; Xue, Dongbo

2017-01-01

Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including “immune response” as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma. PMID:28355233

The strategic management of organizational knowledge exchange related to hospital quality measurement and reporting.

PubMed

Rangachari, Pavani

2008-01-01

CONTEXT/PURPOSE: With the growing momentum toward hospital quality measurement and reporting by public and private health care payers, hospitals face increasing pressures to improve their medical record documentation and administrative data coding accuracy. This study explores the relationship between the organizational knowledge-sharing structure related to quality and hospital coding accuracy for quality measurement. Simultaneously, this study seeks to identify other leadership/management characteristics associated with coding for quality measurement. Drawing upon complexity theory, the literature on "professional complex systems" has put forth various strategies for managing change and turnaround in professional organizations. In so doing, it has emphasized the importance of knowledge creation and organizational learning through interdisciplinary networks. This study integrates complexity, network structure, and "subgoals" theories to develop a framework for knowledge-sharing network effectiveness in professional complex systems. This framework is used to design an exploratory and comparative research study. The sample consists of 4 hospitals, 2 showing "good coding" accuracy for quality measurement and 2 showing "poor coding" accuracy. Interviews and surveys are conducted with administrators and staff in the quality, medical staff, and coding subgroups in each facility. Findings of this study indicate that good coding performance is systematically associated with a knowledge-sharing network structure rich in brokerage and hierarchy (with leaders connecting different professional subgroups to each other and to the external environment), rather than in density (where everyone is directly connected to everyone else). It also implies that for the hospital organization to adapt to the changing environment of quality transparency, senior leaders must undertake proactive and unceasing efforts to coordinate knowledge exchange across physician and coding subgroups and connect these subgroups with the changing external environment.

Connection anonymity analysis in coded-WDM PONs

NASA Astrophysics Data System (ADS)

Sue, Chuan-Ching

2008-04-01

A coded wavelength division multiplexing passive optical network (WDM PON) is presented for fiber to the home (FTTH) systems to protect against eavesdropping. The proposed scheme applies spectral amplitude coding (SAC) with a unipolar maximal-length sequence (M-sequence) code matrix to generate a specific signature address (coding) and to retrieve its matching address codeword (decoding) by exploiting the cyclic properties inherent in array waveguide grating (AWG) routers. In addition to ensuring the confidentiality of user data, the proposed coded-WDM scheme is also a suitable candidate for the physical layer with connection anonymity. Under the assumption that the eavesdropper applies a photo-detection strategy, it is shown that the coded WDM PON outperforms the conventional TDM PON and WDM PON schemes in terms of a higher degree of connection anonymity. Additionally, the proposed scheme allows the system operator to partition the optical network units (ONUs) into appropriate groups so as to achieve a better degree of anonymity.

Nodal network generator for CAVE3

NASA Technical Reports Server (NTRS)

Palmieri, J. V.; Rathjen, K. A.

1982-01-01

A new extension of CAVE3 code was developed that automates the creation of a finite difference math model in digital form ready for input to the CAVE3 code. The new software, Nodal Network Generator, is broken into two segments. One segment generates the model geometry using a Tektronix Tablet Digitizer and the other generates the actual finite difference model and allows for graphic verification using Tektronix 4014 Graphic Scope. Use of the Nodal Network Generator is described.

IMC/RMC Network Professional Film Collection.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Special Education Instructional Materials Center.

The compilation is a comprehensive listing of films available from the centers in the Instructional Materials Centers/Regional Media Centers (IMC/RMC) Network. Each IMC/RMC location is given a numerical code in a preliminary listing. These numerical codes are used within the film listing, which is arranged alphabetically according to film titles,…

Physical-layer network coding in coherent optical OFDM systems.

PubMed

Guan, Xun; Chan, Chun-Kit

2015-04-20

We present the first experimental demonstration and characterization of the application of optical physical-layer network coding in coherent optical OFDM systems. It combines two optical OFDM frames to share the same link so as to enhance system throughput, while individual OFDM frames can be recovered with digital signal processing at the destined node.

Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

DTIC Science & Technology

2010-12-10

Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code.

PubMed

Kunkel, Susanne; Schenck, Wolfram

2017-01-01

NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

PubMed Central

Kunkel, Susanne; Schenck, Wolfram

2017-01-01

NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling. PMID:28701946

Distributed intelligent control and status networking

NASA Technical Reports Server (NTRS)

Fortin, Andre; Patel, Manoj

1993-01-01

Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

Model-based design of RNA hybridization networks implemented in living cells.

PubMed

Rodrigo, Guillermo; Prakash, Satya; Shen, Shensi; Majer, Eszter; Daròs, José-Antonio; Jaramillo, Alfonso

2017-09-19

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

GLOBECOM '86 - Global Telecommunications Conference, Houston, TX, Dec. 1-4, 1986, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Papers are presented on local area networks; formal methods for communication protocols; computer simulation of communication systems; spread spectrum and coded communications; tropical radio propagation; VLSI for communications; strategies for increasing software productivity; multiple access communications; advanced communication satellite technologies; and spread spectrum systems. Topics discussed include Space Station communication and tracking development and design; transmission networks; modulation; data communications; computer network protocols and performance; and coding and synchronization. Consideration is given to free space optical communications systems; VSAT communication networks; network topology design; advances in adaptive filtering echo cancellation and adaptive equalization; advanced signal processing for satellite communications; the elements, design, and analysis of fiber-optic networks; and advances in digital microwave systems.

Random sampling of elementary flux modes in large-scale metabolic networks.

PubMed

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

A comparison of frame synchronization methods. [Deep Space Network

NASA Technical Reports Server (NTRS)

Swanson, L.

1982-01-01

Different methods are considered for frame synchronization of a concatenated block code/Viterbi link. Synchronization after Viterbi decoding, synchronization before Viterbi decoding based on hard-quantized channel symbols are all compared. For each scheme, the probability under certain conditions of true detection of sync within four 10,000 bit frames is tabulated.

Assessing Argumentative Representation with Bayesian Network Models in Debatable Social Issues

ERIC Educational Resources Information Center

Zhang, Zhidong; Lu, Jingyan

2014-01-01

This study seeks to obtain argumentation models, which represent argumentative processes and an assessment structure in secondary school debatable issues in the social sciences. The argumentation model was developed based on mixed methods, a combination of both theory-driven and data-driven methods. The coding system provided a combing point by…

Neural Energy Supply-Consumption Properties Based on Hodgkin-Huxley Model

PubMed Central

2017-01-01

Electrical activity is the foundation of the neural system. Coding theories that describe neural electrical activity by the roles of action potential timing or frequency have been thoroughly studied. However, an alternative method to study coding questions is the energy method, which is more global and economical. In this study, we clearly defined and calculated neural energy supply and consumption based on the Hodgkin-Huxley model, during firing action potentials and subthreshold activities using ion-counting and power-integral model. Furthermore, we analyzed energy properties of each ion channel and found that, under the two circumstances, power synchronization of ion channels and energy utilization ratio have significant differences. This is particularly true of the energy utilization ratio, which can rise to above 100% during subthreshold activity, revealing an overdraft property of energy use. These findings demonstrate the distinct status of the energy properties during neuronal firings and subthreshold activities. Meanwhile, after introducing a synapse energy model, this research can be generalized to energy calculation of a neural network. This is potentially important for understanding the relationship between dynamical network activities and cognitive behaviors. PMID:28316842

Patterns of Electronic Portal Use among Vulnerable Patients in a Nationwide Practice-based Research Network: From the OCHIN Practice-based Research Network (PBRN)

PubMed Central

Wallace, Lorraine S.; Angier, Heather; Huguet, Nathalie; Gaudino, James A.; Krist, Alex; Dearing, Marla; Killerby, Marie; Marino, Miguel; DeVoe, Jennifer E.

2017-01-01

Background Underserved patient populations experience barriers to accessing and engaging within the complex health care system. Electronic patient portals have been proposed as a potential new way to improve access and engagement. We studied patient portal use for 12 consecutive months (365 days) among a large, nationally distributed, underserved patient population within the OCHIN (originally created as the Oregon Community Health Information Network and renamed OCHIN as other states joined) practice-based research network (PBRN). Methods We retrospectively assessed adoption and use of Epic’s MyChart patient portal in the first 12 months after MyChart was made available to the OCHIN PBRN. We examined electronic health record data from 36,549 patients aged ≥18 years who were offered a MyChart access code between May 1, 2012, and April 30, 2013, across the OCHIN PBRN in 13 states. Results Overall, 29% of patients offered an access code logged into their MyChart account. Superusers (minimum of 2 logins per month over a 12-month period) accounted for 6% of users overall. Men, nonwhite patients, Hispanic patients, Spanish-speaking patients, and those with the lowest incomes were significantly less likely to activate. Publicly insured and uninsured patients were also less likely to log in to their MyChart account, but once activated they were more likely than privately insured patients to use MyChart functions. Conclusions Our findings suggest that, compared with others, certain patient groups may be less interested in using patient portals or may have experienced significant barriers that prevented use. Making portal access available is a first step. Additional studies need to specifically identify health system–, clinic-, and patient-level barriers and facilitators to portal adoption and use. PMID:27613792

Neural coordination can be enhanced by occasional interruption of normal firing patterns: a self-optimizing spiking neural network model.

PubMed

Woodward, Alexander; Froese, Tom; Ikegami, Takashi

2015-02-01

The state space of a conventional Hopfield network typically exhibits many different attractors of which only a small subset satisfies constraints between neurons in a globally optimal fashion. It has recently been demonstrated that combining Hebbian learning with occasional alterations of normal neural states avoids this problem by means of self-organized enlargement of the best basins of attraction. However, so far it is not clear to what extent this process of self-optimization is also operative in real brains. Here we demonstrate that it can be transferred to more biologically plausible neural networks by implementing a self-optimizing spiking neural network model. In addition, by using this spiking neural network to emulate a Hopfield network with Hebbian learning, we attempt to make a connection between rate-based and temporal coding based neural systems. Although further work is required to make this model more realistic, it already suggests that the efficacy of the self-optimizing process is independent from the simplifying assumptions of a conventional Hopfield network. We also discuss natural and cultural processes that could be responsible for occasional alteration of neural firing patterns in actual brains. Copyright © 2014 Elsevier Ltd. All rights reserved.

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

PubMed Central

Zhu, Xuqi; Liu, Yu; Zhang, Lin

2009-01-01

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

A Bayesian network coding scheme for annotating biomedical information presented to genetic counseling clients.

PubMed

Green, Nancy

2005-04-01

We developed a Bayesian network coding scheme for annotating biomedical content in layperson-oriented clinical genetics documents. The coding scheme supports the representation of probabilistic and causal relationships among concepts in this domain, at a high enough level of abstraction to capture commonalities among genetic processes and their relationship to health. We are using the coding scheme to annotate a corpus of genetic counseling patient letters as part of the requirements analysis and knowledge acquisition phase of a natural language generation project. This paper describes the coding scheme and presents an evaluation of intercoder reliability for its tag set. In addition to giving examples of use of the coding scheme for analysis of discourse and linguistic features in this genre, we suggest other uses for it in analysis of layperson-oriented text and dialogue in medical communication.

The impact of nuclear mass models on r-process nucleosynthesis network calculations

NASA Astrophysics Data System (ADS)

Vaughan, Kelly

2002-10-01

An insight into understanding various nucleosynthesis processes is via modelling of the process with network calculations. My project focus is r-process network calculations where the r-process is nucleosynthesis via rapid neutron capture thought to take place in high entropy supernova bubbles. One of the main uncertainties of the simulations is the Nuclear Physics input. My project investigates the role that nuclear masses play in the resulting abundances. The code tecode, involves rapid (n,γ) capture reactions in competition with photodisintegration and β decay onto seed nuclei. In order to fully analyze the effects of nuclear mass models on the relative isotopic abundances, calculations were done from the network code, keeping the initial environmental parameters constant throughout. The supernova model investigated by Qian et al (1996) in which two r-processes, of high and low frequency with seed nucleus ^90Se and of fixed luminosity (fracL_ν_e(0)r_7(0)^2 ˜= 8.77), contribute to the nucleosynthesis of the heavier elements. These two r-processes, however, do not contribute equally to the total abundance observed. The total isotopic abundance produced from both events was therefore calculated using equation refabund. Y(H+L) = fracY(H)+fY(L)f+1 <~belabund where Y(H) denotes the relative isotopic abundance produced in the high frequency event, Y(L) corresponds to the low freqeuncy event and f is the ratio of high event matter to low event matter produced. Having established reliable, fixed parameters, the network code was run using data files containing parameters such as the mass excess, neutron separation energy, β decay rates and neutron capture rates based around three different nuclear mass models. The mass models tested are the HFBCS model (Hartree-Fock BCS) derived from first principles, the ETFSI-Q model (Extended Thomas-Fermi with Strutinsky Integral including shell Quenching) known for its particular successes in the replication of Solar System abundances, and the P-Scheme Model tePscheme. The aims of this research is to test the applicability of the P-Scheme in relation to the other mass models to the r-process network calculations. 02 Pscheme Aprahamian,A., Gadala-Maria,A. & Cuka,N. 1996, Revista Mexicana de Fisica,42,1 code Surman,R. & Engel,J. 1998, Phys.Rev. C,54,4 thebibliography

Smooth Upgrade of Existing Passive Optical Networks With Spectral-Shaping Line-Coding Service Overlay

NASA Astrophysics Data System (ADS)

Hsueh, Yu-Li; Rogge, Matthew S.; Shaw, Wei-Tao; Kim, Jaedon; Yamamoto, Shu; Kazovsky, Leonid G.

2005-09-01

A simple and cost-effective upgrade of existing passive optical networks (PONs) is proposed, which realizes service overlay by novel spectral-shaping line codes. A hierarchical coding procedure allows processing simplicity and achieves desired long-term spectral properties. Different code rates are supported, and the spectral shape can be properly tailored to adapt to different systems. The computation can be simplified by quantization of trigonometric functions. DC balance is achieved by passing the dc residual between processing windows. The proposed line codes tend to introduce bit transitions to avoid long consecutive identical bits and facilitate receiver clock recovery. Experiments demonstrate and compare several different optimized line codes. For a specific tolerable interference level, the optimal line code can easily be determined, which maximizes the data throughput. The service overlay using the line-coding technique leaves existing services and field-deployed fibers untouched but fully functional, providing a very flexible and economic way to upgrade existing PONs.

Cooperative MIMO communication at wireless sensor network: an error correcting code approach.

PubMed

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error p(b). It is observed that C-MIMO performs more efficiently when the targeted p(b) is smaller. Also the lower encoding rate for LDPC code offers better error characteristics.

Cooperative MIMO Communication at Wireless Sensor Network: An Error Correcting Code Approach

PubMed Central

Islam, Mohammad Rakibul; Han, Young Shin

2011-01-01

Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error pb. It is observed that C-MIMO performs more efficiently when the targeted pb is smaller. Also the lower encoding rate for LDPC code offers better error characteristics. PMID:22163732

Fast neural network surrogates for very high dimensional physics-based models in computational oceanography.

PubMed

van der Merwe, Rudolph; Leen, Todd K; Lu, Zhengdong; Frolov, Sergey; Baptista, Antonio M

2007-05-01

We present neural network surrogates that provide extremely fast and accurate emulation of a large-scale circulation model for the coupled Columbia River, its estuary and near ocean regions. The circulation model has O(10(7)) degrees of freedom, is highly nonlinear and is driven by ocean, atmospheric and river influences at its boundaries. The surrogates provide accurate emulation of the full circulation code and run over 1000 times faster. Such fast dynamic surrogates will enable significant advances in ensemble forecasts in oceanography and weather.

Android platform based smartphones for a logistical remote association repair framework.

PubMed

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-06-25

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use.

Neural network for image compression

NASA Astrophysics Data System (ADS)

Panchanathan, Sethuraman; Yeap, Tet H.; Pilache, B.

1992-09-01

In this paper, we propose a new scheme for image compression using neural networks. Image data compression deals with minimization of the amount of data required to represent an image while maintaining an acceptable quality. Several image compression techniques have been developed in recent years. We note that the coding performance of these techniques may be improved by employing adaptivity. Over the last few years neural network has emerged as an effective tool for solving a wide range of problems involving adaptivity and learning. A multilayer feed-forward neural network trained using the backward error propagation algorithm is used in many applications. However, this model is not suitable for image compression because of its poor coding performance. Recently, a self-organizing feature map (SOFM) algorithm has been proposed which yields a good coding performance. However, this algorithm requires a long training time because the network starts with random initial weights. In this paper we have used the backward error propagation algorithm (BEP) to quickly obtain the initial weights which are then used to speedup the training time required by the SOFM algorithm. The proposed approach (BEP-SOFM) combines the advantages of the two techniques and, hence, achieves a good coding performance in a shorter training time. Our simulation results demonstrate the potential gains using the proposed technique.

Implementing Signature Neural Networks with Spiking Neurons

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm—i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data—to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks. PMID:28066221

Implementing Signature Neural Networks with Spiking Neurons.

PubMed

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.

Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks.

PubMed

Zhang, Jing; Liu, Shi-Jian; Tsai, Pei-Wei; Zou, Fu-Min; Ji, Xiao-Rong

2018-01-01

Data gathering is a fundamental task in Wireless Visual Sensor Networks (WVSNs). Features of directional antennas and the visual data make WVSNs more complex than the conventional Wireless Sensor Network (WSN). The virtual backbone is a technique, which is capable of constructing clusters. The version associating with the aggregation operation is also referred to as the virtual backbone tree. In most of the existing literature, the main focus is on the efficiency brought by the construction of clusters that the existing methods neglect local-balance problems in general. To fill up this gap, Directional Virtual Backbone based Data Aggregation Scheme (DVBDAS) for the WVSNs is proposed in this paper. In addition, a measurement called the energy consumption density is proposed for evaluating the adequacy of results in the cluster-based construction problems. Moreover, the directional virtual backbone construction scheme is proposed by considering the local-balanced factor. Furthermore, the associated network coding mechanism is utilized to construct DVBDAS. Finally, both the theoretical analysis of the proposed DVBDAS and the simulations are given for evaluating the performance. The experimental results prove that the proposed DVBDAS achieves higher performance in terms of both the energy preservation and the network lifetime extension than the existing methods.

Spread Spectrum Visual Sensor Network Resource Management Using an End-to-End Cross-Layer Design

DTIC Science & Technology

2011-02-01

Coding In this work, we use rate compatible punctured convolutional (RCPC) codes for channel coding [11]. Using RCPC codes al- lows us to utilize Viterbi’s...11] J. Hagenauer, “ Rate - compatible punctured convolutional codes (RCPC codes ) and their applications,” IEEE Trans. Commun., vol. 36, no. 4, pp. 389...source coding rate , a channel coding rate , and a power level to all nodes in the

Evaluation of H.264/AVC over IEEE 802.11p vehicular networks

NASA Astrophysics Data System (ADS)

Rozas-Ramallal, Ismael; Fernández-Caramés, Tiago M.; Dapena, Adriana; García-Naya, José Antonio

2013-12-01

The capacity of vehicular networks to offer non-safety services, like infotainment applications or the exchange of multimedia information between vehicles, have attracted a great deal of attention to the field of Intelligent Transport Systems (ITS). In particular, in this article we focus our attention on IEEE 802.11p which defines enhancements to IEEE 802.11 required to support ITS applications. We present an FPGA-based testbed developed to evaluate H.264/AVC (Advanced Video Coding) video transmission over vehicular networks. The testbed covers some of the most common situations in vehicle-to-vehicle and roadside-to-vehicle communications and it is highly flexible, allowing the performance evaluation of different vehicular standard configurations. We also show several experimental results to illustrate the quality obtained when H.264/AVC encoded video is transmitted over IEEE 802.11p networks. The quality is measured considering two important parameters: the percentage of recovered group of pictures and the frame quality. In order to improve performance, we propose to substitute the convolutional channel encoder used in IEEE 802.11p for a low-density parity-check code encoder. In addition, we suggest a simple strategy to decide the optimum number of iterations needed to decode each packet received.

Neurobehavioral Assessment from Fetus to Infant: The NICU Network Neurobehavioral Scale and the Fetal Neurobehavior Coding Scale

ERIC Educational Resources Information Center

Salisbury, Amy L.; Fallone, Melissa Duncan; Lester, Barry

2005-01-01

This review provides an overview and definition of the concept of neurobehavior in human development. Two neurobehavioral assessments used by the authors in current fetal and infant research are discussed: the NICU Network Neurobehavioral Assessment Scale and the Fetal Neurobehavior Coding System. This review will present how the two assessments…

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

Male-to-Female Transgender Individuals Building Social Support and Capital From Within a Gender-Focused Network

PubMed Central

Pinto, Rogério M.; Melendez, Rita M.; Spector, Anya Y.

2009-01-01

The literature on male-to-female transgender (MTF) individuals lists myriad problems such individuals face in their day-to-day lives, including high rates of HIV/AIDS, addiction to drugs, violence, and lack of health care. These problems are exacerbated for ethnic and racial minority MTFs. Support available from their social networks can help MTFs alleviate these problems. This article explores how minority MTFs, specifically in an urban environment, develop supportive social networks defined by their gender and sexual identities. Using principles of community-based participatory research (CBPR), 20 African American and Latina MTFs were recruited at a community-based health care clinic. Their ages ranged from 18 to 53. Data were coded and analyzed following standard procedure for content analysis. The qualitative interviews revealed that participants formed their gender and sexual identities over time, developed gender-focused social networks based in the clinic from which they receive services, and engaged in social capital building and political action. Implications for using CBPR in research with MTFs are discussed. PMID:20418965

Male-to-Female Transgender Individuals Building Social Support and Capital From Within a Gender-Focused Network.

PubMed

Pinto, Rogério M; Melendez, Rita M; Spector, Anya Y

2008-09-01

The literature on male-to-female transgender (MTF) individuals lists myriad problems such individuals face in their day-to-day lives, including high rates of HIV/AIDS, addiction to drugs, violence, and lack of health care. These problems are exacerbated for ethnic and racial minority MTFs. Support available from their social networks can help MTFs alleviate these problems. This article explores how minority MTFs, specifically in an urban environment, develop supportive social networks defined by their gender and sexual identities. Using principles of community-based participatory research (CBPR), 20 African American and Latina MTFs were recruited at a community-based health care clinic. Their ages ranged from 18 to 53. Data were coded and analyzed following standard procedure for content analysis. The qualitative interviews revealed that participants formed their gender and sexual identities over time, developed gender-focused social networks based in the clinic from which they receive services, and engaged in social capital building and political action. Implications for using CBPR in research with MTFs are discussed.

An Energy Model of Place Cell Network in Three Dimensional Space.

PubMed

Wang, Yihong; Xu, Xuying; Wang, Rubin

2018-01-01

Place cells are important elements in the spatial representation system of the brain. A considerable amount of experimental data and classical models are achieved in this area. However, an important question has not been addressed, which is how the three dimensional space is represented by the place cells. This question is preliminarily surveyed by energy coding method in this research. Energy coding method argues that neural information can be expressed by neural energy and it is convenient to model and compute for neural systems due to the global and linearly addable properties of neural energy. Nevertheless, the models of functional neural networks based on energy coding method have not been established. In this work, we construct a place cell network model to represent three dimensional space on an energy level. Then we define the place field and place field center and test the locating performance in three dimensional space. The results imply that the model successfully simulates the basic properties of place cells. The individual place cell obtains unique spatial selectivity. The place fields in three dimensional space vary in size and energy consumption. Furthermore, the locating error is limited to a certain level and the simulated place field agrees to the experimental results. In conclusion, this is an effective model to represent three dimensional space by energy method. The research verifies the energy efficiency principle of the brain during the neural coding for three dimensional spatial information. It is the first step to complete the three dimensional spatial representing system of the brain, and helps us further understand how the energy efficiency principle directs the locating, navigating, and path planning function of the brain.

Mobile satellite business networks: A part of the European mobile system

NASA Technical Reports Server (NTRS)

deMateo, M. L.; Jongejans, A.; Loisy, C.; VanHimbeeck, C.; Marchal, J. P.; Borella, A.; Sartori, M.

1995-01-01

The European Space Agency (ESA) is presently procuring an L-band payload EMS, to be embarked on the ITALSAT-2 satellite due for launch in early 1996, in order to promote a regional European mobile system. One of the Land Mobile Communication systems supported by EMS is the MSBN (Mobile Satellite Business Network) voice and data system which will offer the services of a business network on a seamless European coverage. This paper will first recall the characteristics of the MSBN system, which is based on quasi-synchronized CDMA (Code Division Multiple Access) techniques in both directions, and then describe the CDMA receivers implementation. Main validation test results will also be reported confirming predicted performances.

Ant-Based Cyber Defense (also known as

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

Glenn Fink, PNNL

2015-09-29

ABCD is a four-level hierarchy with human supervisors at the top, a top-level agent called a Sergeant controlling each enclave, Sentinel agents located at each monitored host, and mobile Sensor agents that swarm through the enclaves to detect cyber malice and misconfigurations. The code comprises four parts: (1) the core agent framework, (2) the user interface and visualization, (3) test-range software to create a network of virtual machines including a simulated Internet and user and host activity emulation scripts, and (4) a test harness to allow the safe running of adversarial code within the framework of monitored virtual machines.

Deep Learning Methods for Improved Decoding of Linear Codes

NASA Astrophysics Data System (ADS)

Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

2018-02-01

The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

Wireless Visual Sensor Network Resource Allocation using Cross-Layer Optimization

DTIC Science & Technology

2009-01-01

Rate Compatible Punctured Convolutional (RCPC) codes for channel...vol. 44, pp. 2943–2959, November 1998. [22] J. Hagenauer, “ Rate - compatible punctured convolutional codes (RCPC codes ) and their applications,” IEEE... coding rate for H.264/AVC video compression is determined. At the data link layer, the Rate - Compatible Puctured Convolutional (RCPC) channel coding

Building Interactive Simulations in Web Pages without Programming.

PubMed

Mailen Kootsey, J; McAuley, Grant; Bernal, Julie

2005-01-01

A software system is described for building interactive simulations and other numerical calculations in Web pages. The system is based on a new Java-based software architecture named NumberLinX (NLX) that isolates each function required to build the simulation so that a library of reusable objects could be assembled. The NLX objects are integrated into a commercial Web design program for coding-free page construction. The model description is entered through a wizard-like utility program that also functions as a model editor. The complete system permits very rapid construction of interactive simulations without coding. A wide range of applications are possible with the system beyond interactive calculations, including remote data collection and processing and collaboration over a network.

Implementation of data management and effect on chronic disease coding in a primary care organisation: A parallel cohort observational study.

PubMed

Greiver, Michelle; Wintemute, Kimberly; Aliarzadeh, Babak; Martin, Ken; Khan, Shahriar; Jackson, Dave; Leggett, Jannet; Lambert-Lanning, Anita; Siu, Maggie

2016-10-12

Consistent and standardized coding for chronic conditions is associated with better care; however, coding may currently be limited in electronic medical records (EMRs) used in Canadian primary care.Objectives To implement data management activities in a community-based primary care organisation and to evaluate the effects on coding for chronic conditions. Fifty-nine family physicians in Toronto, Ontario, belonging to a single primary care organisation, participated in the study. The organisation implemented a central analytical data repository containing their EMR data extracted, cleaned, standardized and returned by the Canadian Primary Care Sentinel Surveillance Network (CPCSSN), a large validated primary care EMR-based database. They used reporting software provided by CPCSSN to identify selected chronic conditions and standardized codes were then added back to the EMR. We studied four chronic conditions (diabetes, hypertension, chronic obstructive pulmonary disease and dementia). We compared changes in coding over six months for physicians in the organisation with changes for 315 primary care physicians participating in CPCSSN across Canada. Chronic disease coding within the organisation increased significantly more than in other primary care sites. The adjusted difference in the increase of coding was 7.7% (95% confidence interval 7.1%-8.2%, p < 0.01). The use of standard codes, consisting of the most common diagnostic codes for each condition in the CPCSSN database, increased by 8.9% more (95% CI 8.3%-9.5%, p < 0.01). Data management activities were associated with an increase in standardized coding for chronic conditions. Exploring requirements to scale and spread this approach in Canadian primary care organisations may be worthwhile.

Decoding the encoding of functional brain networks: An fMRI classification comparison of non-negative matrix factorization (NMF), independent component analysis (ICA), and sparse coding algorithms.

PubMed

Xie, Jianwen; Douglas, Pamela K; Wu, Ying Nian; Brody, Arthur L; Anderson, Ariana E

2017-04-15

Brain networks in fMRI are typically identified using spatial independent component analysis (ICA), yet other mathematical constraints provide alternate biologically-plausible frameworks for generating brain networks. Non-negative matrix factorization (NMF) would suppress negative BOLD signal by enforcing positivity. Spatial sparse coding algorithms (L1 Regularized Learning and K-SVD) would impose local specialization and a discouragement of multitasking, where the total observed activity in a single voxel originates from a restricted number of possible brain networks. The assumptions of independence, positivity, and sparsity to encode task-related brain networks are compared; the resulting brain networks within scan for different constraints are used as basis functions to encode observed functional activity. These encodings are then decoded using machine learning, by using the time series weights to predict within scan whether a subject is viewing a video, listening to an audio cue, or at rest, in 304 fMRI scans from 51 subjects. The sparse coding algorithm of L1 Regularized Learning outperformed 4 variations of ICA (p<0.001) for predicting the task being performed within each scan using artifact-cleaned components. The NMF algorithms, which suppressed negative BOLD signal, had the poorest accuracy compared to the ICA and sparse coding algorithms. Holding constant the effect of the extraction algorithm, encodings using sparser spatial networks (containing more zero-valued voxels) had higher classification accuracy (p<0.001). Lower classification accuracy occurred when the extracted spatial maps contained more CSF regions (p<0.001). The success of sparse coding algorithms suggests that algorithms which enforce sparsity, discourage multitasking, and promote local specialization may capture better the underlying source processes than those which allow inexhaustible local processes such as ICA. Negative BOLD signal may capture task-related activations. Copyright © 2017 Elsevier B.V. All rights reserved.

Signal Detection and Frame Synchronization of Multiple Wireless Networking Waveforms

DTIC Science & Technology

2007-09-01

punctured to obtain coding rates of 2 3 and 3 4 . Convolutional forward error correction coding is used to detect and correct bit...likely to be isolated and be correctable by the convolutional decoder. 44 Data rate (Mbps) Modulation Coding Rate Coded bits per subcarrier...binary convolutional code . A shortened Reed-Solomon technique is employed first. The code is shortened depending upon the data

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

DOE PAGES

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.; ...

2017-01-26

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

Topology-Aware Performance Optimization and Modeling of Adaptive Mesh Refinement Codes for Exascale

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

Chan, Cy P.; Bachan, John D.; Kenny, Joseph P.

Here, we introduce a topology-aware performance optimization and modeling workflow for AMR simulation that includes two new modeling tools, ProgrAMR and Mota Mapper, which interface with the BoxLib AMR framework and the SSTmacro network simulator. ProgrAMR allows us to generate and model the execution of task dependency graphs from high-level specifications of AMR-based applications, which we demonstrate by analyzing two example AMR-based multigrid solvers with varying degrees of asynchrony. Mota Mapper generates multiobjective, network topology-aware box mappings, which we apply to optimize the data layout for the example multigrid solvers. While the sensitivity of these solvers to layout and executionmore » strategy appears to be modest for balanced scenarios, the impact of better mapping algorithms can be significant when performance is highly constrained by network hop latency. Furthermore, we show that network latency in the multigrid bottom solve is the main contributing factor preventing good scaling on exascale-class machines.« less

A robust low-rate coding scheme for packet video

NASA Technical Reports Server (NTRS)

Chen, Y. C.; Sayood, Khalid; Nelson, D. J.; Arikan, E. (Editor)

1991-01-01

Due to the rapidly evolving field of image processing and networking, video information promises to be an important part of telecommunication systems. Although up to now video transmission has been transported mainly over circuit-switched networks, it is likely that packet-switched networks will dominate the communication world in the near future. Asynchronous transfer mode (ATM) techniques in broadband-ISDN can provide a flexible, independent and high performance environment for video communication. For this paper, the network simulator was used only as a channel in this simulation. Mixture blocking coding with progressive transmission (MBCPT) has been investigated for use over packet networks and has been found to provide high compression rate with good visual performance, robustness to packet loss, tractable integration with network mechanics and simplicity in parallel implementation.

Unconstrained handwritten numeral recognition based on radial basis competitive and cooperative networks with spatio-temporal feature representation.

PubMed

Lee, S; Pan, J J

1996-01-01

This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.

Intrinsic and Extrinsic Neuromodulation of Olfactory Processing.

PubMed

Lizbinski, Kristyn M; Dacks, Andrew M

2017-01-01

Neuromodulation is a ubiquitous feature of neural systems, allowing flexible, context specific control over network dynamics. Neuromodulation was first described in invertebrate motor systems and early work established a basic dichotomy for neuromodulation as having either an intrinsic origin (i.e., neurons that participate in network coding) or an extrinsic origin (i.e., neurons from independent networks). In this conceptual dichotomy, intrinsic sources of neuromodulation provide a "memory" by adjusting network dynamics based upon previous and ongoing activation of the network itself, while extrinsic neuromodulators provide the context of ongoing activity of other neural networks. Although this dichotomy has been thoroughly considered in motor systems, it has received far less attention in sensory systems. In this review, we discuss intrinsic and extrinsic modulation in the context of olfactory processing in invertebrate and vertebrate model systems. We begin by discussing presynaptic modulation of olfactory sensory neurons by local interneurons (LNs) as a mechanism for gain control based on ongoing network activation. We then discuss the cell-class specific effects of serotonergic centrifugal neurons on olfactory processing. Finally, we briefly discuss the integration of intrinsic and extrinsic neuromodulation (metamodulation) as an effective mechanism for exerting global control over olfactory network dynamics. The heterogeneous nature of neuromodulation is a recurring theme throughout this review as the effects of both intrinsic and extrinsic modulation are generally non-uniform.

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

Indianapolis emergency medical service and the Indiana Network for Patient Care: evaluating the patient match algorithm.

PubMed

Park, Seong C; Finnell, John T

2012-01-01

In 2009, Indianapolis launched an electronic medical record system within their ambulances1 and started to exchange patient data with the Indiana Network for Patient Care (INPC) This unique system allows EMS personnel to get important information prior to the patient's arrival to the hospital. In this descriptive study, we found EMS personnel requested patient data on 14% of all transports, with a "success" match rate of 46%, and a match "failure" rate of 17%. The three major factors for causing match "failure" were ZIP code 55%, Patient Name 22%, and Birth date 12%. We conclude that the ZIP code matching process needs to be improved by applying a limitation of 5 digits in ZIP code instead of using ZIP+4 code. Non-ZIP code identifiers may be a better choice due to inaccuracies and changes of the ZIP code in a patient's record.

What the success of brain imaging implies about the neural code.

PubMed

Guest, Olivia; Love, Bradley C

2017-01-19

The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI's limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution, the neural code must be smooth at the voxel and functional level such that similar stimuli engender similar internal representations. Through proof and simulation, we determine which coding schemes are plausible given both fMRI's successes and its limitations in measuring neural activity. Deep neural network approaches, which have been forwarded as computational accounts of the ventral stream, are consistent with the success of fMRI, though functional smoothness breaks down in the later network layers. These results have implications for the nature of the neural code and ventral stream, as well as what can be successfully investigated with fMRI.

Theta phase precession and phase selectivity: a cognitive device description of neural coding

NASA Astrophysics Data System (ADS)

Zalay, Osbert C.; Bardakjian, Berj L.

2009-06-01

Information in neural systems is carried by way of phase and rate codes. Neuronal signals are processed through transformative biophysical mechanisms at the cellular and network levels. Neural coding transformations can be represented mathematically in a device called the cognitive rhythm generator (CRG). Incoming signals to the CRG are parsed through a bank of neuronal modes that orchestrate proportional, integrative and derivative transformations associated with neural coding. Mode outputs are then mixed through static nonlinearities to encode (spatio) temporal phase relationships. The static nonlinear outputs feed and modulate a ring device (limit cycle) encoding output dynamics. Small coupled CRG networks were created to investigate coding functionality associated with neuronal phase preference and theta precession in the hippocampus. Phase selectivity was found to be dependent on mode shape and polarity, while phase precession was a product of modal mixing (i.e. changes in the relative contribution or amplitude of mode outputs resulted in shifting phase preference). Nonlinear system identification was implemented to help validate the model and explain response characteristics associated with modal mixing; in particular, principal dynamic modes experimentally derived from a hippocampal neuron were inserted into a CRG and the neuron's dynamic response was successfully cloned. From our results, small CRG networks possessing disynaptic feedforward inhibition in combination with feedforward excitation exhibited frequency-dependent inhibitory-to-excitatory and excitatory-to-inhibitory transitions that were similar to transitions seen in a single CRG with quadratic modal mixing. This suggests nonlinear modal mixing to be a coding manifestation of the effect of network connectivity in shaping system dynamic behavior. We hypothesize that circuits containing disynaptic feedforward inhibition in the nervous system may be candidates for interpreting upstream rate codes to guide downstream processes such as phase precession, because of their demonstrated frequency-selective properties.

Temporal motifs reveal collaboration patterns in online task-oriented networks

NASA Astrophysics Data System (ADS)

Xuan, Qi; Fang, Huiting; Fu, Chenbo; Filkov, Vladimir

2015-05-01

Real networks feature layers of interactions and complexity. In them, different types of nodes can interact with each other via a variety of events. Examples of this complexity are task-oriented social networks (TOSNs), where teams of people share tasks towards creating a quality artifact, such as academic research papers or software development in commercial or open source environments. Accomplishing those tasks involves both work, e.g., writing the papers or code, and communication, to discuss and coordinate. Taking into account the different types of activities and how they alternate over time can result in much more precise understanding of the TOSNs behaviors and outcomes. That calls for modeling techniques that can accommodate both node and link heterogeneity as well as temporal change. In this paper, we report on methodology for finding temporal motifs in TOSNs, limited to a system of two people and an artifact. We apply the methods to publicly available data of TOSNs from 31 Open Source Software projects. We find that these temporal motifs are enriched in the observed data. When applied to software development outcome, temporal motifs reveal a distinct dependency between collaboration and communication in the code writing process. Moreover, we show that models based on temporal motifs can be used to more precisely relate both individual developer centrality and team cohesion to programmer productivity than models based on aggregated TOSNs.

Temporal motifs reveal collaboration patterns in online task-oriented networks.

PubMed

Xuan, Qi; Fang, Huiting; Fu, Chenbo; Filkov, Vladimir

2015-05-01

Real networks feature layers of interactions and complexity. In them, different types of nodes can interact with each other via a variety of events. Examples of this complexity are task-oriented social networks (TOSNs), where teams of people share tasks towards creating a quality artifact, such as academic research papers or software development in commercial or open source environments. Accomplishing those tasks involves both work, e.g., writing the papers or code, and communication, to discuss and coordinate. Taking into account the different types of activities and how they alternate over time can result in much more precise understanding of the TOSNs behaviors and outcomes. That calls for modeling techniques that can accommodate both node and link heterogeneity as well as temporal change. In this paper, we report on methodology for finding temporal motifs in TOSNs, limited to a system of two people and an artifact. We apply the methods to publicly available data of TOSNs from 31 Open Source Software projects. We find that these temporal motifs are enriched in the observed data. When applied to software development outcome, temporal motifs reveal a distinct dependency between collaboration and communication in the code writing process. Moreover, we show that models based on temporal motifs can be used to more precisely relate both individual developer centrality and team cohesion to programmer productivity than models based on aggregated TOSNs.

A DNA-Inspired Encryption Methodology for Secure, Mobile Ad Hoc Networks

NASA Technical Reports Server (NTRS)

Shaw, Harry

2012-01-01

Users are pushing for greater physical mobility with their network and Internet access. Mobile ad hoc networks (MANET) can provide an efficient mobile network architecture, but security is a key concern. A figure summarizes differences in the state of network security for MANET and fixed networks. MANETs require the ability to distinguish trusted peers, and tolerate the ingress/egress of nodes on an unscheduled basis. Because the networks by their very nature are mobile and self-organizing, use of a Public Key Infra structure (PKI), X.509 certificates, RSA, and nonce ex changes becomes problematic if the ideal of MANET is to be achieved. Molecular biology models such as DNA evolution can provide a basis for a proprietary security architecture that achieves high degrees of diffusion and confusion, and resistance to cryptanalysis. A proprietary encryption mechanism was developed that uses the principles of DNA replication and steganography (hidden word cryptography) for confidentiality and authentication. The foundation of the approach includes organization of coded words and messages using base pairs organized into genes, an expandable genome consisting of DNA-based chromosome keys, and a DNA-based message encoding, replication, and evolution and fitness. In evolutionary computing, a fitness algorithm determines whether candidate solutions, in this case encrypted messages, are sufficiently encrypted to be transmitted. The technology provides a mechanism for confidential electronic traffic over a MANET without a PKI for authenticating users.

Network of anatomical texts (NAnaTex), an open-source project for visualizing the interaction between anatomical terms.

PubMed

Momota, Ryusuke; Ohtsuka, Aiji

2018-01-01

Anatomy is the science and art of understanding the structure of the body and its components in relation to the functions of the whole-body system. Medicine is based on a deep understanding of anatomy, but quite a few introductory-level learners are overwhelmed by the sheer amount of anatomical terminology that must be understood, so they regard anatomy as a dull and dense subject. To help them learn anatomical terms in a more contextual way, we started a new open-source project, the Network of Anatomical Texts (NAnaTex), which visualizes relationships of body components by integrating text-based anatomical information using Cytoscape, a network visualization software platform. Here, we present a network of bones and muscles produced from literature descriptions. As this network is primarily text-based and does not require any programming knowledge, it is easy to implement new functions or provide extra information by making changes to the original text files. To facilitate collaborations, we deposited the source code files for the network into the GitHub repository ( https://github.com/ryusukemomota/nanatex ) so that anybody can participate in the evolution of the network and use it for their own non-profit purposes. This project should help not only introductory-level learners but also professional medical practitioners, who could use it as a quick reference.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

Deep linear autoencoder and patch clustering-based unified one-dimensional coding of image and video

NASA Astrophysics Data System (ADS)

Li, Honggui

2017-09-01

This paper proposes a unified one-dimensional (1-D) coding framework of image and video, which depends on deep learning neural network and image patch clustering. First, an improved K-means clustering algorithm for image patches is employed to obtain the compact inputs of deep artificial neural network. Second, for the purpose of best reconstructing original image patches, deep linear autoencoder (DLA), a linear version of the classical deep nonlinear autoencoder, is introduced to achieve the 1-D representation of image blocks. Under the circumstances of 1-D representation, DLA is capable of attaining zero reconstruction error, which is impossible for the classical nonlinear dimensionality reduction methods. Third, a unified 1-D coding infrastructure for image, intraframe, interframe, multiview video, three-dimensional (3-D) video, and multiview 3-D video is built by incorporating different categories of videos into the inputs of patch clustering algorithm. Finally, it is shown in the results of simulation experiments that the proposed methods can simultaneously gain higher compression ratio and peak signal-to-noise ratio than those of the state-of-the-art methods in the situation of low bitrate transmission.

nRC: non-coding RNA Classifier based on structural features.

PubMed

Fiannaca, Antonino; La Rosa, Massimo; La Paglia, Laura; Rizzo, Riccardo; Urso, Alfonso

2017-01-01

Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically relevant roles has opened the way to develop methods able to discriminate between the different ncRNA classes. Moreover, the lack of knowledge about the complete mechanisms in regulative processes, together with the development of high-throughput technologies, has required the help of bioinformatics tools in addressing biologists and clinicians with a deeper comprehension of the functional roles of ncRNAs. In this work, we introduce a new ncRNA classification tool, nRC (non-coding RNA Classifier). Our approach is based on features extraction from the ncRNA secondary structure together with a supervised classification algorithm implementing a deep learning architecture based on convolutional neural networks. We tested our approach for the classification of 13 different ncRNA classes. We obtained classification scores, using the most common statistical measures. In particular, we reach an accuracy and sensitivity score of about 74%. The proposed method outperforms other similar classification methods based on secondary structure features and machine learning algorithms, including the RNAcon tool that, to date, is the reference classifier. nRC tool is freely available as a docker image at https://hub.docker.com/r/tblab/nrc/. The source code of nRC tool is also available at https://github.com/IcarPA-TBlab/nrc.

Performance Analysis of Hybrid ARQ Protocols in a Slotted Code Division Multiple-Access Network

DTIC Science & Technology

1989-08-01

Convolutional Codes . in Proc Int. Conf. Commun., 21.4.1-21.4.5, 1987. [27] J. Hagenauer. Rate Compatible Punctured Convolutional Codes . in Proc Int. Conf...achieved by using a low rate (r = 0.5), high constraint length (e.g., 32) punctured convolutional code . Code puncturing provides for a variable rate code ...investigated the use of convolutional codes in Type II Hybrid ARQ protocols. The error

Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment.

PubMed

Mills, James D; Iyer, Anand M; van Scheppingen, Jackelien; Bongaarts, Anika; Anink, Jasper J; Janssen, Bart; Zimmer, Till S; Spliet, Wim G; van Rijen, Peter C; Jansen, Floor E; Feucht, Martha; Hainfellner, Johannes A; Krsek, Pavel; Zamecnik, Josef; Kotulska, Katarzyna; Jozwiak, Sergiusz; Jansen, Anna; Lagae, Lieven; Curatolo, Paolo; Kwiatkowski, David J; Pasterkamp, R Jeroen; Senthilkumar, Ketharini; von Oerthel, Lars; Hoekman, Marco F; Gorter, Jan A; Crino, Peter B; Mühlebner, Angelika; Scicluna, Brendon P; Aronica, Eleonora

2017-08-14

Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Dynamic quality of service differentiation using fixed code weight in optical CDMA networks

NASA Astrophysics Data System (ADS)

Kakaee, Majid H.; Essa, Shawnim I.; Abd, Thanaa H.; Seyedzadeh, Saleh

2015-11-01

The emergence of network-driven applications, such as internet, video conferencing, and online gaming, brings in the need for a network the environments with capability of providing diverse Quality of Services (QoS). In this paper, a new code family of novel spreading sequences, called a Multi-Service (MS) code, has been constructed to support multiple services in Optical- Code Division Multiple Access (CDMA) system. The proposed method uses fixed weight for all services, however reducing the interfering codewords for the users requiring higher QoS. The performance of the proposed code is demonstrated using mathematical analysis. It shown that the total number of served users with satisfactory BER of 10-9 using NB=2 is 82, while they are only 36 and 10 when NB=3 and 4 respectively. The developed MS code is compared with variable-weight codes such as Variable Weight-Khazani Syed (VW-KS) and Multi-Weight-Random Diagonal (MW-RD). Different numbers of basic users (NB) are used to support triple-play services (audio, data and video) with different QoS requirements. Furthermore, reference to the BER of 10-12, 10-9, and 10-3 for video, data and audio, respectively, the system can support up to 45 total users. Hence, results show that the technique can clearly provide a relative QoS differentiation with lower value of basic users can support larger number of subscribers as well as better performance in terms of acceptable BER of 10-9 at fixed code weight.

Evaluation of four-dimensional nonbinary LDPC-coded modulation for next-generation long-haul optical transport networks.

PubMed

Zhang, Yequn; Arabaci, Murat; Djordjevic, Ivan B

2012-04-09

Leveraging the advanced coherent optical communication technologies, this paper explores the feasibility of using four-dimensional (4D) nonbinary LDPC-coded modulation (4D-NB-LDPC-CM) schemes for long-haul transmission in future optical transport networks. In contrast to our previous works on 4D-NB-LDPC-CM which considered amplified spontaneous emission (ASE) noise as the dominant impairment, this paper undertakes transmission in a more realistic optical fiber transmission environment, taking into account impairments due to dispersion effects, nonlinear phase noise, Kerr nonlinearities, and stimulated Raman scattering in addition to ASE noise. We first reveal the advantages of using 4D modulation formats in LDPC-coded modulation instead of conventional two-dimensional (2D) modulation formats used with polarization-division multiplexing (PDM). Then we demonstrate that 4D LDPC-coded modulation schemes with nonbinary LDPC component codes significantly outperform not only their conventional PDM-2D counterparts but also the corresponding 4D bit-interleaved LDPC-coded modulation (4D-BI-LDPC-CM) schemes, which employ binary LDPC codes as component codes. We also show that the transmission reach improvement offered by the 4D-NB-LDPC-CM over 4D-BI-LDPC-CM increases as the underlying constellation size and hence the spectral efficiency of transmission increases. Our results suggest that 4D-NB-LDPC-CM can be an excellent candidate for long-haul transmission in next-generation optical networks.

Entropy based file type identification and partitioning

DTIC Science & Technology

2017-06-01

energy spectrum,” Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, pp. 288–293, 2016...ABBREVIATIONS AES Advanced Encryption Standard ANN Artificial Neural Network ASCII American Standard Code for Information Interchange CWT...the identification of file types and file partitioning. This approach has applications in cybersecurity as it allows for a quick determination of

Teaching Energy as Part of Education for Sustainability

ERIC Educational Resources Information Center

Tas, Maarten; McKeon, Frankie; Charnley, Fiona; Fleming, Margaret

2014-01-01

This article describes how energy issues and education for sustainable development (ESD) are part of the agenda for two current European projects, CoDeS and SUSTAIN. The latter is mainly concerned with the development of inquiry-based primary and lower secondary science education while the former is a network that aims to learn more about…

The Basis of Hyperspecificity in Autism: A Preliminary Suggestion Based on Properties of Neural Nets.

ERIC Educational Resources Information Center

McClelland, James L.

2000-01-01

This article discusses representation of information in neural networks and the apparent hyperspecificity that is often seen in the application of previously acquired information by children with autism. Hyperspecificity is seen as reflecting a possible feature of the neural codes used to represent concepts in the autistic brain. (Contains 12…

Unsupervised segmentation with dynamical units.

PubMed

Rao, A Ravishankar; Cecchi, Guillermo A; Peck, Charles C; Kozloski, James R

2008-01-01

In this paper, we present a novel network to separate mixtures of inputs that have been previously learned. A significant capability of the network is that it segments the components of each input object that most contribute to its classification. The network consists of amplitude-phase units that can synchronize their dynamics, so that separation is determined by the amplitude of units in an output layer, and segmentation by phase similarity between input and output layer units. Learning is unsupervised and based on a Hebbian update, and the architecture is very simple. Moreover, efficient segmentation can be achieved even when there is considerable superposition of the inputs. The network dynamics are derived from an objective function that rewards sparse coding in the generalized amplitude-phase variables. We argue that this objective function can provide a possible formal interpretation of the binding problem and that the implementation of the network architecture and dynamics is biologically plausible.

Validation of The Health Improvement Network (THIN) Database for Epidemiologic Studies of Chronic Kidney Disease

PubMed Central

Denburg, Michelle R.; Haynes, Kevin; Shults, Justine; Lewis, James D.; Leonard, Mary B.

2011-01-01

Purpose Chronic kidney disease (CKD) is a prevalent and important outcome and covariate in pharmacoepidemiology. The Health Improvement Network (THIN) in the U.K. represents a unique resource for population-based studies of CKD. We compiled a valid list of Read codes to identify subjects with moderate to advanced CKD. Methods A cross-sectional validation study was performed to identify codes that best define CKD stages 3–5. All subjects with at least one non-zero measure of serum creatinine after 1-Jan-2002 were included. Estimated glomerular filtration rate (eGFR) was calculated according to the Schwartz formula for subjects <18 years and the Modification of Diet in Renal Disease formula for subjects ≥18 years of age. CKD was defined as an eGFR <60 ml/min/1.73m2 on at least two occasions, more than 90 days apart. Results The laboratory definition identified 230,426 subjects with CKD, for a period prevalence in 2008 of 4.56% (95% CI: 4.54, 4.58). A list of 45 Read codes was compiled which yielded a positive predictive value of 88.9% (95% CI: 88.7, 89.1), sensitivity of 48.8%, negative predictive value of 86.5%, and specificity of 98.2%. Of the 11.1% of subjects with a code who did not meet the laboratory definition, 83.6% had at least one eGFR <60. The most commonly used code was for CKD stage 3. Conclusions The proposed list of codes can be used to accurately identify CKD when serum creatinine data are limited. The most sensitive approach for the detection of CKD is to use this list to supplement creatinine measures. PMID:22020900

Validation of The Health Improvement Network (THIN) database for epidemiologic studies of chronic kidney disease.

PubMed

Denburg, Michelle R; Haynes, Kevin; Shults, Justine; Lewis, James D; Leonard, Mary B

2011-11-01

Chronic kidney disease (CKD) is a prevalent and important outcome and covariate in pharmacoepidemiology. The Health Improvement Network (THIN) in the UK represents a unique resource for population-based studies of CKD. We compiled a valid list of Read codes to identify subjects with moderate to advanced CKD. A cross-sectional validation study was performed to identify codes that best define CKD Stages 3-5. All subjects with at least one non-zero measure of serum creatinine after 1 January 2002 were included. Estimated glomerular filtration rate (eGFR) was calculated according to the Schwartz formula for subjects aged < 18 years and the Modification of Diet in Renal Disease formula for subjects aged ≥ 18 years. CKD was defined as an eGFR <60 mL/minute/1.73 m² on at least two occasions, more than 90 days apart. The laboratory definition identified 230,426 subjects with CKD, for a period prevalence in 2008 of 4.56% (95%CI, 4.54-4.58). A list of 45 Read codes was compiled, which yielded a positive predictive value of 88.9% (95%CI, 88.7-89.1), sensitivity of 48.8%, negative predictive value of 86.5%, and specificity of 98.2%. Of the 11.1% of subjects with a code who did not meet the laboratory definition, 83.6% had at least one eGFR <60. The most commonly used code was for CKD Stage 3. The proposed list of codes can be used to accurately identify CKD when serum creatinine data are limited. The most sensitive approach for the detection of CKD is to use this list to supplement creatinine measures. Copyright © 2011 John Wiley & Sons, Ltd.

Threshold Tear Strength of some Molecular Networks.

DTIC Science & Technology

1981-04-03

Attn: Dr. F. Roberto Office of Naval Research 1 AFSC Western Office Andrews AFB, Code DLFP 1030 East Green Street Washington, DC 20334 Pasadena, CA...of Chemical & Office Atmospheric Sciences 495 Summer Street Bolling Air Force Base Boston, MA 02210 Washington, DC 20332 Attn: Dr. L. Peebles Dr. A...Plaza Suite 601 Bolling Air Force Base San Francisco, CA 94102 Washington, DC 20332 Attn: Dr. P. A. Miller Attn: Dr. L. H. Caveny Defense Technical

Aviation Security: Biometric Technology and Risk Based Security Aviation Passenger Screening Program

DTIC Science & Technology

2012-12-01

distribution is unlimited 12b. DISTRIBUTION CODE A 13. ABSTRACT (maximum 200 words ) Since 9/11, the Transportation Security Administration (TSA...Council POE Point Of Entry RBS Risk-Based Security SENTRI Secure Electronic Network for Travelers Rapid Inspection SFPD Secure Flight Passenger...Committee on Biometrics provides the origins of biometrics; the term “biometrics” is derived from the Greek words “bio” (life) and “metrics” (to measure

Automated Run-Time Mission and Dialog Generation

DTIC Science & Technology

2007-03-01

Processing, Social Network Analysis, Simulation, Automated Scenario Generation 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified...9 D. SOCIAL NETWORKS...13 B. MISSION AND DIALOG GENERATION.................................................13 C. SOCIAL NETWORKS

Operational problems of Haniwa net as a form of social capital: interdependence between human networks of physicians and information networks.

PubMed

Maeda, Minoru; Araki, Sanae; Suzuki, Muneou; Umemoto, Katsuhiro; Kai, Yukiko; Araki, Kenji

2012-10-01

In August 2009, Miyazaki Health and Welfare Network (Haniwa Net, hereafter referred to as "the Net"), centrally led by University of Miyazaki Hospital (UMH), adopted a center hospital-based system offering a unilateral linkage that enables the viewing of UMH's medical records through a web-based browser (electronic medical records (EMR)). By the end of December 2010, the network had developed into a system of 79 collaborating physicians from within the prefecture. Beginning in August 2010, physicians in 12 medical institutions were visited and asked to speak freely on the operational issues concerning the Net. Recordings and written accounts were coded using the text analysis software MAXQDA 10 to understand the actual state of operations. Analysis of calculations of Kendall's rank correlation confirmed that the interdependency between human networks and information networks is significant. At the same time, while the negative opinions concerning the functions of the Net were somewhat conspicuous, the results showed a correlation between requests and proposals for operational improvements of the Net, clearly indicating the need for a more user-friendly system and a better viewer.

Network meta-analysis of disconnected networks: How dangerous are random baseline treatment effects?

PubMed

Béliveau, Audrey; Goring, Sarah; Platt, Robert W; Gustafson, Paul

2017-12-01

In network meta-analysis, the use of fixed baseline treatment effects (a priori independent) in a contrast-based approach is regularly preferred to the use of random baseline treatment effects (a priori dependent). That is because, often, there is not a need to model baseline treatment effects, which carry the risk of model misspecification. However, in disconnected networks, fixed baseline treatment effects do not work (unless extra assumptions are made), as there is not enough information in the data to update the prior distribution on the contrasts between disconnected treatments. In this paper, we investigate to what extent the use of random baseline treatment effects is dangerous in disconnected networks. We take 2 publicly available datasets of connected networks and disconnect them in multiple ways. We then compare the results of treatment comparisons obtained from a Bayesian contrast-based analysis of each disconnected network using random normally distributed and exchangeable baseline treatment effects to those obtained from a Bayesian contrast-based analysis of their initial connected network using fixed baseline treatment effects. For the 2 datasets considered, we found that the use of random baseline treatment effects in disconnected networks was appropriate. Because those datasets were not cherry-picked, there should be other disconnected networks that would benefit from being analyzed using random baseline treatment effects. However, there is also a risk for the normality and exchangeability assumption to be inappropriate in other datasets even though we have not observed this situation in our case study. We provide code, so other datasets can be investigated. Copyright © 2017 John Wiley & Sons, Ltd.

The origins and evolutionary history of human non-coding RNA regulatory networks.

PubMed

Sherafatian, Masih; Mowla, Seyed Javad

2017-04-01

The evolutionary history and origin of the regulatory function of animal non-coding RNAs are not well understood. Lack of conservation of long non-coding RNAs and small sizes of microRNAs has been major obstacles in their phylogenetic analysis. In this study, we tried to shed more light on the evolution of ncRNA regulatory networks by changing our phylogenetic strategy to focus on the evolutionary pattern of their protein coding targets. We used available target databases of miRNAs and lncRNAs to find their protein coding targets in human. We were able to recognize evolutionary hallmarks of ncRNA targets by phylostratigraphic analysis. We found the conventional 3'-UTR and lesser known 5'-UTR targets of miRNAs to be enriched at three consecutive phylostrata. Firstly, in eukaryata phylostratum corresponding to the emergence of miRNAs, our study revealed that miRNA targets function primarily in cell cycle processes. Moreover, the same overrepresentation of the targets observed in the next two consecutive phylostrata, opisthokonta and eumetazoa, corresponded to the expansion periods of miRNAs in animals evolution. Coding sequence targets of miRNAs showed a delayed rise at opisthokonta phylostratum, compared to the 3' and 5' UTR targets of miRNAs. LncRNA regulatory network was the latest to evolve at eumetazoa.

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

OpenSoC Fabric

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

2014-08-21

Recent advancements in technology scaling have shown a trend towards greater integration with large-scale chips containing thousands of processors connected to memories and other I/O devices using non-trivial network topologies. Software simulation proves insufficient to study the tradeoffs in such complex systems due to slow execution time, whereas hardware RTL development is too time-consuming. We present OpenSoC Fabric, an on-chip network generation infrastructure which aims to provide a parameterizable and powerful on-chip network generator for evaluating future high performance computing architectures based on SoC technology. OpenSoC Fabric leverages a new hardware DSL, Chisel, which contains powerful abstractions provided by itsmore » base language, Scala, and generates both software (C++) and hardware (Verilog) models from a single code base. The OpenSoC Fabric2 infrastructure is modeled after existing state-of-the-art simulators, offers large and powerful collections of configuration options, and follows object-oriented design and functional programming to make functionality extension as easy as possible.« less

Recent research in network problems with applications

NASA Technical Reports Server (NTRS)

Thompson, G. L.

1980-01-01

The capabilities of network codes and their extensions are surveyed in regard to specially structured integer programming problems which are solved by using the solutions of a series of ordinary network problems.

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres

PubMed Central

Ince, Robin A. A.; Jaworska, Katarzyna; Gross, Joachim; Panzeri, Stefano; van Rijsbergen, Nicola J.; Rousselet, Guillaume A.; Schyns, Philippe G.

2016-01-01

A key to understanding visual cognition is to determine “where”, “when”, and “how” brain responses reflect the processing of the specific visual features that modulate categorization behavior—the “what”. The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event. Reverse-correlation methods coupled with information-theoretic analyses revealed that visibility of the eyes influences face detection behavior. The N170 initially reflects coding of the behaviorally relevant eye contralateral to the sensor, followed by a causal communication of the other eye from the other hemisphere. These findings demonstrate that the deceptively simple N170 ERP hides a complex network information processing mechanism involving initial coding and subsequent cross-hemispheric transfer of visual features. PMID:27550865

Evaluation of a new neutron energy spectrum unfolding code based on an Adaptive Neuro-Fuzzy Inference System (ANFIS).

PubMed

Hosseini, Seyed Abolfazl; Esmaili Paeen Afrakoti, Iman

2018-01-17

The purpose of the present study was to reconstruct the energy spectrum of a poly-energetic neutron source using an algorithm developed based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). ANFIS is a kind of artificial neural network based on the Takagi-Sugeno fuzzy inference system. The ANFIS algorithm uses the advantages of both fuzzy inference systems and artificial neural networks to improve the effectiveness of algorithms in various applications such as modeling, control and classification. The neutron pulse height distributions used as input data in the training procedure for the ANFIS algorithm were obtained from the simulations performed by MCNPX-ESUT computational code (MCNPX-Energy engineering of Sharif University of Technology). Taking into account the normalization condition of each energy spectrum, 4300 neutron energy spectra were generated randomly. (The value in each bin was generated randomly, and finally a normalization of each generated energy spectrum was performed). The randomly generated neutron energy spectra were considered as output data of the developed ANFIS computational code in the training step. To calculate the neutron energy spectrum using conventional methods, an inverse problem with an approximately singular response matrix (with the determinant of the matrix close to zero) should be solved. The solution of the inverse problem using the conventional methods unfold neutron energy spectrum with low accuracy. Application of the iterative algorithms in the solution of such a problem, or utilizing the intelligent algorithms (in which there is no need to solve the problem), is usually preferred for unfolding of the energy spectrum. Therefore, the main reason for development of intelligent algorithms like ANFIS for unfolding of neutron energy spectra is to avoid solving the inverse problem. In the present study, the unfolded neutron energy spectra of 252Cf and 241Am-9Be neutron sources using the developed computational code were found to have excellent agreement with the reference data. Also, the unfolded energy spectra of the neutron sources as obtained using ANFIS were more accurate than the results reported from calculations performed using artificial neural networks in previously published papers. © The Author(s) 2018. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Software for Brain Network Simulations: A Comparative Study

PubMed Central

Tikidji-Hamburyan, Ruben A.; Narayana, Vikram; Bozkus, Zeki; El-Ghazawi, Tarek A.

2017-01-01

Numerical simulations of brain networks are a critical part of our efforts in understanding brain functions under pathological and normal conditions. For several decades, the community has developed many software packages and simulators to accelerate research in computational neuroscience. In this article, we select the three most popular simulators, as determined by the number of models in the ModelDB database, such as NEURON, GENESIS, and BRIAN, and perform an independent evaluation of these simulators. In addition, we study NEST, one of the lead simulators of the Human Brain Project. First, we study them based on one of the most important characteristics, the range of supported models. Our investigation reveals that brain network simulators may be biased toward supporting a specific set of models. However, all simulators tend to expand the supported range of models by providing a universal environment for the computational study of individual neurons and brain networks. Next, our investigations on the characteristics of computational architecture and efficiency indicate that all simulators compile the most computationally intensive procedures into binary code, with the aim of maximizing their computational performance. However, not all simulators provide the simplest method for module development and/or guarantee efficient binary code. Third, a study of their amenability for high-performance computing reveals that NEST can almost transparently map an existing model on a cluster or multicore computer, while NEURON requires code modification if the model developed for a single computer has to be mapped on a computational cluster. Interestingly, parallelization is the weakest characteristic of BRIAN, which provides no support for cluster computations and limited support for multicore computers. Fourth, we identify the level of user support and frequency of usage for all simulators. Finally, we carry out an evaluation using two case studies: a large network with simplified neural and synaptic models and a small network with detailed models. These two case studies allow us to avoid any bias toward a particular software package. The results indicate that BRIAN provides the most concise language for both cases considered. Furthermore, as expected, NEST mostly favors large network models, while NEURON is better suited for detailed models. Overall, the case studies reinforce our general observation that simulators have a bias in the computational performance toward specific types of the brain network models. PMID:28775687

Application of Mobile Router to Military Communications

NASA Technical Reports Server (NTRS)

Stewart, David H.; Ivancic, William D.; Bell, Terry L.; Kachmar, Brian A.; Shell, Dan; Leung, Kent

2002-01-01

Cisco Systems and NASA Glenn Research Center under a NASA Space Act Agreement have been performing joint networking research to apply Internet technologies and protocols to space-based communications. During this time, Cisco Systems developed the mobile-router which NASA and Cisco jointly tested. The early field trials of this technology have been successfully completed. The mobile-router is software code that resides in a network router. A Mobile-Router allows entire networks to roam while maintaining connectivity to the Internet. This router code is pertinent to a myriad of applications for both the government and commercial sectors. This technology will be applied to the wireless battlefield. NASA and the Department of Defense will utilize this technology for near-planetary observation and sensing spacecraft. It is the enabling technology for communication via the Internet or Intranets to aircraft. Information such as weather, air traffic control, voice and video can be easily and inexpensively transmitted to the aircraft using Internet protocols. The mobile router can be incorporated into emergency vehicles particularly ambulances and life-flight aircraft to provide real-time connectivity back to the hospital and healthcare experts. Commercial applications include entertainment services, IP telephone, and Internet connectivity for cruise ships, commercial shipping, tour busses, aircraft, and eventually cars. This paper will briefly describe the mobile router operation. An upcoming wide area network field test with application to US Coast Guard communications will be described. The paper will also highlight military and government networks that will benefit from the deployment of mobile router and the associated applications.

The Spanish national health care-associated infection surveillance network (INCLIMECC): data summary January 1997 through December 2006 adapted to the new National Healthcare Safety Network Procedure-associated module codes.

PubMed

Pérez, Cristina Díaz-Agero; Rodela, Ana Robustillo; Monge Jodrá, Vincente

2009-12-01

In 1997, a national standardized surveillance system (designated INCLIMECC [Indicadores Clínicos de Mejora Continua de la Calidad]) was established in Spain for health care-associated infection (HAI) in surgery patients, based on the National Nosocomial Infection Surveillance (NNIS) system. In 2005, in its procedure-associated module, the National Healthcare Safety Network (NHSN) inherited the NNIS program for surveillance of HAI in surgery patients and reorganized all surgical procedures. INCLIMECC actively monitors all patients referred to the surgical ward of each participating hospital. We present a summary of the data collected from January 1997 to December 2006 adapted to the new NHSN procedures. Surgical site infection (SSI) rates are provided by operative procedure and NNIS risk index category. Further quality indicators reported are surgical complications, length of stay, antimicrobial prophylaxis, mortality, readmission because of infection or other complication, and revision surgery. Because the ICD-9-CM surgery procedure code is included in each patient's record, we were able to reorganize our database avoiding the loss of extensive information, as has occurred with other systems.

Case Presentations Demonstrating Periodontal Treatment Variation: PEARL Network.

PubMed

Curro, Frederick A; Grill, Ashley C; Matthews, Abigail G; Martin, John; Kalenderian, Elisabeth; Craig, Ronald G; Naftolin, Frederick; Thompson, Van P

2015-06-01

Variation in periodontal terminology can affect the diagnosis and treatment plan as assessed by practicing general dentists in the Practitioners Engaged in Applied Research and Learning (PEARL) Network. General dentists participating in the PEARL Network are highly screened, credentialed, and qualified and may not be representative of the general population of dentists. Ten randomized case presentations ranging from periodontal health to gingivitis, to mild, moderate, and severe periodontitis were randomly presented to respondents. Descriptive comparisons were made between these diagnosis groups in terms of the treatment recommendations following diagnosis. PEARL practitioners assessing periodontal clinical scenarios were found to either over- or under-diagnose the case presentations, which affected treatment planning, while the remaining responses concurred with respect to the diagnosis. The predominant diagnosis was compared with that assigned by two practicing periodontists. There was variation in treatment based on the diagnosis for gingivitis and the lesser forms of periodontitis. Data suggests that a lack of clarity of periodontal terminology affects both diagnosis and treatment planning, and terminology may be improved by having diagnosis codes, which could be used to assess treatment outcomes. This article provides data to support best practice for the use of diagnosis coding and integration of dentistry with medicine using ICD-10 terminology.

lpNet: a linear programming approach to reconstruct signal transduction networks.

PubMed

Matos, Marta R A; Knapp, Bettina; Kaderali, Lars

2015-10-01

With the widespread availability of high-throughput experimental technologies it has become possible to study hundreds to thousands of cellular factors simultaneously, such as coding- or non-coding mRNA or protein concentrations. Still, extracting information about the underlying regulatory or signaling interactions from these data remains a difficult challenge. We present a flexible approach towards network inference based on linear programming. Our method reconstructs the interactions of factors from a combination of perturbation/non-perturbation and steady-state/time-series data. We show both on simulated and real data that our methods are able to reconstruct the underlying networks fast and efficiently, thus shedding new light on biological processes and, in particular, into disease's mechanisms of action. We have implemented the approach as an R package available through bioconductor. This R package is freely available under the Gnu Public License (GPL-3) from bioconductor.org (http://bioconductor.org/packages/release/bioc/html/lpNet.html) and is compatible with most operating systems (Windows, Linux, Mac OS) and hardware architectures. bettina.knapp@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network.

PubMed

Han, Changcai; Yang, Jinsheng

2017-10-30

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes.

Multi-Source Cooperative Data Collection with a Mobile Sink for the Wireless Sensor Network

PubMed Central

Han, Changcai; Yang, Jinsheng

2017-01-01

The multi-source cooperation integrating distributed low-density parity-check codes is investigated to jointly collect data from multiple sensor nodes to the mobile sink in the wireless sensor network. The one-round and two-round cooperative data collection schemes are proposed according to the moving trajectories of the sink node. Specifically, two sparse cooperation models are firstly formed based on geographical locations of sensor source nodes, the impairment of inter-node wireless channels and moving trajectories of the mobile sink. Then, distributed low-density parity-check codes are devised to match the directed graphs and cooperation matrices related with the cooperation models. In the proposed schemes, each source node has quite low complexity attributed to the sparse cooperation and the distributed processing. Simulation results reveal that the proposed cooperative data collection schemes obtain significant bit error rate performance and the two-round cooperation exhibits better performance compared with the one-round scheme. The performance can be further improved when more source nodes participate in the sparse cooperation. For the two-round data collection schemes, the performance is evaluated for the wireless sensor networks with different moving trajectories and the variant data sizes. PMID:29084155

Fast computation of quadrupole and hexadecapole approximations in microlensing with a single point-source evaluation

NASA Astrophysics Data System (ADS)

Cassan, Arnaud

2017-07-01

The exoplanet detection rate from gravitational microlensing has grown significantly in recent years thanks to a great enhancement of resources and improved observational strategy. Current observatories include ground-based wide-field and/or robotic world-wide networks of telescopes, as well as space-based observatories such as satellites Spitzer or Kepler/K2. This results in a large quantity of data to be processed and analysed, which is a challenge for modelling codes because of the complexity of the parameter space to be explored and the intensive computations required to evaluate the models. In this work, I present a method that allows to compute the quadrupole and hexadecapole approximations of the finite-source magnification with more efficiency than previously available codes, with routines about six times and four times faster, respectively. The quadrupole takes just about twice the time of a point-source evaluation, which advocates for generalizing its use to large portions of the light curves. The corresponding routines are available as open-source python codes.

Optimizing Distribution of Pandemic Influenza Antiviral Drugs

PubMed Central

Huang, Hsin-Chan; Morton, David P.; Johnson, Gregory P.; Gutfraind, Alexander; Galvani, Alison P.; Clements, Bruce; Meyers, Lauren A.

2015-01-01

We provide a data-driven method for optimizing pharmacy-based distribution of antiviral drugs during an influenza pandemic in terms of overall access for a target population and apply it to the state of Texas, USA. We found that during the 2009 influenza pandemic, the Texas Department of State Health Services achieved an estimated statewide access of 88% (proportion of population willing to travel to the nearest dispensing point). However, access reached only 34.5% of US postal code (ZIP code) areas containing <1,000 underinsured persons. Optimized distribution networks increased expected access to 91% overall and 60% in hard-to-reach regions, and 2 or 3 major pharmacy chains achieved near maximal coverage in well-populated areas. Independent pharmacies were essential for reaching ZIP code areas containing <1,000 underinsured persons. This model was developed during a collaboration between academic researchers and public health officials and is available as a decision support tool for Texas Department of State Health Services at a Web-based interface. PMID:25625858

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.

PubMed

Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

2017-01-01

The recent "deep learning revolution" in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding

PubMed Central

Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

2017-01-01

The recent “deep learning revolution” in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems. PMID:28377709

Biographer: web-based editing and rendering of SBGN compliant biochemical networks.

PubMed

Krause, Falko; Schulz, Marvin; Ripkens, Ben; Flöttmann, Max; Krantz, Marcus; Klipp, Edda; Handorf, Thomas

2013-06-01

The rapid accumulation of knowledge in the field of Systems Biology during the past years requires advanced, but simple-to-use, methods for the visualization of information in a structured and easily comprehensible manner. We have developed biographer, a web-based renderer and editor for reaction networks, which can be integrated as a library into tools dealing with network-related information. Our software enables visualizations based on the emerging standard Systems Biology Graphical Notation. It is able to import networks encoded in various formats such as SBML, SBGN-ML and jSBGN, a custom lightweight exchange format. The core package is implemented in HTML5, CSS and JavaScript and can be used within any kind of web-based project. It features interactive graph-editing tools and automatic graph layout algorithms. In addition, we provide a standalone graph editor and a web server, which contains enhanced features like web services for the import and export of models and visualizations in different formats. The biographer tool can be used at and downloaded from the web page http://biographer.biologie.hu-berlin.de/. The different software packages, including a server-independent version as well as a web server for Windows and Linux based systems, are available at http://code.google.com/p/biographer/ under the open-source license LGPL

Stakeholders perspectives on the key components of community-based interventions coordinating care in dementia: a qualitative systematic review.

PubMed

Backhouse, Amy; Richards, David A; McCabe, Rose; Watkins, Ross; Dickens, Chris

2017-11-22

Interventions aiming to coordinate services for the community-based dementia population vary in components, organisation and implementation. In this review we aimed to investigate the views of stakeholders on the key components of community-based interventions coordinating care in dementia. We searched four databases from inception to June 2015; Medline, The Cochrane Library, EMBASE and PsycINFO, this was aided by a search of four grey literature databases, and backward and forward citation tracking of included papers. Title and abstract screening was followed by a full text screen by two independent reviewers, and quality was assessed using the CASP appraisal tool. We then conducted thematic synthesis on extracted data. A total of seven papers from five independent studies were included in the review, and encompassed the views of over 100 participants from three countries. Through thematic synthesis we identified 32 initial codes that were grouped into 5 second-order themes: (1) case manager had four associated codes and described preferences for the case manager personal and professional attributes, including a sound knowledge in dementia and availability of local services; (2) communication had five associated codes and emphasized the importance stakeholders placed on multichannel communication with service users, as well as between multidisciplinary teams and across organisations; (3) intervention had 11 associated codes which focused primarily on the practicalities of implementation such as the contact type and frequency between case managers and service users, and the importance of case manager training and service evaluation; (4) resources had five associated codes which outlined stakeholder views on the required resources for coordinating interventions and potential overlap with existing resources, as well as arising issues when available resources do not meet those required for successful implementation; and (5) support had seven associated codes that reflect the importance that was placed on the support network around the case manager and the investment of professionals involved directly in care as well as the wider professional network. The synthesis of relevant qualitative studies has shown how various stakeholder groups considered dementia care coordination interventions to be acceptable, useful and appropriate for dementia care, and have clear preferences for components, implementation methods and settings of these interventions. By incorporating stakeholders' perspectives and preferences when planning and developing coordinating interventions we may increase the likelihood of successful implementation and patient benefits.

Cross-layer model design in wireless ad hoc networks for the Internet of Things.

PubMed

Yang, Xin; Wang, Ling; Xie, Jian; Zhang, Zhaolin

2018-01-01

Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods.

Cross-layer model design in wireless ad hoc networks for the Internet of Things

PubMed Central

Wang, Ling; Xie, Jian; Zhang, Zhaolin

2018-01-01

Wireless ad hoc networks can experience extreme fluctuations in transmission traffic in the Internet of Things, which is widely used today. Currently, the most crucial issues requiring attention for wireless ad hoc networks are making the best use of low traffic periods, reducing congestion during high traffic periods, and improving transmission performance. To solve these problems, the present paper proposes a novel cross-layer transmission model based on decentralized coded caching in the physical layer and a content division multiplexing scheme in the media access control layer. Simulation results demonstrate that the proposed model effectively addresses these issues by substantially increasing the throughput and successful transmission rate compared to existing protocols without a negative influence on delay, particularly for large scale networks under conditions of highly contrasting high and low traffic periods. PMID:29734355

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

PubMed

Bush, Daniel; Philippides, Andrew; Husbands, Phil; O'Shea, Michael

2010-07-01

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.

Improvement of signal to noise ratio of time domain mutliplexing fiber Bragg grating sensor network with Golay complementary codes

NASA Astrophysics Data System (ADS)

Elgaud, M. M.; Zan, M. S. D.; Abushagur, A. G.; Bakar, A. Ashrif A.

2017-07-01

This paper reports the employment of autocorrelation properties of Golay complementary codes (GCC) to enhance the performance of the time domain multiplexing fiber Bragg grating (TDM-FBG) sensing network. By encoding the light from laser with a stream of non-return-to-zero (NRZ) form of GCC and launching it into the sensing area that consists of the FBG sensors, we have found that the FBG signals can be decoded correctly with the autocorrelation calculations, confirming the successful demonstration of coded TDM-FBG sensor network. OptiGrating and OptiSystem simulators were used to design customized FBG sensors and perform the coded TDM-FBG sensor simulations, respectively. Results have substantiated the theoretical dependence of SNR enhancement on the code length of GCC, where the maximum SNR improvement of about 9 dB is achievable with the use of 256 bits of GCC compared to that of 4 bits case. Furthermore, the GCC has also extended the strain exposure up to 30% higher compared to the maximum of the conventional single pulse case. The employment of GCC in the TDM-FBG sensor system provides overall performance enhancement over the conventional single pulse case, under the same conditions.

Leveraging hospital big data to monitor flu epidemics.

PubMed

Bouzillé, Guillaume; Poirier, Canelle; Campillo-Gimenez, Boris; Aubert, Marie-Laure; Chabot, Mélanie; Chazard, Emmanuel; Lavenu, Audrey; Cuggia, Marc

2018-02-01

Influenza epidemics are a major public health concern and require a costly and time-consuming surveillance system at different geographical scales. The main challenge is being able to predict epidemics. Besides traditional surveillance systems, such as the French Sentinel network, several studies proposed prediction models based on internet-user activity. Here, we assessed the potential of hospital big data to monitor influenza epidemics. We used the clinical data warehouse of the Academic Hospital of Rennes (France) and then built different queries to retrieve relevant information from electronic health records to gather weekly influenza-like illness activity. We found that the query most highly correlated with Sentinel network estimates was based on emergency reports concerning discharged patients with a final diagnosis of influenza (Pearson's correlation coefficient (PCC) of 0.931). The other tested queries were based on structured data (ICD-10 codes of influenza in Diagnosis-related Groups, and influenza PCR tests) and performed best (PCC of 0.981 and 0.953, respectively) during the flu season 2014-15. This suggests that both ICD-10 codes and PCR results are associated with severe epidemics. Finally, our approach allowed us to obtain additional patients' characteristics, such as the sex ratio or age groups, comparable with those from the Sentinel network. Conclusions: Hospital big data seem to have a great potential for monitoring influenza epidemics in near real-time. Such a method could constitute a complementary tool to standard surveillance systems by providing additional characteristics on the concerned population or by providing information earlier. This system could also be easily extended to other diseases with possible activity changes. Additional work is needed to assess the real efficacy of predictive models based on hospital big data to predict flu epidemics. Copyright © 2017 Elsevier B.V. All rights reserved.

RuleMonkey: software for stochastic simulation of rule-based models

PubMed Central

2010-01-01

Background The system-level dynamics of many molecular interactions, particularly protein-protein interactions, can be conveniently represented using reaction rules, which can be specified using model-specification languages, such as the BioNetGen language (BNGL). A set of rules implicitly defines a (bio)chemical reaction network. The reaction network implied by a set of rules is often very large, and as a result, generation of the network implied by rules tends to be computationally expensive. Moreover, the cost of many commonly used methods for simulating network dynamics is a function of network size. Together these factors have limited application of the rule-based modeling approach. Recently, several methods for simulating rule-based models have been developed that avoid the expensive step of network generation. The cost of these "network-free" simulation methods is independent of the number of reactions implied by rules. Software implementing such methods is now needed for the simulation and analysis of rule-based models of biochemical systems. Results Here, we present a software tool called RuleMonkey, which implements a network-free method for simulation of rule-based models that is similar to Gillespie's method. The method is suitable for rule-based models that can be encoded in BNGL, including models with rules that have global application conditions, such as rules for intramolecular association reactions. In addition, the method is rejection free, unlike other network-free methods that introduce null events, i.e., steps in the simulation procedure that do not change the state of the reaction system being simulated. We verify that RuleMonkey produces correct simulation results, and we compare its performance against DYNSTOC, another BNGL-compliant tool for network-free simulation of rule-based models. We also compare RuleMonkey against problem-specific codes implementing network-free simulation methods. Conclusions RuleMonkey enables the simulation of rule-based models for which the underlying reaction networks are large. It is typically faster than DYNSTOC for benchmark problems that we have examined. RuleMonkey is freely available as a stand-alone application http://public.tgen.org/rulemonkey. It is also available as a simulation engine within GetBonNie, a web-based environment for building, analyzing and sharing rule-based models. PMID:20673321

Network effects across the earnings distribution: payoffs to visible and invisible job finding assistance.

PubMed

McDonald, Steve

2015-01-01

This study makes three critical contributions to the "Do Contacts Matter?" debate. First, the widely reported null relationship between informal job searching and wages is shown to be mostly the artifact of a coding error and sample selection restrictions. Second, previous analyses examined only active informal job searching without fully considering the benefits derived from unsolicited network assistance (the "invisible hand of social capital") - thereby underestimating the network effect. Third, wage returns to networks are examined across the earnings distribution. Longitudinal data from the NLSY reveal significant wage returns for network-based job finding over formal job searching, especially for individuals who were informally recruited into their jobs (non-searchers). Fixed effects quantile regression analyses show that contacts generate wage premiums among middle and high wage jobs, but not low wage jobs. These findings challenge conventional wisdom on contact effects and advance understanding of how social networks affect wage attainment and inequality. Copyright © 2014 Elsevier Inc. All rights reserved.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

PubMed

Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S

2015-10-30

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Quantum Graphical Models and Belief Propagation

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

Leifer, M.S.; Perimeter Institute for Theoretical Physics, 31 Caroline Street North, Waterloo Ont., N2L 2Y5; Poulin, D.

Belief Propagation algorithms acting on Graphical Models of classical probability distributions, such as Markov Networks, Factor Graphs and Bayesian Networks, are amongst the most powerful known methods for deriving probabilistic inferences amongst large numbers of random variables. This paper presents a generalization of these concepts and methods to the quantum case, based on the idea that quantum theory can be thought of as a noncommutative, operator-valued, generalization of classical probability theory. Some novel characterizations of quantum conditional independence are derived, and definitions of Quantum n-Bifactor Networks, Markov Networks, Factor Graphs and Bayesian Networks are proposed. The structure of Quantum Markovmore » Networks is investigated and some partial characterization results are obtained, along the lines of the Hammersley-Clifford theorem. A Quantum Belief Propagation algorithm is presented and is shown to converge on 1-Bifactor Networks and Markov Networks when the underlying graph is a tree. The use of Quantum Belief Propagation as a heuristic algorithm in cases where it is not known to converge is discussed. Applications to decoding quantum error correcting codes and to the simulation of many-body quantum systems are described.« less

The effect of an exogenous magnetic field on neural coding in deep spiking neural networks.

PubMed

Guo, Lei; Zhang, Wei; Zhang, Jialei

2018-01-01

A ten-layer feed forward network is constructed in the presence of an exogenous alternating magnetic field. Specifically, our results indicate that for rate coding, the firing rate is significantly increased in the presence of an exogenous alternating magnetic field and particularly with increasing enhancement of the alternating magnetic field amplitude. For temporal coding, the interspike intervals of the spiking sequence are decreased and the distribution of the interspike intervals of the spiking sequence tends to be uniform in the presence of alternating magnetic field.

Reinforce: An Ensemble Approach for Inferring PPI Network from AP-MS Data.

PubMed

Tian, Bo; Duan, Qiong; Zhao, Can; Teng, Ben; He, Zengyou

2017-05-17

Affinity Purification-Mass Spectrometry (AP-MS) is one of the most important technologies for constructing protein-protein interaction (PPI) networks. In this paper, we propose an ensemble method, Reinforce, for inferring PPI network from AP-MS data set. The new algorithm named Reinforce is based on rank aggregation and false discovery rate control. Under the null hypothesis that the interaction scores from different scoring methods are randomly generated, Reinforce follows three steps to integrate multiple ranking results from different algorithms or different data sets. The experimental results show that Reinforce can get more stable and accurate inference results than existing algorithms. The source codes of Reinforce and data sets used in the experiments are available at: https://sourceforge.net/projects/reinforce/.

Android Platform Based Smartphones for a Logistical Remote Association Repair Framework

PubMed Central

Lien, Shao-Fan; Wang, Chun-Chieh; Su, Juhng-Perng; Chen, Hong-Ming; Wu, Chein-Hsing

2014-01-01

The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use. PMID:24967603

Deconvolution using a neural network

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

Lehman, S.K.

1990-11-15

Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.

Method and system for pattern analysis using a coarse-coded neural network

NASA Technical Reports Server (NTRS)

Spirkovska, Liljana (Inventor); Reid, Max B. (Inventor)

1994-01-01

A method and system for performing pattern analysis with a neural network coarse-coding a pattern to be analyzed so as to form a plurality of sub-patterns collectively defined by data. Each of the sub-patterns comprises sets of pattern data. The neural network includes a plurality fields, each field being associated with one of the sub-patterns so as to receive the sub-pattern data therefrom. Training and testing by the neural network then proceeds in the usual way, with one modification: the transfer function thresholds the value obtained from summing the weighted products of each field over all sub-patterns associated with each pattern being analyzed by the system.

Improvement of single wavelength-based Thai jasmine rice identification with elliptic Fourier descriptor and neural network analysis

NASA Astrophysics Data System (ADS)

Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

2012-11-01

Instead of considering only the amount of fluorescent signal spatially distributed on the image of milled rice grains this paper shows how our single-wavelength spectral-imaging-based Thai jasmine (KDML105) rice identification system can be improved by analyzing the shape and size of the image of each milled rice variety especially during the image threshold operation. The image of each milled rice variety is expressed as chain codes and elliptic Fourier coefficients. After that, a feed-forward back-propagation neural network model is applied, resulting in an improved average FAR of 11.0% and FRR of 19.0% in identifying KDML105 milled rice from the unwanted four milled rice varieties.

Design of pseudorandom binary sequence generator using lithium-niobate-based Mach-Zehnder interferometers

NASA Astrophysics Data System (ADS)

Choudhary, Kuldeep; Kumar, Santosh

2017-05-01

The application of electro-optic effect in lithium-niobate-based Mach-Zehnder interferometer to design a 3-bit optical pseudorandom binary sequence (PRBS) generator has been proposed, which is characterized by its simplicity of generation and stability. The proposed device is optoelectronic in nature. The PBRS generator is immensely applicable for pattern generation, encryption, and coding applications in optical networks. The study is carried out by simulating the proposed device with beam propagation method.

Long-Term Durability and Integrity of Built-In Piezoelectric-Based Active Sensing Network in Structures

DTIC Science & Technology

2007-03-31

iterating to the end-time step. 1.3 Code Verification 1.3.1 Statement of the Problem A square aluminum alloy plate (thickness = 1.02 mm, width and...plate. The electro-mechanical properties of the piezoelectric materials (APC850) are available from American Piezoceramics, Inc. . The piezoceramic...structural usage and provide an early indication of physical damage. Piezoelectric (PZT) based SHM systems are among the most widely used for active and

Single neuron firing properties impact correlation-based population coding

PubMed Central

Hong, Sungho; Ratté, Stéphanie; Prescott, Steven A.; De Schutter, Erik

2012-01-01

Correlated spiking has been widely observed but its impact on neural coding remains controversial. Correlation arising from co-modulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate co-modulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: “ideal” integrators (with spike generation sensitive to stimulus mean) exhibit rate co-modulation whereas “ideal” coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate co-modulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons. PMID:22279226

The transfer and transformation of collective network information in gene-matched networks.

PubMed

Kitsukawa, Takashi; Yagi, Takeshi

2015-10-09

Networks, such as the human society network, social and professional networks, and biological system networks, contain vast amounts of information. Information signals in networks are distributed over nodes and transmitted through intricately wired links, making the transfer and transformation of such information difficult to follow. Here we introduce a novel method for describing network information and its transfer using a model network, the Gene-matched network (GMN), in which nodes (neurons) possess attributes (genes). In the GMN, nodes are connected according to their expression of common genes. Because neurons have multiple genes, the GMN is cluster-rich. We show that, in the GMN, information transfer and transformation were controlled systematically, according to the activity level of the network. Furthermore, information transfer and transformation could be traced numerically with a vector using genes expressed in the activated neurons, the active-gene array, which was used to assess the relative activity among overlapping neuronal groups. Interestingly, this coding style closely resembles the cell-assembly neural coding theory. The method introduced here could be applied to many real-world networks, since many systems, including human society and various biological systems, can be represented as a network of this type.