Adversaries in Networks

DTIC Science & Technology

2010-08-01

between east and west. In 330 AD, the emperor Constantine I moved the capital of the eastern part to Byzantium, and renamed the city Constantinople . In...Byzantium was renamed. Long after the empire collapsed after Constantinople fell to the Ottomans in 1453, the Byzantine Empire became known for being...It was shown in [19] that standard network coding problems fall into three categories: (1) coding is un- necessary, and routing is enough to achieve

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.

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.

A mean field neural network for hierarchical module placement

NASA Technical Reports Server (NTRS)

Unaltuna, M. Kemal; Pitchumani, Vijay

1992-01-01

This paper proposes a mean field neural network for the two-dimensional module placement problem. An efficient coding scheme with only O(N log N) neurons is employed where N is the number of modules. The neurons are evolved in groups of N in log N iteration steps such that the circuit is recursively partitioned in alternating vertical and horizontal directions. In our simulations, the network was able to find optimal solutions to all test problems with up to 128 modules.

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.

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

Neural networks for vertical microcode compaction

NASA Astrophysics Data System (ADS)

Chu, Pong P.

1992-09-01

Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional computer, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use the neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP- complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an `energy function' and map it to a two-layer fully connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

User's manual for a two-dimensional, ground-water flow code on the Octopus computer network

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

Naymik, T.G.

1978-08-30

A ground-water hydrology computer code, programmed by R.L. Taylor (in Proc. American Society of Civil Engineers, Journal of Hydraulics Division, 93(HY2), pp. 25-33 (1967)), has been adapted to the Octopus computer system at Lawrence Livermore Laboratory. Using an example problem, this manual details the input, output, and execution options of the code.

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.

Modeling and Simulation with INS.

ERIC Educational Resources Information Center

Roberts, Stephen D.; And Others

INS, the Integrated Network Simulation language, puts simulation modeling into a network framework and automatically performs such programming activities as placing the problem into a next event structure, coding events, collecting statistics, monitoring status, and formatting reports. To do this, INS provides a set of symbols (nodes and branches)…

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

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

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

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.

Surveying multidisciplinary aspects in real-time distributed coding for Wireless Sensor Networks.

PubMed

Braccini, Carlo; Davoli, Franco; Marchese, Mario; Mongelli, Maurizio

2015-01-27

Wireless Sensor Networks (WSNs), where a multiplicity of sensors observe a physical phenomenon and transmit their measurements to one or more sinks, pertain to the class of multi-terminal source and channel coding problems of Information Theory. In this category, "real-time" coding is often encountered for WSNs, referring to the problem of finding the minimum distortion (according to a given measure), under transmission power constraints, attainable by encoding and decoding functions, with stringent limits on delay and complexity. On the other hand, the Decision Theory approach seeks to determine the optimal coding/decoding strategies or some of their structural properties. Since encoder(s) and decoder(s) possess different information, though sharing a common goal, the setting here is that of Team Decision Theory. A more pragmatic vision rooted in Signal Processing consists of fixing the form of the coding strategies (e.g., to linear functions) and, consequently, finding the corresponding optimal decoding strategies and the achievable distortion, generally by applying parametric optimization techniques. All approaches have a long history of past investigations and recent results. The goal of the present paper is to provide the taxonomy of the various formulations, a survey of the vast related literature, examples from the authors' own research, and some highlights on the inter-play of the different theories.

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.

An edge preserving differential image coding scheme

NASA Technical Reports Server (NTRS)

Rost, Martin C.; Sayood, Khalid

1992-01-01

Differential encoding techniques are fast and easy to implement. However, a major problem with the use of differential encoding for images is the rapid edge degradation encountered when using such systems. This makes differential encoding techniques of limited utility, especially when coding medical or scientific images, where edge preservation is of utmost importance. A simple, easy to implement differential image coding system with excellent edge preservation properties is presented. The coding system can be used over variable rate channels, which makes it especially attractive for use in the packet network environment.

Relay selection in energy harvesting cooperative networks with rateless codes

NASA Astrophysics Data System (ADS)

Zhu, Kaiyan; Wang, Fei

2018-04-01

This paper investigates the relay selection in energy harvesting cooperative networks, where the relays harvests energy from the radio frequency (RF) signals transmitted by a source, and the optimal relay is selected and uses the harvested energy to assist the information transmission from the source to its destination. Both source and the selected relay transmit information using rateless code, which allows the destination recover original information after collecting codes bits marginally surpass the entropy of original information. In order to improve transmission performance and efficiently utilize the harvested power, the optimal relay is selected. The optimization problem are formulated to maximize the achievable information rates of the system. Simulation results demonstrate that our proposed relay selection scheme outperform other strategies.

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.

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.

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.

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.

Coarse-coded higher-order neural networks for PSRI object recognition. [position, scale, and rotation invariant

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly; Reid, Max B.

1993-01-01

A higher-order neural network (HONN) can be designed to be invariant to changes in scale, translation, and inplane rotation. Invariances are built directly into the architecture of a HONN and do not need to be learned. Consequently, fewer training passes and a smaller training set are required to learn to distinguish between objects. The size of the input field is limited, however, because of the memory required for the large number of interconnections in a fully connected HONN. By coarse coding the input image, the input field size can be increased to allow the larger input scenes required for practical object recognition problems. We describe a coarse coding technique and present simulation results illustrating its usefulness and its limitations. Our simulations show that a third-order neural network can be trained to distinguish between two objects in a 4096 x 4096 pixel input field independent of transformations in translation, in-plane rotation, and scale in less than ten passes through the training set. Furthermore, we empirically determine the limits of the coarse coding technique in the object recognition domain.

NetCoffee: a fast and accurate global alignment approach to identify functionally conserved proteins in multiple networks.

PubMed

Hu, Jialu; Kehr, Birte; Reinert, Knut

2014-02-15

Owing to recent advancements in high-throughput technologies, protein-protein interaction networks of more and more species become available in public databases. The question of how to identify functionally conserved proteins across species attracts a lot of attention in computational biology. Network alignments provide a systematic way to solve this problem. However, most existing alignment tools encounter limitations in tackling this problem. Therefore, the demand for faster and more efficient alignment tools is growing. We present a fast and accurate algorithm, NetCoffee, which allows to find a global alignment of multiple protein-protein interaction networks. NetCoffee searches for a global alignment by maximizing a target function using simulated annealing on a set of weighted bipartite graphs that are constructed using a triplet approach similar to T-Coffee. To assess its performance, NetCoffee was applied to four real datasets. Our results suggest that NetCoffee remedies several limitations of previous algorithms, outperforms all existing alignment tools in terms of speed and nevertheless identifies biologically meaningful alignments. The source code and data are freely available for download under the GNU GPL v3 license at https://code.google.com/p/netcoffee/.

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

PubMed Central

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

Decoding communities in networks

NASA Astrophysics Data System (ADS)

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Decoding communities in networks.

PubMed

Radicchi, Filippo

2018-02-01

According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.

Steady state analysis of Boolean molecular network models via model reduction and computational algebra.

PubMed

Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard

2014-06-26

A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem.

Steady state analysis of Boolean molecular network models via model reduction and computational algebra

PubMed Central

2014-01-01

Background A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. Results This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. Conclusions The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for large Boolean networks with high average connectivity remains an open problem. PMID:24965213

Perfect quantum multiple-unicast network coding protocol

NASA Astrophysics Data System (ADS)

Li, Dan-Dan; Gao, Fei; Qin, Su-Juan; Wen, Qiao-Yan

2018-01-01

In order to realize long-distance and large-scale quantum communication, it is natural to utilize quantum repeater. For a general quantum multiple-unicast network, it is still puzzling how to complete communication tasks perfectly with less resources such as registers. In this paper, we solve this problem. By applying quantum repeaters to multiple-unicast communication problem, we give encoding-decoding schemes for source nodes, internal ones and target ones, respectively. Source-target nodes share EPR pairs by using our encoding-decoding schemes over quantum multiple-unicast network. Furthermore, quantum communication can be accomplished perfectly via teleportation. Compared with existed schemes, our schemes can reduce resource consumption and realize long-distance transmission of quantum information.

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACINTOSH VERSION)

NASA Technical Reports Server (NTRS)

Phillips, T. A.

1994-01-01

NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS allows the user to generate C code to implement the network loaded into the system. This permits the placement of networks as components, or subroutines, in other systems. In short, once a network performs satisfactorily, the Generate C Code option provides the means for creating a program separate from NETS to run the network. Other features: files may be stored in binary or ASCII format; multiple input propagation is permitted; bias values may be included; capability to scale data without writing scaling code; quick interactive testing of network from the main menu; and several options that allow the user to manipulate learning efficiency. NETS is written in ANSI standard C language to be machine independent. The Macintosh version (MSC-22108) includes code for both a graphical user interface version and a command line interface version. The machine independent version (MSC-21588) only includes code for the command line interface version of NETS 3.0. The Macintosh version requires a Macintosh II series computer and has been successfully implemented under System 7. Four executables are included on these diskettes, two for floating point operations and two for integer arithmetic. It requires Think C 5.0 to compile. A minimum of 1Mb of RAM is required for execution. Sample input files and executables for both the command line version and the Macintosh user interface version are provided on the distribution medium. The Macintosh version is available on a set of three 3.5 inch 800K Macintosh format diskettes. The machine independent version has been successfully implemented on an IBM PC series compatible running MS-DOS, a DEC VAX running VMS, a SunIPC running SunOS, and a CRAY Y-MP running UNICOS. Two executables for the IBM PC version are included on the MS-DOS distribution media, one compiled for floating point operations and one for integer arithmetic. The machine independent version is available on a set of three 5.25 inch 360K MS-DOS format diskettes (standard distribution medium) or a .25 inch streaming magnetic tape cartridge in UNIX tar format. NETS was developed in 1989 and updated in 1992. IBM PC is a registered trademark of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation. DEC, VAX, and VMS are trademarks of Digital Equipment Corporation. SunIPC and SunOS are trademarks of Sun Microsystems, Inc. CRAY Y-MP and UNICOS are trademarks of Cray Research, Inc.

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACHINE INDEPENDENT VERSION)

NASA Technical Reports Server (NTRS)

Baffes, P. T.

1994-01-01

NETS, A Tool for the Development and Evaluation of Neural Networks, provides a simulation of Neural Network algorithms plus an environment for developing such algorithms. Neural Networks are a class of systems modeled after the human brain. Artificial Neural Networks are formed from hundreds or thousands of simulated neurons, connected to each other in a manner similar to brain neurons. Problems which involve pattern matching readily fit the class of problems which NETS is designed to solve. NETS uses the back propagation learning method for all of the networks which it creates. The nodes of a network are usually grouped together into clumps called layers. Generally, a network will have an input layer through which the various environment stimuli are presented to the network, and an output layer for determining the network's response. The number of nodes in these two layers is usually tied to some features of the problem being solved. Other layers, which form intermediate stops between the input and output layers, are called hidden layers. NETS allows the user to customize the patterns of connections between layers of a network. NETS also provides features for saving the weight values of a network during the learning process, which allows for more precise control over the learning process. NETS is an interpreter. Its method of execution is the familiar "read-evaluate-print" loop found in interpreted languages such as BASIC and LISP. The user is presented with a prompt which is the simulator's way of asking for input. After a command is issued, NETS will attempt to evaluate the command, which may produce more prompts requesting specific information or an error if the command is not understood. The typical process involved when using NETS consists of translating the problem into a format which uses input/output pairs, designing a network configuration for the problem, and finally training the network with input/output pairs until an acceptable error is reached. NETS allows the user to generate C code to implement the network loaded into the system. This permits the placement of networks as components, or subroutines, in other systems. In short, once a network performs satisfactorily, the Generate C Code option provides the means for creating a program separate from NETS to run the network. Other features: files may be stored in binary or ASCII format; multiple input propagation is permitted; bias values may be included; capability to scale data without writing scaling code; quick interactive testing of network from the main menu; and several options that allow the user to manipulate learning efficiency. NETS is written in ANSI standard C language to be machine independent. The Macintosh version (MSC-22108) includes code for both a graphical user interface version and a command line interface version. The machine independent version (MSC-21588) only includes code for the command line interface version of NETS 3.0. The Macintosh version requires a Macintosh II series computer and has been successfully implemented under System 7. Four executables are included on these diskettes, two for floating point operations and two for integer arithmetic. It requires Think C 5.0 to compile. A minimum of 1Mb of RAM is required for execution. Sample input files and executables for both the command line version and the Macintosh user interface version are provided on the distribution medium. The Macintosh version is available on a set of three 3.5 inch 800K Macintosh format diskettes. The machine independent version has been successfully implemented on an IBM PC series compatible running MS-DOS, a DEC VAX running VMS, a SunIPC running SunOS, and a CRAY Y-MP running UNICOS. Two executables for the IBM PC version are included on the MS-DOS distribution media, one compiled for floating point operations and one for integer arithmetic. The machine independent version is available on a set of three 5.25 inch 360K MS-DOS format diskettes (standard distribution medium) or a .25 inch streaming magnetic tape cartridge in UNIX tar format. NETS was developed in 1989 and updated in 1992. IBM PC is a registered trademark of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation. DEC, VAX, and VMS are trademarks of Digital Equipment Corporation. SunIPC and SunOS are trademarks of Sun Microsystems, Inc. CRAY Y-MP and UNICOS are trademarks of Cray Research, Inc.

Optimization of multicast optical networks with genetic algorithm

NASA Astrophysics Data System (ADS)

Lv, Bo; Mao, Xiangqiao; Zhang, Feng; Qin, Xi; Lu, Dan; Chen, Ming; Chen, Yong; Cao, Jihong; Jian, Shuisheng

2007-11-01

In this letter, aiming to obtain the best multicast performance of optical network in which the video conference information is carried by specified wavelength, we extend the solutions of matrix games with the network coding theory and devise a new method to solve the complex problems of multicast network switching. In addition, an experimental optical network has been testified with best switching strategies by employing the novel numerical solution designed with an effective way of genetic algorithm. The result shows that optimal solutions with genetic algorithm are accordance with the ones with the traditional fictitious play method.

An Object-Oriented Network-Centric Software Architecture for Physical Computing

NASA Astrophysics Data System (ADS)

Palmer, Richard

1997-08-01

Recent developments in object-oriented computer languages and infrastructure such as the Internet, Web browsers, and the like provide an opportunity to define a more productive computational environment for scientific programming that is based more closely on the underlying mathematics describing physics than traditional programming languages such as FORTRAN or C++. In this talk I describe an object-oriented software architecture for representing physical problems that includes classes for such common mathematical objects as geometry, boundary conditions, partial differential and integral equations, discretization and numerical solution methods, etc. In practice, a scientific program written using this architecture looks remarkably like the mathematics used to understand the problem, is typically an order of magnitude smaller than traditional FORTRAN or C++ codes, and hence easier to understand, debug, describe, etc. All objects in this architecture are ``network-enabled,'' which means that components of a software solution to a physical problem can be transparently loaded from anywhere on the Internet or other global network. The architecture is expressed as an ``API,'' or application programmers interface specification, with reference embeddings in Java, Python, and C++. A C++ class library for an early version of this API has been implemented for machines ranging from PC's to the IBM SP2, meaning that phidentical codes run on all architectures.

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

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

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks

NASA Astrophysics Data System (ADS)

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

2012-01-01

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

Cascade Optimization for Aircraft Engines With Regression and Neural Network Analysis - Approximators

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Guptill, James D.; Hopkins, Dale A.; Lavelle, Thomas M.

2000-01-01

The NASA Engine Performance Program (NEPP) can configure and analyze almost any type of gas turbine engine that can be generated through the interconnection of a set of standard physical components. In addition, the code can optimize engine performance by changing adjustable variables under a set of constraints. However, for engine cycle problems at certain operating points, the NEPP code can encounter difficulties: nonconvergence in the currently implemented Powell's optimization algorithm and deficiencies in the Newton-Raphson solver during engine balancing. A project was undertaken to correct these deficiencies. Nonconvergence was avoided through a cascade optimization strategy, and deficiencies associated with engine balancing were eliminated through neural network and linear regression methods. An approximation-interspersed cascade strategy was used to optimize the engine's operation over its flight envelope. Replacement of Powell's algorithm by the cascade strategy improved the optimization segment of the NEPP code. The performance of the linear regression and neural network methods as alternative engine analyzers was found to be satisfactory. This report considers two examples-a supersonic mixed-flow turbofan engine and a subsonic waverotor-topped engine-to illustrate the results, and it discusses insights gained from the improved version of the NEPP code.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior.

PubMed

Liu, Ding; Wang, Zhaowen; Wen, Bihan; Yang, Jianchao; Han, Wei; Huang, Thomas S

2016-07-01

Single image super-resolution (SR) is an ill-posed problem, which tries to recover a high-resolution image from its low-resolution observation. To regularize the solution of the problem, previous methods have focused on designing good priors for natural images, such as sparse representation, or directly learning the priors from a large data set with models, such as deep neural networks. In this paper, we argue that domain expertise from the conventional sparse coding model can be combined with the key ingredients of deep learning to achieve further improved results. We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data. The network has a cascaded structure, which boosts the SR performance for both fixed and incremental scaling factors. The proposed training and testing schemes can be extended for robust handling of images with additional degradation, such as noise and blurring. A subjective assessment is conducted and analyzed in order to thoroughly evaluate various SR techniques. Our proposed model is tested on a wide range of images, and it significantly outperforms the existing state-of-the-art methods for various scaling factors both quantitatively and perceptually.

Signature neural networks: definition and application to multidimensional sorting problems.

PubMed

Latorre, Roberto; de Borja Rodriguez, Francisco; Varona, Pablo

2011-01-01

In this paper we present a self-organizing neural network paradigm that is able to discriminate information locally using a strategy for information coding and processing inspired in recent findings in living neural systems. The proposed neural network uses: 1) neural signatures to identify each unit in the network; 2) local discrimination of input information during the processing; and 3) a multicoding mechanism for information propagation regarding the who and the what of the information. The local discrimination implies a distinct processing as a function of the neural signature recognition and a local transient memory. In the context of artificial neural networks none of these mechanisms has been analyzed in detail, and our goal is to demonstrate that they can be used to efficiently solve some specific problems. To illustrate the proposed paradigm, we apply it to the problem of multidimensional sorting, which can take advantage of the local information discrimination. In particular, we compare the results of this new approach with traditional methods to solve jigsaw puzzles and we analyze the situations where the new paradigm improves the performance.

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.

Game theoretic wireless resource allocation for H.264 MGS video transmission over cognitive radio networks

NASA Astrophysics Data System (ADS)

Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2015-03-01

We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.

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.

Modeling of video traffic in packet networks, low rate video compression, and the development of a lossy+lossless image compression algorithm

NASA Technical Reports Server (NTRS)

Sayood, K.; Chen, Y. C.; Wang, X.

1992-01-01

During this reporting period we have worked on three somewhat different problems. These are modeling of video traffic in packet networks, low rate video compression, and the development of a lossy + lossless image compression algorithm, which might have some application in browsing algorithms. The lossy + lossless scheme is an extension of work previously done under this grant. It provides a simple technique for incorporating browsing capability. The low rate coding scheme is also a simple variation on the standard discrete cosine transform (DCT) coding approach. In spite of its simplicity, the approach provides surprisingly high quality reconstructions. The modeling approach is borrowed from the speech recognition literature, and seems to be promising in that it provides a simple way of obtaining an idea about the second order behavior of a particular coding scheme. Details about these are presented.

Dynamic full-scalability conversion in scalable video coding

NASA Astrophysics Data System (ADS)

Lee, Dong Su; Bae, Tae Meon; Thang, Truong Cong; Ro, Yong Man

2007-02-01

For outstanding coding efficiency with scalability functions, SVC (Scalable Video Coding) is being standardized. SVC can support spatial, temporal and SNR scalability and these scalabilities are useful to provide a smooth video streaming service even in a time varying network such as a mobile environment. But current SVC is insufficient to support dynamic video conversion with scalability, thereby the adaptation of bitrate to meet a fluctuating network condition is limited. In this paper, we propose dynamic full-scalability conversion methods for QoS adaptive video streaming in SVC. To accomplish full scalability dynamic conversion, we develop corresponding bitstream extraction, encoding and decoding schemes. At the encoder, we insert the IDR NAL periodically to solve the problems of spatial scalability conversion. At the extractor, we analyze the SVC bitstream to get the information which enable dynamic extraction. Real time extraction is achieved by using this information. Finally, we develop the decoder so that it can manage the changing scalability. Experimental results showed that dynamic full-scalability conversion was verified and it was necessary for time varying network condition.

Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee.

PubMed

Schmuker, Michael; Yamagata, Nobuhiro; Nawrot, Martin Paul; Menzel, Randolf

2011-01-01

The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee's olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.

CAVE3: A general transient heat transfer computer code utilizing eigenvectors and eigenvalues

NASA Technical Reports Server (NTRS)

Palmieri, J. V.; Rathjen, K. A.

1978-01-01

The method of solution is a hybrid analytical numerical technique which utilizes eigenvalues and eigenvectors. The method is inherently stable, permitting large time steps even with the best of conductors with the finest of mesh sizes which can provide a factor of five reduction in machine time compared to conventional explicit finite difference methods when structures with small time constants are analyzed over long time periods. This code will find utility in analyzing hypersonic missile and aircraft structures which fall naturally into this class. The code is a completely general one in that problems involving any geometry, boundary conditions and materials can be analyzed. This is made possible by requiring the user to establish the thermal network conductances between nodes. Dynamic storage allocation is used to minimize core storage requirements. This report is primarily a user's manual for CAVE3 code. Input and output formats are presented and explained. Sample problems are included which illustrate the usage of the code as well as establish the validity and accuracy of the method.

Applications of Functional Analytic and Martingale Methods to Problems in Queueing Network Theory.

DTIC Science & Technology

1983-05-14

8217’") Air Force Office of Scientific Research Sf. ADDRESS (Cllty. State and ZIP Code) 7b. ADDRESS (City. State and ZIP Code) Directorate of Mathematical... Scientific Report on Air Force Grant #82-0167 Principal Investigator: Professor Walter A. Rosenkrantz I. Publications (1) Calculation of the LaPlace transform...whether or not a protocol for accessing a comunications channel is stable. In AFOSR 82-0167, Report No. 3 we showed that the SLOTTED ALOHA Multi access

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Coding Skills as a Success Factor for a Society

ERIC Educational Resources Information Center

Tuomi, Pauliina; Multisilta, Jari Antero; Saarikoski, Petri; Suominen, Jaakko

2018-01-01

Digitalization is one of the most promising ways to increase productivity in the public sector and is needed to reform the economy by creating new innovation related jobs. The implementation of digital services requires problem solving, design skills, logical thinking, an understanding of how computers and networks operate, and programming…

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.

Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

PubMed Central

Lee, Chaewoo

2014-01-01

The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862

Convergence and rate analysis of neural networks for sparse approximation.

PubMed

Balavoine, Aurèle; Romberg, Justin; Rozell, Christopher J

2012-09-01

We present an analysis of the Locally Competitive Algorithm (LCA), which is a Hopfield-style neural network that efficiently solves sparse approximation problems (e.g., approximating a vector from a dictionary using just a few nonzero coefficients). This class of problems plays a significant role in both theories of neural coding and applications in signal processing. However, the LCA lacks analysis of its convergence properties, and previous results on neural networks for nonsmooth optimization do not apply to the specifics of the LCA architecture. We show that the LCA has desirable convergence properties, such as stability and global convergence to the optimum of the objective function when it is unique. Under some mild conditions, the support of the solution is also proven to be reached in finite time. Furthermore, some restrictions on the problem specifics allow us to characterize the convergence rate of the system by showing that the LCA converges exponentially fast with an analytically bounded convergence rate. We support our analysis with several illustrative simulations.

AMPS/PC - AUTOMATIC MANUFACTURING PROGRAMMING SYSTEM

NASA Technical Reports Server (NTRS)

Schroer, B. J.

1994-01-01

The AMPS/PC system is a simulation tool designed to aid the user in defining the specifications of a manufacturing environment and then automatically writing code for the target simulation language, GPSS/PC. The domain of problems that AMPS/PC can simulate are manufacturing assembly lines with subassembly lines and manufacturing cells. The user defines the problem domain by responding to the questions from the interface program. Based on the responses, the interface program creates an internal problem specification file. This file includes the manufacturing process network flow and the attributes for all stations, cells, and stock points. AMPS then uses the problem specification file as input for the automatic code generator program to produce a simulation program in the target language GPSS. The output of the generator program is the source code of the corresponding GPSS/PC simulation program. The system runs entirely on an IBM PC running PC DOS Version 2.0 or higher and is written in Turbo Pascal Version 4 requiring 640K memory and one 360K disk drive. To execute the GPSS program, the PC must have resident the GPSS/PC System Version 2.0 from Minuteman Software. The AMPS/PC program was developed in 1988.

Optical network security using unipolar Walsh code

NASA Astrophysics Data System (ADS)

Sikder, Somali; Sarkar, Madhumita; Ghosh, Shila

2018-04-01

Optical code-division multiple-access (OCDMA) is considered as a good technique to provide optical layer security. Many research works have been published to enhance optical network security by using optical signal processing. The paper, demonstrates the design of the AWG (arrayed waveguide grating) router-based optical network for spectral-amplitude-coding (SAC) OCDMA networks with Walsh Code to design a reconfigurable network codec by changing signature codes to against eavesdropping. In this paper we proposed a code reconfiguration scheme to improve the network access confidentiality changing the signature codes by cyclic rotations, for OCDMA system. Each of the OCDMA network users is assigned a unique signature code to transmit the information and at the receiving end each receiver correlates its own signature pattern a(n) with the receiving pattern s(n). The signal arriving at proper destination leads to s(n)=a(n).

Applications and development of communication models for the touchstone GAMMA and DELTA prototypes

NASA Technical Reports Server (NTRS)

Seidel, Steven R.

1993-01-01

The goal of this project was to develop models of the interconnection networks of the Intel iPSC/860 and DELTA multicomputers to guide the design of efficient algorithms for interprocessor communication in problems that commonly occur in CFD codes and other applications. Interprocessor communication costs of codes for message-passing architectures such as the iPSC/860 and DELTA significantly affect the level of performance that can be obtained from those machines. This project addressed several specific problems in the achievement of efficient communication on the Intel iPSC/860 hypercube and DELTA mesh. In particular, an efficient global processor synchronization algorithm was developed for the iPSC/860 and numerous broadcast algorithms were designed for the DELTA.

Automatic programming of simulation models

NASA Technical Reports Server (NTRS)

Schroer, Bernard J.; Tseng, Fan T.; Zhang, Shou X.; Dwan, Wen S.

1990-01-01

The concepts of software engineering were used to improve the simulation modeling environment. Emphasis was placed on the application of an element of rapid prototyping, or automatic programming, to assist the modeler define the problem specification. Then, once the problem specification has been defined, an automatic code generator is used to write the simulation code. The following two domains were selected for evaluating the concepts of software engineering for discrete event simulation: manufacturing domain and a spacecraft countdown network sequence. The specific tasks were to: (1) define the software requirements for a graphical user interface to the Automatic Manufacturing Programming System (AMPS) system; (2) develop a graphical user interface for AMPS; and (3) compare the AMPS graphical interface with the AMPS interactive user interface.

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

NASA Astrophysics Data System (ADS)

Ballora, Mark; Hall, David L.

2010-04-01

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

A programming environment for distributed complex computing. An overview of the Framework for Interdisciplinary Design Optimization (FIDO) project. NASA Langley TOPS exhibit H120b

NASA Technical Reports Server (NTRS)

Townsend, James C.; Weston, Robert P.; Eidson, Thomas M.

1993-01-01

The Framework for Interdisciplinary Design Optimization (FIDO) is a general programming environment for automating the distribution of complex computing tasks over a networked system of heterogeneous computers. For example, instead of manually passing a complex design problem between its diverse specialty disciplines, the FIDO system provides for automatic interactions between the discipline tasks and facilitates their communications. The FIDO system networks all the computers involved into a distributed heterogeneous computing system, so they have access to centralized data and can work on their parts of the total computation simultaneously in parallel whenever possible. Thus, each computational task can be done by the most appropriate computer. Results can be viewed as they are produced and variables changed manually for steering the process. The software is modular in order to ease migration to new problems: different codes can be substituted for each of the current code modules with little or no effect on the others. The potential for commercial use of FIDO rests in the capability it provides for automatically coordinating diverse computations on a networked system of workstations and computers. For example, FIDO could provide the coordination required for the design of vehicles or electronics or for modeling complex systems.

The hacker ethic

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

Granger, S.

The hacker ethic can be a peculiar concept to those unfamiliar with hacking and what really is. In fact, the entire definition of hacking is somewhat obscure. Hacking originated as a challenge between programmers. Programmers at MIT are known for coining the term. Individuals would hack at code meaning that they would work at programming problems until they could maniuplate their computers into doing exactly what they wanted. The MIT hackers began with simple programs and moved on to fidding with UNIX machines, especially those on the Arpanet. Hackers started freely distributing their code to their friends and eventually tomore » their friends across the network. This gave rise to a notion that software should be free. Eventually this was taken to the extreme information and network access should also be free.« less

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.

Maestro and Castro: Simulation Codes for Astrophysical Flows

NASA Astrophysics Data System (ADS)

Zingale, Michael; Almgren, Ann; Beckner, Vince; Bell, John; Friesen, Brian; Jacobs, Adam; Katz, Maximilian P.; Malone, Christopher; Nonaka, Andrew; Zhang, Weiqun

2017-01-01

Stellar explosions are multiphysics problems—modeling them requires the coordinated input of gravity solvers, reaction networks, radiation transport, and hydrodynamics together with microphysics recipes to describe the physics of matter under extreme conditions. Furthermore, these models involve following a wide range of spatial and temporal scales, which puts tough demands on simulation codes. We developed the codes Maestro and Castro to meet the computational challenges of these problems. Maestro uses a low Mach number formulation of the hydrodynamics to efficiently model convection. Castro solves the fully compressible radiation hydrodynamics equations to capture the explosive phases of stellar phenomena. Both codes are built upon the BoxLib adaptive mesh refinement library, which prepares them for next-generation exascale computers. Common microphysics shared between the codes allows us to transfer a problem from the low Mach number regime in Maestro to the explosive regime in Castro. Importantly, both codes are freely available (https://github.com/BoxLib-Codes). We will describe the design of the codes and some of their science applications, as well as future development directions.Support for development was provided by NSF award AST-1211563 and DOE/Office of Nuclear Physics grant DE-FG02-87ER40317 to Stony Brook and by the Applied Mathematics Program of the DOE Office of Advance Scientific Computing Research under US DOE contract DE-AC02-05CH11231 to LBNL.

Evaluation of nonlinear structural dynamic responses using a fast-running spring-mass formulation

NASA Astrophysics Data System (ADS)

Benjamin, A. S.; Altman, B. S.; Gruda, J. D.

In today's world, accurate finite-element simulations of large nonlinear systems may require meshes composed of hundreds of thousands of degrees of freedom. Even with today's fast computers and the promise of ever-faster ones in the future, central processing unit (CPU) expenditures for such problems could be measured in days. Many contemporary engineering problems, such as those found in risk assessment, probabilistic structural analysis, and structural design optimization, cannot tolerate the cost or turnaround time for such CPU-intensive analyses, because these applications require a large number of cases to be run with different inputs. For many risk assessment applications, analysts would prefer running times to be measurable in minutes. There is therefore a need for approximation methods which can solve such problems far more efficiently than the very detailed methods and yet maintain an acceptable degree of accuracy. For this purpose, we have been working on two methods of approximation: neural networks and spring-mass models. This paper presents our work and results to date for spring-mass modeling and analysis, since we are further along in this area than in the neural network formulation. It describes the physical and numerical models contained in a code we developed called STRESS, which stands for 'Spring-mass Transient Response Evaluation for structural Systems'. The paper also presents results for a demonstration problem, and compares these with results obtained for the same problem using PRONTO3D, a state-of-the-art finite element code which was also developed at Sandia.

shiftNMFk 1.1: Robust Nonnegative matrix factorization with kmeans clustering and signal shift, for allocation of unknown physical sources, toy version for open sourcing with publications

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

Alexandrov, Boian S.; Lliev, Filip L.; Stanev, Valentin G.

This code is a toy (short) version of CODE-2016-83. From a general perspective, the code represents an unsupervised adaptive machine learning algorithm that allows efficient and high performance de-mixing and feature extraction of a multitude of non-negative signals mixed and recorded by a network of uncorrelated sensor arrays. The code identifies the number of the mixed original signals and their locations. Further, the code also allows deciphering of signals that have been delayed in regards to the mixing process in each sensor. This code is high customizable and it can be efficiently used for a fast macro-analyses of data. Themore » code is applicable to a plethora of distinct problems: chemical decomposition, pressure transient decomposition, unknown sources/signal allocation, EM signal decomposition. An additional procedure for allocation of the unknown sources is incorporated in the code.« less

Establishing Malware Attribution and Binary Provenance Using Multicompilation Techniques

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

Ramshaw, M. J.

2017-07-28

Malware is a serious problem for computer systems and costs businesses and customers billions of dollars a year in addition to compromising their private information. Detecting malware is particularly difficult because malware source code can be compiled in many different ways and generate many different digital signatures, which causes problems for most anti-malware programs that rely on static signature detection. Our project uses a convolutional neural network to identify malware programs but these require large amounts of data to be effective. Towards that end, we gather thousands of source code files from publicly available programming contest sites and compile themmore » with several different compilers and flags. Building upon current research, we then transform these binary files into image representations and use them to train a long-term recurrent convolutional neural network that will eventually be used to identify how a malware binary was compiled. This information will include the compiler, version of the compiler and the options used in compilation, information which can be critical in determining where a malware program came from and even who authored it.« less

Hidden Markov models and other machine learning approaches in computational molecular biology

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

Baldi, P.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In thismore » tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.« less

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).

Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity.

PubMed

Koyluoglu, Onur Ozan; Pertzov, Yoni; Manohar, Sanjay; Husain, Masud; Fiete, Ila R

2017-09-07

It is widely believed that persistent neural activity underlies short-term memory. Yet, as we show, the degradation of information stored directly in such networks behaves differently from human short-term memory performance. We build a more general framework where memory is viewed as a problem of passing information through noisy channels whose degradation characteristics resemble those of persistent activity networks. If the brain first encoded the information appropriately before passing the information into such networks, the information can be stored substantially more faithfully. Within this framework, we derive a fundamental lower-bound on recall precision, which declines with storage duration and number of stored items. We show that human performance, though inconsistent with models involving direct (uncoded) storage in persistent activity networks, can be well-fit by the theoretical bound. This finding is consistent with the view that if the brain stores information in patterns of persistent activity, it might use codes that minimize the effects of noise, motivating the search for such codes in the brain.

Fundamental bound on the persistence and capacity of short-term memory stored as graded persistent activity

PubMed Central

Pertzov, Yoni; Manohar, Sanjay; Husain, Masud; Fiete, Ila R

2017-01-01

It is widely believed that persistent neural activity underlies short-term memory. Yet, as we show, the degradation of information stored directly in such networks behaves differently from human short-term memory performance. We build a more general framework where memory is viewed as a problem of passing information through noisy channels whose degradation characteristics resemble those of persistent activity networks. If the brain first encoded the information appropriately before passing the information into such networks, the information can be stored substantially more faithfully. Within this framework, we derive a fundamental lower-bound on recall precision, which declines with storage duration and number of stored items. We show that human performance, though inconsistent with models involving direct (uncoded) storage in persistent activity networks, can be well-fit by the theoretical bound. This finding is consistent with the view that if the brain stores information in patterns of persistent activity, it might use codes that minimize the effects of noise, motivating the search for such codes in the brain. PMID:28879851

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

PubMed

Gibbs, David L; Shmulevich, Ilya

2017-06-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

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

GFSSP Training Course Lectures

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.

2008-01-01

GFSSP has been extended to model conjugate heat transfer Fluid Solid Network Elements include: a) Fluid nodes and Flow Branches; b) Solid Nodes and Ambient Nodes; c) Conductors connecting Fluid-Solid, Solid-Solid and Solid-Ambient Nodes. Heat Conduction Equations are solved simultaneously with Fluid Conservation Equations for Mass, Momentum, Energy and Equation of State. The extended code was verified by comparing with analytical solution for simple conduction-convection problem The code was applied to model: a) Pressurization of Cryogenic Tank; b) Freezing and Thawing of Metal; c) Chilldown of Cryogenic Transfer Line; d) Boil-off from Cryogenic Tank.

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

PubMed

Majumder, Saikat; Verma, Shrish

2015-01-01

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

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.

Hybrid expert system for decision supporting in the medical area: complexity and cognitive computing.

PubMed

Brasil, L M; de Azevedo, F M; Barreto, J M

2001-09-01

This paper proposes a hybrid expert system (HES) to minimise some complexity problems pervasive to the artificial intelligence such as: the knowledge elicitation process, known as the bottleneck of expert systems; the model choice for knowledge representation to code human reasoning; the number of neurons in the hidden layer and the topology used in the connectionist approach; the difficulty to obtain the explanation on how the network arrived to a conclusion. Two algorithms applied to developing of HES are also suggested. One of them is used to train the fuzzy neural network and the other to obtain explanations on how the fuzzy neural network attained a conclusion. To overcome these difficulties the cognitive computing was integrated to the developed system. A case study is presented (e.g. epileptic crisis) with the problem definition and simulations. Results are also discussed.

Adolescent peer relationships and behavior problems predict young adults' communication on social networking websites.

PubMed

Mikami, Amori Yee; Szwedo, David E; Allen, Joseph P; Evans, Meredyth A; Hare, Amanda L

2010-01-01

This study examined online communication on social networking web pages in a longitudinal sample of 92 youths (39 male, 53 female). Participants' social and behavioral adjustment was assessed when they were ages 13-14 years and again at ages 20-22 years. At ages 20-22 years, participants' social networking website use and indicators of friendship quality on their web pages were coded by observers. Results suggested that youths who had been better adjusted at ages 13-14 years were more likely to be using social networking web pages at ages 20-22 years, after statistically controlling for age, gender, ethnicity, and parental income. Overall, youths' patterns of peer relationships, friendship quality, and behavioral adjustment at ages 13-14 years and at ages 20-22 years predicted similar qualities of interaction and problem behavior on their social networking websites at ages 20-22 years. Findings are consistent with developmental theory asserting that youths display cross-situational continuity in their social behaviors and suggest that the conceptualization of continuity may be extended into the online domain. Copyright 2009 APA, all rights reserved.

Adolescent Peer Relationships and Behavior Problems Predict Young Adults' Communication on Social Networking Websites

PubMed Central

Mikami, Amori Yee; Szwedo, David E.; Allen, Joseph P.; Evans, Meredyth A.; Hare, Amanda L.

2010-01-01

This study examined online communication on social networking web pages in a longitudinal sample of 92 youths (39 male, 53 female). Participants' social and behavioral adjustment was assessed when they were ages 13–14 years and again at ages 20–22 years. At ages 20–22 years, participants' social networking website use and indicators of friendship quality on their web pages were coded by observers. Results suggested that youths who had been better adjusted at ages 13–14 years were more likely to be using social networking web pages at ages 20–22 years, after statistically controlling for age, gender, ethnicity, and parental income. Overall, youths' patterns of peer relationships, friendship quality, and behavioral adjustment at ages 13–14 years and at ages 20–22 years predicted similar qualities of interaction and problem behavior on their social networking websites at ages 20–22 years. Findings are consistent with developmental theory asserting that youths display cross-situational continuity in their social behaviors and suggest that the conceptualization of continuity may be extended into the online domain. PMID:20053005

Application of a distributed network in computational fluid dynamic simulations

NASA Technical Reports Server (NTRS)

Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.; Deshpande, Ashish

1994-01-01

A general-purpose 3-D, incompressible Navier-Stokes algorithm is implemented on a network of concurrently operating workstations using parallel virtual machine (PVM) and compared with its performance on a CRAY Y-MP and on an Intel iPSC/860. The problem is relatively computationally intensive, and has a communication structure based primarily on nearest-neighbor communication, making it ideally suited to message passing. Such problems are frequently encountered in computational fluid dynamics (CDF), and their solution is increasingly in demand. The communication structure is explicitly coded in the implementation to fully exploit the regularity in message passing in order to produce a near-optimal solution. Results are presented for various grid sizes using up to eight processors.

Hybrid services efficient provisioning over the network coding-enabled elastic optical networks

NASA Astrophysics Data System (ADS)

Wang, Xin; Gu, Rentao; Ji, Yuefeng; Kavehrad, Mohsen

2017-03-01

As a variety of services have emerged, hybrid services have become more common in real optical networks. Although the elastic spectrum resource optimizations over the elastic optical networks (EONs) have been widely investigated, little research has been carried out on the hybrid services of the routing and spectrum allocation (RSA), especially over the network coding-enabled EON. We investigated the RSA for the unicast service and network coding-based multicast service over the network coding-enabled EON with the constraints of time delay and transmission distance. To address this issue, a mathematical model was built to minimize the total spectrum consumption for the hybrid services over the network coding-enabled EON under the constraints of time delay and transmission distance. The model guarantees different routing constraints for different types of services. The immediate nodes over the network coding-enabled EON are assumed to be capable of encoding the flows for different kinds of information. We proposed an efficient heuristic algorithm of the network coding-based adaptive routing and layered graph-based spectrum allocation algorithm (NCAR-LGSA). From the simulation results, NCAR-LGSA shows highly efficient performances in terms of the spectrum resources utilization under different network scenarios compared with the benchmark algorithms.

The Study on Network Examinational Database based on ASP Technology

NASA Astrophysics Data System (ADS)

Zhang, Yanfu; Han, Yuexiao; Zhou, Yanshuang

This article introduces the structure of the general test base system based on .NET technology, discussing the design of the function modules and its implementation methods. It focuses on key technology of the system, proposing utilizing the WEB online editor control to solve the input problem and regular expression to solve the problem HTML code, making use of genetic algorithm to optimize test paper and the automated tools of WORD to solve the problem of exporting papers and others. Practical effective design and implementation technology can be used as reference for the development of similar systems.

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.

Nuclear Forensics and Radiochemistry: Reaction Networks

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

Rundberg, Robert S.

In the intense neutron flux of a nuclear explosion the production of isotopes may occur through successive neutron induced reactions. The pathway to these isotopes illustrates both the complexity of the problem and the need for high quality nuclear data. The growth and decay of radioactive isotopes can follow a similarly complex network. The Bateman equation will be described and modified to apply to the transmutation of isotopes in a high flux reactor. A alternative model of growth and decay, the GD code, that can be applied to fission products will also be described.

Variable weight spectral amplitude coding for multiservice OCDMA networks

NASA Astrophysics Data System (ADS)

Seyedzadeh, Saleh; Rahimian, Farzad Pour; Glesk, Ivan; Kakaee, Majid H.

2017-09-01

The emergence of heterogeneous data traffic such as voice over IP, video streaming and online gaming have demanded networks with capability of supporting quality of service (QoS) at the physical layer with traffic prioritisation. This paper proposes a new variable-weight code based on spectral amplitude coding for optical code-division multiple-access (OCDMA) networks to support QoS differentiation. The proposed variable-weight multi-service (VW-MS) code relies on basic matrix construction. A mathematical model is developed for performance evaluation of VW-MS OCDMA networks. It is shown that the proposed code provides an optimal code length with minimum cross-correlation value when compared to other codes. Numerical results for a VW-MS OCDMA network designed for triple-play services operating at 0.622 Gb/s, 1.25 Gb/s and 2.5 Gb/s are considered.

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.

[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.

Quantum internet using code division multiple access

PubMed Central

Zhang, Jing; Liu, Yu-xi; Özdemir, Şahin Kaya; Wu, Re-Bing; Gao, Feifei; Wang, Xiang-Bin; Yang, Lan; Nori, Franco

2013-01-01

A crucial open problem inS large-scale quantum networks is how to efficiently transmit quantum data among many pairs of users via a common data-transmission medium. We propose a solution by developing a quantum code division multiple access (q-CDMA) approach in which quantum information is chaotically encoded to spread its spectral content, and then decoded via chaos synchronization to separate different sender-receiver pairs. In comparison to other existing approaches, such as frequency division multiple access (FDMA), the proposed q-CDMA can greatly increase the information rates per channel used, especially for very noisy quantum channels. PMID:23860488

Parameter as a Switch Between Dynamical States of a Network in Population Decoding.

PubMed

Yu, Jiali; Mao, Hua; Yi, Zhang

2017-04-01

Population coding is a method to represent stimuli using the collective activities of a number of neurons. Nevertheless, it is difficult to extract information from these population codes with the noise inherent in neuronal responses. Moreover, it is a challenge to identify the right parameter of the decoding model, which plays a key role for convergence. To address the problem, a population decoding model is proposed for parameter selection. Our method successfully identified the key conditions for a nonzero continuous attractor. Both the theoretical analysis and the application studies demonstrate the correctness and effectiveness of this strategy.

The Role of the Social Network in Access to Psychosocial Services for Migrant Elderly—A Qualitative Study

PubMed Central

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-01-01

Background: Despite high prevalence of mental problems among elderly migrants in The Netherlands, the use of psychosocial care services by this group is low. Scientific evidence points at the crucial role of social support for mental health and the use of psychosocial services. We therefore explored the role of social networks in the access to psychosocial care among elderly migrants in The Netherlands. Methods: A qualitative study was conducted using semi-structured group interviews and individual interviews. The eight group and eleven individual interviews (respectively n = 58 and n = 11) were conducted in The Netherlands with Turkish, Moroccan, Surinamese, and Dutch elderly. The data were analysed through coding and comparing fragments and recognizing patterns. Results: Support of the social network is important to navigate to psychosocial care and is most frequently provided by children. However, the social network of elderly migrants is generally not able to meet the needs of the elderly. This is mostly due to poor mental health literacy of the social network, taboo, and stigma around mental illness and the busy lives of the social network members. Conclusions: Strategies to address help-seeking barriers should consider mental health literacy in elderly migrants as well as their social networks, and counteract taboos and stigma of mental health problems. PMID:29019961

The Role of the Social Network in Access to Psychosocial Services for Migrant Elderly-A Qualitative Study.

PubMed

Schoenmakers, Daphne; Lamkaddem, Majda; Suurmond, Jeanine

2017-10-11

Abstract : Background: Despite high prevalence of mental problems among elderly migrants in The Netherlands, the use of psychosocial care services by this group is low. Scientific evidence points at the crucial role of social support for mental health and the use of psychosocial services. We therefore explored the role of social networks in the access to psychosocial care among elderly migrants in The Netherlands. Methods: A qualitative study was conducted using semi-structured group interviews and individual interviews. The eight group and eleven individual interviews (respectively n = 58 and n = 11) were conducted in The Netherlands with Turkish, Moroccan, Surinamese, and Dutch elderly. The data were analysed through coding and comparing fragments and recognizing patterns. Results: Support of the social network is important to navigate to psychosocial care and is most frequently provided by children. However, the social network of elderly migrants is generally not able to meet the needs of the elderly. This is mostly due to poor mental health literacy of the social network, taboo, and stigma around mental illness and the busy lives of the social network members. Conclusion s : Strategies to address help-seeking barriers should consider mental health literacy in elderly migrants as well as their social networks, and counteract taboos and stigma of mental health problems.

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…

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 Modified Artificial Bee Colony Algorithm for p-Center Problems

PubMed Central

Yurtkuran, Alkın

2014-01-01

The objective of the p-center problem is to locate p-centers on a network such that the maximum of the distances from each node to its nearest center is minimized. The artificial bee colony algorithm is a swarm-based meta-heuristic algorithm that mimics the foraging behavior of honey bee colonies. This study proposes a modified ABC algorithm that benefits from a variety of search strategies to balance exploration and exploitation. Moreover, random key-based coding schemes are used to solve the p-center problem effectively. The proposed algorithm is compared to state-of-the-art techniques using different benchmark problems, and computational results reveal that the proposed approach is very efficient. PMID:24616648

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.

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

PubMed

Ni, Jingchao; Koyuturk, Mehmet; Tong, Hanghang; Haines, Jonathan; Xu, Rong; Zhang, Xiang

2016-11-10

Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity network and molecular networks such as protein interaction or gene co-expression networks. Although successful, a common limitation of the existing methods is that they assume all diseases share the same molecular network and a single generic molecular network is used to predict candidate genes for all diseases. However, different diseases tend to manifest in different tissues, and the molecular networks in different tissues are usually different. An ideal method should be able to incorporate tissue-specific molecular networks for different diseases. In this paper, we develop a robust and flexible method to integrate tissue-specific molecular networks for disease gene prioritization. Our method allows each disease to have its own tissue-specific network(s). We formulate the problem of candidate gene prioritization as an optimization problem based on network propagation. When there are multiple tissue-specific networks available for a disease, our method can automatically infer the relative importance of each tissue-specific network. Thus it is robust to the noisy and incomplete network data. To solve the optimization problem, we develop fast algorithms which have linear time complexities in the number of nodes in the molecular networks. We also provide rigorous theoretical foundations for our algorithms in terms of their optimality and convergence properties. Extensive experimental results show that our method can significantly improve the accuracy of candidate gene prioritization compared with the state-of-the-art methods. In our experiments, we compare our methods with 7 popular network-based disease gene prioritization algorithms on diseases from Online Mendelian Inheritance in Man (OMIM) database. The experimental results demonstrate that our methods recover true associations more accurately than other methods in terms of AUC values, and the performance differences are significant (with paired t-test p-values less than 0.05). This validates the importance to integrate tissue-specific molecular networks for studying disease gene prioritization and show the superiority of our network models and ranking algorithms toward this purpose. The source code and datasets are available at http://nijingchao.github.io/CRstar/ .

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

Carothers, Christopher D.; Meredith, Jeremy S.; Blanco, Marc

Performance modeling of extreme-scale applications on accurate representations of potential architectures is critical for designing next generation supercomputing systems because it is impractical to construct prototype systems at scale with new network hardware in order to explore designs and policies. However, these simulations often rely on static application traces that can be difficult to work with because of their size and lack of flexibility to extend or scale up without rerunning the original application. To address this problem, we have created a new technique for generating scalable, flexible workloads from real applications, we have implemented a prototype, called Durango, thatmore » combines a proven analytical performance modeling language, Aspen, with the massively parallel HPC network modeling capabilities of the CODES framework.Our models are compact, parameterized and representative of real applications with computation events. They are not resource intensive to create and are portable across simulator environments. We demonstrate the utility of Durango by simulating the LULESH application in the CODES simulation environment on several topologies and show that Durango is practical to use for simulation without loss of fidelity, as quantified by simulation metrics. During our validation of Durango's generated communication model of LULESH, we found that the original LULESH miniapp code had a latent bug where the MPI_Waitall operation was used incorrectly. This finding underscores the potential need for a tool such as Durango, beyond its benefits for flexible workload generation and modeling.Additionally, we demonstrate the efficacy of Durango's direct integration approach, which links Aspen into CODES as part of the running network simulation model. Here, Aspen generates the application-level computation timing events, which in turn drive the start of a network communication phase. Results show that Durango's performance scales well when executing both torus and dragonfly network models on up to 4K Blue Gene/Q nodes using 32K MPI ranks, Durango also avoids the overheads and complexities associated with extreme-scale trace files.« less

Classical and neural methods of image sequence interpolation

NASA Astrophysics Data System (ADS)

Skoneczny, Slawomir; Szostakowski, Jaroslaw

2001-08-01

An image interpolation problem is often encountered in many areas. Some examples are interpolation for coding/decoding process for transmission purposes, reconstruction a full frame from two interlaced sub-frames in normal TV or HDTV, or reconstruction of missing frames in old destroyed cinematic sequences. In this paper an overview of interframe interpolation methods is presented. Both direct as well as motion compensated interpolation techniques are given by examples. The used methodology can also be either classical or based on neural networks depending on demand of a specific interpolation problem solving person.

MAC Protocol for Ad Hoc Networks Using a Genetic Algorithm

PubMed Central

Elizarraras, Omar; Panduro, Marco; Méndez, Aldo L.

2014-01-01

The problem of obtaining the transmission rate in an ad hoc network consists in adjusting the power of each node to ensure the signal to interference ratio (SIR) and the energy required to transmit from one node to another is obtained at the same time. Therefore, an optimal transmission rate for each node in a medium access control (MAC) protocol based on CSMA-CDMA (carrier sense multiple access-code division multiple access) for ad hoc networks can be obtained using evolutionary optimization. This work proposes a genetic algorithm for the transmission rate election considering a perfect power control, and our proposition achieves improvement of 10% compared with the scheme that handles the handshaking phase to adjust the transmission rate. Furthermore, this paper proposes a genetic algorithm that solves the problem of power combining, interference, data rate, and energy ensuring the signal to interference ratio in an ad hoc network. The result of the proposed genetic algorithm has a better performance (15%) compared to the CSMA-CDMA protocol without optimizing. Therefore, we show by simulation the effectiveness of the proposed protocol in terms of the throughput. PMID:25140339

A high-order language for a system of closely coupled processing elements

NASA Technical Reports Server (NTRS)

Feyock, S.; Collins, W. R.

1986-01-01

The research reported in this paper was occasioned by the requirements on part of the Real-Time Digital Simulator (RTDS) project under way at NASA Lewis Research Center. The RTDS simulation scheme employs a network of CPUs running lock-step cycles in the parallel computations of jet airplane simulations. Their need for a high order language (HOL) that would allow non-experts to write simulation applications and that could be implemented on a possibly varying network can best be fulfilled by using the programming language Ada. We describe how the simulation problems can be modeled in Ada, how to map a single, multi-processing Ada program into code for individual processors, regardless of network reconfiguration, and why some Ada language features are particulary well-suited to network simulations.

Network Coding in Relay-based Device-to-Device Communications

PubMed Central

Huang, Jun; Gharavi, Hamid; Yan, Huifang; Xing, Cong-cong

2018-01-01

Device-to-Device (D2D) communications has been realized as an effective means to improve network throughput, reduce transmission latency, and extend cellular coverage in 5G systems. Network coding is a well-established technique known for its capability to reduce the number of retransmissions. In this article, we review state-of-the-art network coding in relay-based D2D communications, in terms of application scenarios and network coding techniques. We then apply two representative network coding techniques to dual-hop D2D communications and present an efficient relay node selecting mechanism as a case study. We also outline potential future research directions, according to the current research challenges. Our intention is to provide researchers and practitioners with a comprehensive overview of the current research status in this area and hope that this article may motivate more researchers to participate in developing network coding techniques for different relay-based D2D communications scenarios. PMID:29503504

SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks.

PubMed

Zenke, Friedemann; Ganguli, Surya

2018-06-01

A vast majority of computation in the brain is performed by spiking neural networks. Despite the ubiquity of such spiking, we currently lack an understanding of how biological spiking neural circuits learn and compute in vivo, as well as how we can instantiate such capabilities in artificial spiking circuits in silico. Here we revisit the problem of supervised learning in temporally coding multilayer spiking neural networks. First, by using a surrogate gradient approach, we derive SuperSpike, a nonlinear voltage-based three-factor learning rule capable of training multilayer networks of deterministic integrate-and-fire neurons to perform nonlinear computations on spatiotemporal spike patterns. Second, inspired by recent results on feedback alignment, we compare the performance of our learning rule under different credit assignment strategies for propagating output errors to hidden units. Specifically, we test uniform, symmetric, and random feedback, finding that simpler tasks can be solved with any type of feedback, while more complex tasks require symmetric feedback. In summary, our results open the door to obtaining a better scientific understanding of learning and computation in spiking neural networks by advancing our ability to train them to solve nonlinear problems involving transformations between different spatiotemporal spike time patterns.

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.

Distributed Coding/Decoding Complexity in Video Sensor Networks

PubMed Central

Cordeiro, Paulo J.; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality. PMID:22736972

Distributed coding/decoding complexity in video sensor networks.

PubMed

Cordeiro, Paulo J; Assunção, Pedro

2012-01-01

Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.

Mobile code security

NASA Astrophysics Data System (ADS)

Ramalingam, Srikumar

2001-11-01

A highly secure mobile agent system is very important for a mobile computing environment. The security issues in mobile agent system comprise protecting mobile hosts from malicious agents, protecting agents from other malicious agents, protecting hosts from other malicious hosts and protecting agents from malicious hosts. Using traditional security mechanisms the first three security problems can be solved. Apart from using trusted hardware, very few approaches exist to protect mobile code from malicious hosts. Some of the approaches to solve this problem are the use of trusted computing, computing with encrypted function, steganography, cryptographic traces, Seal Calculas, etc. This paper focuses on the simulation of some of these existing techniques in the designed mobile language. Some new approaches to solve malicious network problem and agent tampering problem are developed using public key encryption system and steganographic concepts. The approaches are based on encrypting and hiding the partial solutions of the mobile agents. The partial results are stored and the address of the storage is destroyed as the agent moves from one host to another host. This allows only the originator to make use of the partial results. Through these approaches some of the existing problems are solved.

Genetic learning in rule-based and neural systems

NASA Technical Reports Server (NTRS)

Smith, Robert E.

1993-01-01

The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

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.

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.

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.

A Descriptive Study of the Prevalence and Typology of Alcohol-Related Posts in an Online Social Network for Smoking Cessation.

PubMed

Cohn, Amy M; Zhao, Kang; Cha, Sarah; Wang, Xi; Amato, Michael S; Pearson, Jennifer L; Papandonatos, George D; Graham, Amanda L

2017-09-01

Alcohol use and problem drinking are associated with smoking relapse and poor smoking-cessation success. User-generated content in online social networks for smoking cessation provides an opportunity to understand the challenges and treatment needs of smokers. This study used machine-learning text classification to identify the prevalence, sentiment, and social network correlates of alcohol-related content in the social network of a large online smoking-cessation program, BecomeAnEX.org. Data were analyzed from 814,258 posts (January 2012 to May 2015). Posts containing alcohol keywords were coded via supervised machine-learning text classification for information about the user's personal experience with drinking, whether the user self-identified as a problem drinker or indicated problem drinking, and negative sentiment about drinking in the context of a quit attempt (i.e., alcohol should be avoided during a quit attempt). Less than 1% of posts were related to alcohol, contributed by 13% of users. Roughly a third of alcohol posts described a personal experience with drinking; very few (3%) indicated "problem drinking." The majority (70%) of alcohol posts did not express negative sentiment about drinking alcohol during a quit attempt. Users who did express negative sentiment about drinking were more centrally located within the network compared with those who did not. Discussion of alcohol was rare, and most posts did not signal the need to quit or abstain from drinking during a quit attempt. Featuring expert information or highlighting discussions that are consistent with treatment guidelines may be important steps to ensure smokers are educated about drinking risks.

Self-organizing feature maps for dynamic control of radio resources in CDMA microcellular networks

NASA Astrophysics Data System (ADS)

Hortos, William S.

1998-03-01

The application of artificial neural networks to the channel assignment problem for cellular code-division multiple access (CDMA) cellular networks has previously been investigated. CDMA takes advantage of voice activity and spatial isolation because its capacity is only interference limited, unlike time-division multiple access (TDMA) and frequency-division multiple access (FDMA) where capacities are bandwidth-limited. Any reduction in interference in CDMA translates linearly into increased capacity. To satisfy the high demands for new services and improved connectivity for mobile communications, microcellular and picocellular systems are being introduced. For these systems, there is a need to develop robust and efficient management procedures for the allocation of power and spectrum to maximize radio capacity. Topology-conserving mappings play an important role in the biological processing of sensory inputs. The same principles underlying Kohonen's self-organizing feature maps (SOFMs) are applied to the adaptive control of radio resources to minimize interference, hence, maximize capacity in direct-sequence (DS) CDMA networks. The approach based on SOFMs is applied to some published examples of both theoretical and empirical models of DS/CDMA microcellular networks in metropolitan areas. The results of the approach for these examples are informally compared to the performance of algorithms, based on Hopfield- Tank neural networks and on genetic algorithms, for the channel assignment problem.

Preschool Teacher Assessment of the NTC Program Reach: Encouraging Creative Elements of Thinking

ERIC Educational Resources Information Center

Rajovic, Ranko; Gojkov-Rajic, Aleksandra; Stojanovic, Aleksandar

2017-01-01

The paper presents a part of the findings of an evaluation study which is experimental in character and in which the experiment with one group was used as a method. The subject and problem relate to the observation of the effects of the project "Smart Children Network-SMART", code: 1286, which is based on the NTC learning system with the…

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.

Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli

PubMed Central

Rossi-Pool, Román; Salinas, Emilio; Zainos, Antonio; Alvarez, Manuel; Vergara, José; Parga, Néstor; Romo, Ranulfo

2016-01-01

The problem of neural coding in perceptual decision making revolves around two fundamental questions: (i) How are the neural representations of sensory stimuli related to perception, and (ii) what attributes of these neural responses are relevant for downstream networks, and how do they influence decision making? We studied these two questions by recording neurons in primary somatosensory (S1) and dorsal premotor (DPC) cortex while trained monkeys reported whether the temporal pattern structure of two sequential vibrotactile stimuli (of equal mean frequency) was the same or different. We found that S1 neurons coded the temporal patterns in a literal way and only during the stimulation periods and did not reflect the monkeys’ decisions. In contrast, DPC neurons coded the stimulus patterns as broader categories and signaled them during the working memory, comparison, and decision periods. These results show that the initial sensory representation is transformed into an intermediate, more abstract categorical code that combines past and present information to ultimately generate a perceptually informed choice. PMID:27872293

Robust pattern decoding in shape-coded structured light

NASA Astrophysics Data System (ADS)

Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai

2017-09-01

Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.

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.

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.

Efficiently modeling neural networks on massively parallel computers

NASA Technical Reports Server (NTRS)

Farber, Robert M.

1993-01-01

Neural networks are a very useful tool for analyzing and modeling complex real world systems. Applying neural network simulations to real world problems generally involves large amounts of data and massive amounts of computation. To efficiently handle the computational requirements of large problems, we have implemented at Los Alamos a highly efficient neural network compiler for serial computers, vector computers, vector parallel computers, and fine grain SIMD computers such as the CM-2 connection machine. This paper describes the mapping used by the compiler to implement feed-forward backpropagation neural networks for a SIMD (Single Instruction Multiple Data) architecture parallel computer. Thinking Machines Corporation has benchmarked our code at 1.3 billion interconnects per second (approximately 3 gigaflops) on a 64,000 processor CM-2 connection machine (Singer 1990). This mapping is applicable to other SIMD computers and can be implemented on MIMD computers such as the CM-5 connection machine. Our mapping has virtually no communications overhead with the exception of the communications required for a global summation across the processors (which has a sub-linear runtime growth on the order of O(log(number of processors)). We can efficiently model very large neural networks which have many neurons and interconnects and our mapping can extend to arbitrarily large networks (within memory limitations) by merging the memory space of separate processors with fast adjacent processor interprocessor communications. This paper will consider the simulation of only feed forward neural network although this method is extendable to recurrent networks.

Stochastic Computations in Cortical Microcircuit Models

PubMed Central

Maass, Wolfgang

2013-01-01

Experimental data from neuroscience suggest that a substantial amount of knowledge is stored in the brain in the form of probability distributions over network states and trajectories of network states. We provide a theoretical foundation for this hypothesis by showing that even very detailed models for cortical microcircuits, with data-based diverse nonlinear neurons and synapses, have a stationary distribution of network states and trajectories of network states to which they converge exponentially fast from any initial state. We demonstrate that this convergence holds in spite of the non-reversibility of the stochastic dynamics of cortical microcircuits. We further show that, in the presence of background network oscillations, separate stationary distributions emerge for different phases of the oscillation, in accordance with experimentally reported phase-specific codes. We complement these theoretical results by computer simulations that investigate resulting computation times for typical probabilistic inference tasks on these internally stored distributions, such as marginalization or marginal maximum-a-posteriori estimation. Furthermore, we show that the inherent stochastic dynamics of generic cortical microcircuits enables them to quickly generate approximate solutions to difficult constraint satisfaction problems, where stored knowledge and current inputs jointly constrain possible solutions. This provides a powerful new computing paradigm for networks of spiking neurons, that also throws new light on how networks of neurons in the brain could carry out complex computational tasks such as prediction, imagination, memory recall and problem solving. PMID:24244126

Delay Analysis of Car-to-Car Reliable Data Delivery Strategies Based on Data Mulling with Network Coding

NASA Astrophysics Data System (ADS)

Park, Joon-Sang; Lee, Uichin; Oh, Soon Young; Gerla, Mario; Lun, Desmond Siumen; Ro, Won Woo; Park, Joonseok

Vehicular ad hoc networks (VANET) aims to enhance vehicle navigation safety by providing an early warning system: any chance of accidents is informed through the wireless communication between vehicles. For the warning system to work, it is crucial that safety messages be reliably delivered to the target vehicles in a timely manner and thus reliable and timely data dissemination service is the key building block of VANET. Data mulling technique combined with three strategies, network codeing, erasure coding and repetition coding, is proposed for the reliable and timely data dissemination service. Particularly, vehicles in the opposite direction on a highway are exploited as data mules, mobile nodes physically delivering data to destinations, to overcome intermittent network connectivity cause by sparse vehicle traffic. Using analytic models, we show that in such a highway data mulling scenario the network coding based strategy outperforms erasure coding and repetition based strategies.

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

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

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.

An introduction to deep learning on biological sequence data: examples and solutions.

PubMed

Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae

2017-11-15

Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. skaaesonderby@gmail.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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.

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.

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.

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.

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.

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.

Space-Time Processing for Tactical Mobile Ad Hoc Networks

DTIC Science & Technology

2010-05-01

Spatial Diversity and Imperfect Channel Estimation on Wideband MC- DS - CDMA and MC- CDMA " IEEE Transactions on Communications, Vol. 57, No. 10, pp. 2988...include direct sequence code division multiple access ( DS - CDMA ), Frequency Hopped (FH) CDMA and Orthogonal Frequency Division Multiple Access (OFDMA...capability, LPD/LPI, and operability in non-continuous spectrum. In addition, FH- CDMA is robust to the near-far problem, while DS - CDMA requires

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

NASA Astrophysics Data System (ADS)

Andreotti, Riccardo; Del Fiorentino, Paolo; Giannetti, Filippo; Lottici, Vincenzo

2016-12-01

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

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.

MIDER: Network Inference with Mutual Information Distance and Entropy Reduction

PubMed Central

Villaverde, Alejandro F.; Ross, John; Morán, Federico; Banga, Julio R.

2014-01-01

The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information–theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning. PMID:24806471

MIDER: network inference with mutual information distance and entropy reduction.

PubMed

Villaverde, Alejandro F; Ross, John; Morán, Federico; Banga, Julio R

2014-01-01

The prediction of links among variables from a given dataset is a task referred to as network inference or reverse engineering. It is an open problem in bioinformatics and systems biology, as well as in other areas of science. Information theory, which uses concepts such as mutual information, provides a rigorous framework for addressing it. While a number of information-theoretic methods are already available, most of them focus on a particular type of problem, introducing assumptions that limit their generality. Furthermore, many of these methods lack a publicly available implementation. Here we present MIDER, a method for inferring network structures with information theoretic concepts. It consists of two steps: first, it provides a representation of the network in which the distance among nodes indicates their statistical closeness. Second, it refines the prediction of the existing links to distinguish between direct and indirect interactions and to assign directionality. The method accepts as input time-series data related to some quantitative features of the network nodes (such as e.g. concentrations, if the nodes are chemical species). It takes into account time delays between variables, and allows choosing among several definitions and normalizations of mutual information. It is general purpose: it may be applied to any type of network, cellular or otherwise. A Matlab implementation including source code and data is freely available (http://www.iim.csic.es/~gingproc/mider.html). The performance of MIDER has been evaluated on seven different benchmark problems that cover the main types of cellular networks, including metabolic, gene regulatory, and signaling. Comparisons with state of the art information-theoretic methods have demonstrated the competitive performance of MIDER, as well as its versatility. Its use does not demand any a priori knowledge from the user; the default settings and the adaptive nature of the method provide good results for a wide range of problems without requiring tuning.

Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

NASA Astrophysics Data System (ADS)

Kuvich, Gary

2004-08-01

Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

Power prediction in mobile communication systems using an optimal neural-network structure.

PubMed

Gao, X M; Gao, X Z; Tanskanen, J A; Ovaska, S J

1997-01-01

Presents a novel neural-network-based predictor for received power level prediction in direct sequence code division multiple access (DS/CDMA) systems. The predictor consists of an adaptive linear element (Adaline) followed by a multilayer perceptron (MLP). An important but difficult problem in designing such a cascade predictor is to determine the complexity of the networks. We solve this problem by using the predictive minimum description length (PMDL) principle to select the optimal numbers of input and hidden nodes. This approach results in a predictor with both good noise attenuation and excellent generalization capability. The optimized neural networks are used for predictive filtering of very noisy Rayleigh fading signals with 1.8 GHz carrier frequency. Our results show that the optimal neural predictor can provide smoothed in-phase and quadrature signals with signal-to-noise ratio (SNR) gains of about 12 and 7 dB at the urban mobile speeds of 5 and 50 km/h, respectively. The corresponding power signal SNR gains are about 11 and 5 dB. Therefore, the neural predictor is well suitable for power control applications where ldquodelaylessrdquo noise attenuation and efficient reduction of fast fading are required.

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

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

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

L2-LBMT: A Layered Load Balance Routing Protocol for underwater multimedia data transmission

NASA Astrophysics Data System (ADS)

Lv, Ze; Tang, Ruichun; Tao, Ye; Sun, Xin; Xu, Xiaowei

2017-12-01

Providing highly efficient underwater transmission of mass multimedia data is challenging due to the particularities of the underwater environment. Although there are many schemes proposed to optimize the underwater acoustic network communication protocols, from physical layer, data link layer, network layer to transport layer, the existing routing protocols for underwater wireless sensor network (UWSN) still cannot well deal with the problems in transmitting multimedia data because of the difficulties involved in high energy consumption, low transmission reliability or high transmission delay. It prevents us from applying underwater multimedia data to real-time monitoring of marine environment in practical application, especially in emergency search, rescue operation and military field. Therefore, the inefficient transmission of marine multimedia data has become a serious problem that needs to be solved urgently. In this paper, A Layered Load Balance Routing Protocol (L2-LBMT) is proposed for underwater multimedia data transmission. In L2-LBMT, we use layered and load-balance Ad Hoc Network to transmit data, and adopt segmented data reliable transfer (SDRT) protocol to improve the data transport reliability. And a 3-node variant of tornado (3-VT) code is also combined with the Ad Hoc Network to transmit little emergency data more quickly. The simulation results show that the proposed protocol can balance energy consumption of each node, effectively prolong the network lifetime and reduce transmission delay of marine multimedia data.

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.

On Applicability of Network Coding Technique for 6LoWPAN-based Sensor Networks.

PubMed

Amanowicz, Marek; Krygier, Jaroslaw

2018-05-26

In this paper, the applicability of the network coding technique in 6LoWPAN-based sensor multihop networks is examined. The 6LoWPAN is one of the standards proposed for the Internet of Things architecture. Thus, we can expect the significant growth of traffic in such networks, which can lead to overload and decrease in the sensor network lifetime. The authors propose the inter-session network coding mechanism that can be implemented in resource-limited sensor motes. The solution reduces the overall traffic in the network, and in consequence, the energy consumption is decreased. Used procedures take into account deep header compressions of the native 6LoWPAN packets and the hop-by-hop changes of the header structure. Applied simplifications reduce signaling traffic that is typically occurring in network coding deployments, keeping the solution usefulness for the wireless sensor networks with limited resources. The authors validate the proposed procedures in terms of end-to-end packet delay, packet loss ratio, traffic in the air, total energy consumption, and network lifetime. The solution has been tested in a real wireless sensor network. The results confirm the efficiency of the proposed technique, mostly in delay-tolerant 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.

Network Coded Cooperative Communication in a Real-Time Wireless Hospital Sensor Network.

PubMed

Prakash, R; Balaji Ganesh, A; Sivabalan, Somu

2017-05-01

The paper presents a network coded cooperative communication (NC-CC) enabled wireless hospital sensor network architecture for monitoring health as well as postural activities of a patient. A wearable device, referred as a smartband is interfaced with pulse rate, body temperature sensors and an accelerometer along with wireless protocol services, such as Bluetooth and Radio-Frequency transceiver and Wi-Fi. The energy efficiency of wearable device is improved by embedding a linear acceleration based transmission duty cycling algorithm (NC-DRDC). The real-time demonstration is carried-out in a hospital environment to evaluate the performance characteristics, such as power spectral density, energy consumption, signal to noise ratio, packet delivery ratio and transmission offset. The resource sharing and energy efficiency features of network coding technique are improved by proposing an algorithm referred as network coding based dynamic retransmit/rebroadcast decision control (LA-TDC). From the experimental results, it is observed that the proposed LA-TDC algorithm reduces network traffic and end-to-end delay by an average of 27.8% and 21.6%, respectively than traditional network coded wireless transmission. The wireless architecture is deployed in a hospital environment and results are then successfully validated.

ADFNE: Open source software for discrete fracture network engineering, two and three dimensional applications

NASA Astrophysics Data System (ADS)

Fadakar Alghalandis, Younes

2017-05-01

Rapidly growing topic, the discrete fracture network engineering (DFNE), has already attracted many talents from diverse disciplines in academia and industry around the world to challenge difficult problems related to mining, geothermal, civil, oil and gas, water and many other projects. Although, there are few commercial software capable of providing some useful functionalities fundamental for DFNE, their costs, closed code (black box) distributions and hence limited programmability and tractability encouraged us to respond to this rising demand with a new solution. This paper introduces an open source comprehensive software package for stochastic modeling of fracture networks in two- and three-dimension in discrete formulation. Functionalities included are geometric modeling (e.g., complex polygonal fracture faces, and utilizing directional statistics), simulations, characterizations (e.g., intersection, clustering and connectivity analyses) and applications (e.g., fluid flow). The package is completely written in Matlab scripting language. Significant efforts have been made to bring maximum flexibility to the functions in order to solve problems in both two- and three-dimensions in an easy and united way that is suitable for beginners, advanced and experienced users.

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

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.

Study on multiple-hops performance of MOOC sequences-based optical labels for OPS networks

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Qiu, Kun; Ma, Chunli

2009-11-01

In this paper, we utilize a new study method that is under independent case of multiple optical orthogonal codes to derive the probability function of MOOCS-OPS networks, discuss the performance characteristics for a variety of parameters, and compare some characteristics of the system employed by single optical orthogonal code or multiple optical orthogonal codes sequences-based optical labels. The performance of the system is also calculated, and our results verify that the method is effective. Additionally it is found that performance of MOOCS-OPS networks would, negatively, be worsened, compared with single optical orthogonal code-based optical label for optical packet switching (SOOC-OPS); however, MOOCS-OPS networks can greatly enlarge the scalability of optical packet switching networks.

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.

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.

New Parallel computing framework for radiation transport codes

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

Kostin, M.A.; /Michigan State U., NSCL; Mokhov, N.V.

A new parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was integrated with the MARS15 code, and an effort is under way to deploy it in PHITS. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility canmore » be used in single process calculations as well as in the parallel regime. Several checkpoint files can be merged into one thus combining results of several calculations. The framework also corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.« less

Parallelized direct execution simulation of message-passing parallel programs

NASA Technical Reports Server (NTRS)

Dickens, Phillip M.; Heidelberger, Philip; Nicol, David M.

1994-01-01

As massively parallel computers proliferate, there is growing interest in findings ways by which performance of massively parallel codes can be efficiently predicted. This problem arises in diverse contexts such as parallelizing computers, parallel performance monitoring, and parallel algorithm development. In this paper we describe one solution where one directly executes the application code, but uses a discrete-event simulator to model details of the presumed parallel machine such as operating system and communication network behavior. Because this approach is computationally expensive, we are interested in its own parallelization specifically the parallelization of the discrete-event simulator. We describe methods suitable for parallelized direct execution simulation of message-passing parallel programs, and report on the performance of such a system, Large Application Parallel Simulation Environment (LAPSE), we have built on the Intel Paragon. On all codes measured to date, LAPSE predicts performance well typically within 10 percent relative error. Depending on the nature of the application code, we have observed low slowdowns (relative to natively executing code) and high relative speedups using up to 64 processors.

ICD-10 procedure codes produce transition challenges.

PubMed

Boyd, Andrew D; Li, Jianrong 'John'; Kenost, Colleen; Zaim, Samir Rachid; Krive, Jacob; Mittal, Manish; Satava, Richard A; Burton, Michael; Smith, Jacob; Lussier, Yves A

2018-01-01

The transition of procedure coding from ICD-9-CM-Vol-3 to ICD-10-PCS has generated problems for the medical community at large resulting from the lack of clarity required to integrate two non-congruent coding systems. We hypothesized that quantifying these issues with network topology analyses offers a better understanding of the issues, and therefore we developed solutions (online tools) to empower hospital administrators and researchers to address these challenges. Five topologies were identified: "identity"(I), "class-to-subclass"(C2S), "subclass-toclass"(S2C), "convoluted(C)", and "no mapping"(NM). The procedure codes in the 2010 Illinois Medicaid dataset (3,290 patients, 116 institutions) were categorized as C=55%, C2S=40%, I=3%, NM=2%, and S2C=1%. Majority of the problematic and ambiguous mappings (convoluted) pertained to operations in ophthalmology cardiology, urology, gyneco-obstetrics, and dermatology. Finally, the algorithms were expanded into a user-friendly tool to identify problematic topologies and specify lists of procedural codes utilized by medical professionals and researchers for mitigating error-prone translations, simplifying research, and improving quality.http://www.lussiergroup.org/transition-to-ICD10PCS.

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.

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.

Fostering Team Awareness in Earth System Modeling Communities

NASA Astrophysics Data System (ADS)

Easterbrook, S. M.; Lawson, A.; Strong, S.

2009-12-01

Existing Global Climate Models are typically managed and controlled at a single site, with varied levels of participation by scientists outside the core lab. As these models evolve to encompass a wider set of earth systems, this central control of the modeling effort becomes a bottleneck. But such models cannot evolve to become fully distributed open source projects unless they address the imbalance in the availability of communication channels: scientists at the core site have access to regular face-to-face communication with one another, while those at remote sites have access to only a subset of these conversations - e.g. formally scheduled teleconferences and user meetings. Because of this imbalance, critical decision making can be hidden from many participants, their code contributions can interact in unanticipated ways, and the community loses awareness of who knows what. We have documented some of these problems in a field study at one climate modeling centre, and started to develop tools to overcome these problems. We report on one such tool, TracSNAP, which analyzes the social network of the scientists contributing code to the model by extracting the data in an existing project code repository. The tool presents the results of this analysis to modelers and model users in a number of ways: recommendation for who has expertise on particular code modules, suggestions for code sections that are related to files being worked on, and visualizations of team communication patterns. The tool is currently available as a plugin for the Trac bug tracking system.

Analysis of Intelligent Transportation Systems Using Model-Driven Simulations.

PubMed

Fernández-Isabel, Alberto; Fuentes-Fernández, Rubén

2015-06-15

Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use.

Analysis of Intelligent Transportation Systems Using Model-Driven Simulations

PubMed Central

Fernández-Isabel, Alberto; Fuentes-Fernández, Rubén

2015-01-01

Intelligent Transportation Systems (ITSs) integrate information, sensor, control, and communication technologies to provide transport related services. Their users range from everyday commuters to policy makers and urban planners. Given the complexity of these systems and their environment, their study in real settings is frequently unfeasible. Simulations help to address this problem, but present their own issues: there can be unintended mistakes in the transition from models to code; their platforms frequently bias modeling; and it is difficult to compare works that use different models and tools. In order to overcome these problems, this paper proposes a framework for a model-driven development of these simulations. It is based on a specific modeling language that supports the integrated specification of the multiple facets of an ITS: people, their vehicles, and the external environment; and a network of sensors and actuators conveniently arranged and distributed that operates over them. The framework works with a model editor to generate specifications compliant with that language, and a code generator to produce code from them using platform specifications. There are also guidelines to help researchers in the application of this infrastructure. A case study on advanced management of traffic lights with cameras illustrates its use. PMID:26083232

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.

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

Automatic Generation of Algorithms for the Statistical Analysis of Planetary Nebulae Images

NASA Technical Reports Server (NTRS)

Fischer, Bernd

2004-01-01

Analyzing data sets collected in experiments or by observations is a Core scientific activity. Typically, experimentd and observational data are &aught with uncertainty, and the analysis is based on a statistical model of the conjectured underlying processes, The large data volumes collected by modern instruments make computer support indispensible for this. Consequently, scientists spend significant amounts of their time with the development and refinement of the data analysis programs. AutoBayes [GF+02, FS03] is a fully automatic synthesis system for generating statistical data analysis programs. Externally, it looks like a compiler: it takes an abstract problem specification and translates it into executable code. Its input is a concise description of a data analysis problem in the form of a statistical model as shown in Figure 1; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. Internally, however, it is quite different: AutoBayes derives a customized algorithm implementing the given model using a schema-based process, and then further refines and optimizes the algorithm into code. A schema is a parameterized code template with associated semantic constraints which define and restrict the template s applicability. The schema parameters are instantiated in a problem-specific way during synthesis as AutoBayes checks the constraints against the original model or, recursively, against emerging sub-problems. AutoBayes schema library contains problem decomposition operators (which are justified by theorems in a formal logic in the domain of Bayesian networks) as well as machine learning algorithms (e.g., EM, k-Means) and nu- meric optimization methods (e.g., Nelder-Mead simplex, conjugate gradient). AutoBayes augments this schema-based approach by symbolic computation to derive closed-form solutions whenever possible. This is a major advantage over other statistical data analysis systems which use numerical approximations even in cases where closed-form solutions exist. AutoBayes is implemented in Prolog and comprises approximately 75.000 lines of code. In this paper, we take one typical scientific data analysis problem-analyzing planetary nebulae images taken by the Hubble Space Telescope-and show how AutoBayes can be used to automate the implementation of the necessary anal- ysis programs. We initially follow the analysis described by Knuth and Hajian [KHO2] and use AutoBayes to derive code for the published models. We show the details of the code derivation process, including the symbolic computations and automatic integration of library procedures, and compare the results of the automatically generated and manually implemented code. We then go beyond the original analysis and use AutoBayes to derive code for a simple image segmentation procedure based on a mixture model which can be used to automate a manual preproceesing step. Finally, we combine the original approach with the simple segmentation which yields a more detailed analysis. This also demonstrates that AutoBayes makes it easy to combine different aspects of data analysis.

CAVE: A computer code for two-dimensional transient heating analysis of conceptual thermal protection systems for hypersonic vehicles

NASA Technical Reports Server (NTRS)

Rathjen, K. A.

1977-01-01

A digital computer code CAVE (Conduction Analysis Via Eigenvalues), which finds application in the analysis of two dimensional transient heating of hypersonic vehicles is described. The CAVE is written in FORTRAN 4 and is operational on both IBM 360-67 and CDC 6600 computers. The method of solution is a hybrid analytical numerical technique that is inherently stable permitting large time steps even with the best of conductors having the finest of mesh size. The aerodynamic heating boundary conditions are calculated by the code based on the input flight trajectory or can optionally be calculated external to the code and then entered as input data. The code computes the network conduction and convection links, as well as capacitance values, given basic geometrical and mesh sizes, for four generations (leading edges, cooled panels, X-24C structure and slabs). Input and output formats are presented and explained. Sample problems are included. A brief summary of the hybrid analytical-numerical technique, which utilizes eigenvalues (thermal frequencies) and eigenvectors (thermal mode vectors) is given along with aerodynamic heating equations that have been incorporated in the code and flow charts.

State estimation for networked control systems using fixed data rates

NASA Astrophysics Data System (ADS)

Liu, Qing-Quan; Jin, Fang

2017-07-01

This paper investigates state estimation for linear time-invariant systems where sensors and controllers are geographically separated and connected via a bandwidth-limited and errorless communication channel with the fixed data rate. All plant states are quantised, coded and converted together into a codeword in our quantisation and coding scheme. We present necessary and sufficient conditions on the fixed data rate for observability of such systems, and further develop the data-rate theorem. It is shown in our results that there exists a quantisation and coding scheme to ensure observability of the system if the fixed data rate is larger than the lower bound given, which is less conservative than the one in the literature. Furthermore, we also examine the role that the disturbances have on the state estimation problem in the case with data-rate limitations. Illustrative examples are given to demonstrate the effectiveness of the proposed method.

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

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.

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.

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.

L-GRAAL: Lagrangian graphlet-based network aligner.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2015-07-01

Discovering and understanding patterns in networks of protein-protein interactions (PPIs) is a central problem in systems biology. Alignments between these networks aid functional understanding as they uncover important information, such as evolutionary conserved pathways, protein complexes and functional orthologs. A few methods have been proposed for global PPI network alignments, but because of NP-completeness of underlying sub-graph isomorphism problem, producing topologically and biologically accurate alignments remains a challenge. We introduce a novel global network alignment tool, Lagrangian GRAphlet-based ALigner (L-GRAAL), which directly optimizes both the protein and the interaction functional conservations, using a novel alignment search heuristic based on integer programming and Lagrangian relaxation. We compare L-GRAAL with the state-of-the-art network aligners on the largest available PPI networks from BioGRID and observe that L-GRAAL uncovers the largest common sub-graphs between the networks, as measured by edge-correctness and symmetric sub-structures scores, which allow transferring more functional information across networks. We assess the biological quality of the protein mappings using the semantic similarity of their Gene Ontology annotations and observe that L-GRAAL best uncovers functionally conserved proteins. Furthermore, we introduce for the first time a measure of the semantic similarity of the mapped interactions and show that L-GRAAL also uncovers best functionally conserved interactions. In addition, we illustrate on the PPI networks of baker's yeast and human the ability of L-GRAAL to predict new PPIs. Finally, L-GRAAL's results are the first to show that topological information is more important than sequence information for uncovering functionally conserved interactions. L-GRAAL is coded in C++. Software is available at: http://bio-nets.doc.ic.ac.uk/L-GRAAL/. n.malod-dognin@imperial.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

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.

A Datacenter Backstage: The Knowledge that Supports the Brazilian Seismic Network

NASA Astrophysics Data System (ADS)

Calhau, J.; Assumpcao, M.; Collaço, B.; Bianchi, M.; Pirchiner, M.

2015-12-01

Historically, Brazilian seismology never had a clear strategic vision about how its data should be acquired, evaluated, stored and shared. Without a data management plan, data (for any practical purpose) could be lost, resulting in a non-uniform coverage that will reduce any chance of local and international collaboration, i.e., data will never become scientific knowledge. Since 2009, huge efforts from four different institutions are establishing the new permanent Brazilian Seismographic Network (RSBR), mainly with resources from PETROBRAS, the Brazilian Government oil company. Four FDSN sub-networks currently compose RSBR, with a total of 80 permanent stations. BL and BR codes (from BRASIS subnet) with 47 stations maintained by University of Sao Paulo (USP) and University of Brasilia (UnB) respectively; NB code (RSISNE subnet), with 16 stations deployed by University of Rio Grande do Norte (UFRN); and ON code (RSIS subnet), with 18 stations operated by the National Observatory (ON) in Rio de Janeiro. Most stations transmit data in real-time via satellite or cell-phone links. Each node acquires its own stations locally, and data is real-time shared using SeedLink. Archived data is distributed via ArcLink and/or FDSNWS services. All nodes use the SeisComP3 system for real-time processing and as a levering back-end. Open-source solutions like Seiscomp3 require some homemade tools to be developed, to help solve the most common daily problems of a data management center: local magnitude into the real-time earthquake processor, website plugins, regional earthquake catalog, contribution with ISC catalog, quality-control tools, data request tools, etc. The main data products and community activities include: kml files, data availability plots, request charts, summer school courses, an Open Lab Day and news interviews. Finally, a good effort was made to establish BRASIS sub-network and the whole RSBR as a unified project, that serves as a communication channel between individuals operating local networks.

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.

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.

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.

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

Parallel ALLSPD-3D: Speeding Up Combustor Analysis Via Parallel Processing

NASA Technical Reports Server (NTRS)

Fricker, David M.

1997-01-01

The ALLSPD-3D Computational Fluid Dynamics code for reacting flow simulation was run on a set of benchmark test cases to determine its parallel efficiency. These test cases included non-reacting and reacting flow simulations with varying numbers of processors. Also, the tests explored the effects of scaling the simulation with the number of processors in addition to distributing a constant size problem over an increasing number of processors. The test cases were run on a cluster of IBM RS/6000 Model 590 workstations with ethernet and ATM networking plus a shared memory SGI Power Challenge L workstation. The results indicate that the network capabilities significantly influence the parallel efficiency, i.e., a shared memory machine is fastest and ATM networking provides acceptable performance. The limitations of ethernet greatly hamper the rapid calculation of flows using ALLSPD-3D.

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…

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

Reservoir characterization using core, well log, and seismic data and intelligent software

NASA Astrophysics Data System (ADS)

Soto Becerra, Rodolfo

We have developed intelligent software, Oilfield Intelligence (OI), as an engineering tool to improve the characterization of oil and gas reservoirs. OI integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphics design, and inference engine modules. More than 1,200 lines of programming code as M-files using the language MATLAB been written. The degree of success of many oil and gas drilling, completion, and production activities depends upon the accuracy of the models used in a reservoir description. Neural networks have been applied for identification of nonlinear systems in almost all scientific fields of humankind. Solving reservoir characterization problems is no exception. Neural networks have a number of attractive features that can help to extract and recognize underlying patterns, structures, and relationships among data. However, before developing a neural network model, we must solve the problem of dimensionality such as determining dominant and irrelevant variables. We can apply principal components and factor analysis to reduce the dimensionality and help the neural networks formulate more realistic models. We validated OI by obtaining confident models in three different oil field problems: (1) A neural network in-situ stress model using lithology and gamma ray logs for the Travis Peak formation of east Texas, (2) A neural network permeability model using porosity and gamma ray and a neural network pseudo-gamma ray log model using 3D seismic attributes for the reservoir VLE 196 Lamar field located in Block V of south-central Lake Maracaibo (Venezuela), and (3) Neural network primary ultimate oil recovery (PRUR), initial waterflooding ultimate oil recovery (IWUR), and infill drilling ultimate oil recovery (IDUR) models using reservoir parameters for San Andres and Clearfork carbonate formations in west Texas. In all cases, we compared the results from the neural network models with the results from regression statistical and non-parametric approach models. The results show that it is possible to obtain the highest cross-correlation coefficient between predicted and actual target variables, and the lowest average absolute errors using the integrated techniques of multivariate statistical analysis and neural networks in our intelligent software.

Development of Parallel Computing Framework to Enhance Radiation Transport Code Capabilities for Rare Isotope Beam Facility Design

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

Kostin, Mikhail; Mokhov, Nikolai; Niita, Koji

A parallel computing framework has been developed to use with general-purpose radiation transport codes. The framework was implemented as a C++ module that uses MPI for message passing. It is intended to be used with older radiation transport codes implemented in Fortran77, Fortran 90 or C. The module is significantly independent of radiation transport codes it can be used with, and is connected to the codes by means of a number of interface functions. The framework was developed and tested in conjunction with the MARS15 code. It is possible to use it with other codes such as PHITS, FLUKA andmore » MCNP after certain adjustments. Besides the parallel computing functionality, the framework offers a checkpoint facility that allows restarting calculations with a saved checkpoint file. The checkpoint facility can be used in single process calculations as well as in the parallel regime. The framework corrects some of the known problems with the scheduling and load balancing found in the original implementations of the parallel computing functionality in MARS15 and PHITS. The framework can be used efficiently on homogeneous systems and networks of workstations, where the interference from the other users is possible.« less

Time coded distribution via broadcasting stations

NASA Technical Reports Server (NTRS)

Leschiutta, S.; Pettiti, V.; Detoma, E.

1979-01-01

The distribution of standard time signals via AM and FM broadcasting stations presents the distinct advantages to offer a wide area coverage and to allow the use of inexpensive receivers, but the signals are radiated a limited number of times per day, are not usually available during the night, and no full and automatic synchronization of a remote clock is possible. As an attempt to overcome some of these problems, a time coded signal with a complete date information is diffused by the IEN via the national broadcasting networks in Italy. These signals are radiated by some 120 AM and about 3000 FM and TV transmitters around the country. In such a way, a time ordered system with an accuracy of a couple of milliseconds is easily achieved.

Using computer algebra and SMT solvers in algebraic biology

NASA Astrophysics Data System (ADS)

Pineda Osorio, Mateo

2014-05-01

Biologic processes are represented as Boolean networks, in a discrete time. The dynamics within these networks are approached with the help of SMT Solvers and the use of computer algebra. Software such as Maple and Z3 was used in this case. The number of stationary states for each network was calculated. The network studied here corresponds to the immune system under the effects of drastic mood changes. Mood is considered as a Boolean variable that affects the entire dynamics of the immune system, changing the Boolean satisfiability and the number of stationary states of the immune network. Results obtained show Z3's great potential as a SMT Solver. Some of these results were verified in Maple, even though it showed not to be as suitable for the problem approach. The solving code was constructed using Z3-Python and Z3-SMT-LiB. Results obtained are important in biology systems and are expected to help in the design of immune therapies. As a future line of research, more complex Boolean network representations of the immune system as well as the whole psychological apparatus are suggested.

Application of neural networks to software quality modeling of a very large telecommunications system.

PubMed

Khoshgoftaar, T M; Allen, E B; Hudepohl, J P; Aud, S J

1997-01-01

Society relies on telecommunications to such an extent that telecommunications software must have high reliability. Enhanced measurement for early risk assessment of latent defects (EMERALD) is a joint project of Nortel and Bell Canada for improving the reliability of telecommunications software products. This paper reports a case study of neural-network modeling techniques developed for the EMERALD system. The resulting neural network is currently in the prototype testing phase at Nortel. Neural-network models can be used to identify fault-prone modules for extra attention early in development, and thus reduce the risk of operational problems with those modules. We modeled a subset of modules representing over seven million lines of code from a very large telecommunications software system. The set consisted of those modules reused with changes from the previous release. The dependent variable was membership in the class of fault-prone modules. The independent variables were principal components of nine measures of software design attributes. We compared the neural-network model with a nonparametric discriminant model and found the neural-network model had better predictive accuracy.

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.

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

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.

Identification of control targets in Boolean molecular network models via computational algebra.

PubMed

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Spatiotemporal Computations of an Excitable and Plastic Brain: Neuronal Plasticity Leads to Noise-Robust and Noise-Constructive Computations

PubMed Central

Toutounji, Hazem; Pipa, Gordon

2014-01-01

It is a long-established fact that neuronal plasticity occupies the central role in generating neural function and computation. Nevertheless, no unifying account exists of how neurons in a recurrent cortical network learn to compute on temporally and spatially extended stimuli. However, these stimuli constitute the norm, rather than the exception, of the brain's input. Here, we introduce a geometric theory of learning spatiotemporal computations through neuronal plasticity. To that end, we rigorously formulate the problem of neural representations as a relation in space between stimulus-induced neural activity and the asymptotic dynamics of excitable cortical networks. Backed up by computer simulations and numerical analysis, we show that two canonical and widely spread forms of neuronal plasticity, that is, spike-timing-dependent synaptic plasticity and intrinsic plasticity, are both necessary for creating neural representations, such that these computations become realizable. Interestingly, the effects of these forms of plasticity on the emerging neural code relate to properties necessary for both combating and utilizing noise. The neural dynamics also exhibits features of the most likely stimulus in the network's spontaneous activity. These properties of the spatiotemporal neural code resulting from plasticity, having their grounding in nature, further consolidate the biological relevance of our findings. PMID:24651447

A content analysis of displayed alcohol references on a social networking web site.

PubMed

Moreno, Megan A; Briner, Leslie R; Williams, Amanda; Brockman, Libby; Walker, Leslie; Christakis, Dimitri A

2010-08-01

Exposure to alcohol use in media is associated with adolescent alcohol use. Adolescents frequently display alcohol references on Internet media, such as social networking web sites. The purpose of this study was to conduct a theoretically based content analysis of older adolescents' displayed alcohol references on a social networking web site. We evaluated 400 randomly selected public MySpace profiles of self-reported 17- to 20-year-olds from zip codes, representing urban, suburban, and rural communities in one Washington county. Content was evaluated for alcohol references, suggesting: (1) explicit versus figurative alcohol use, (2) alcohol-related motivations, associations, and consequences, including references that met CRAFFT problem drinking criteria. We compared profiles from four target zip codes for prevalence and frequency of alcohol display. Of 400 profiles, 225 (56.3%) contained 341 references to alcohol. Profile owners who displayed alcohol references were mostly male (54.2%) and white (70.7%). The most frequent reference category was explicit use (49.3%); the most commonly displayed alcohol use motivation was peer pressure (4.7%). Few references met CRAFFT problem drinking criteria (3.2%). There were no differences in prevalence or frequency of alcohol display among the four sociodemographic communities. Despite alcohol use being illegal and potentially stigmatizing in this population, explicit alcohol use is frequently referenced on adolescents' MySpace profiles across several sociodemographic communities. Motivations, associations, and consequences regarding alcohol use referenced on MySpace appear consistent with previous studies of adolescent alcohol use. These references may be a potent source of influence on adolescents, particularly given that they are created and displayed by peers. (c) 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

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.

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.

Evolution of a Patient Information Management System in a Local Area Network Environment at Loyola University of Chicago Medical Center

PubMed Central

Price, Ronald N; Chandrasekhar, Arcot J; Tamirisa, Balaji

1990-01-01

The Department of Medicine at Loyola University Medical Center (LUMC) of Chicago has implemented a local area network (LAN) based Patient Information Management System (PIMS) as part of its integrated departmental database management system. PIMS consists of related database applications encompassing demographic information, current medications, problem lists, clinical data, prior events, and on-line procedure results. Integration into the existing departmental database system permits PIMS to capture and manipulate data in other departmental applications. Standardization of clinical data is accomplished through three data tables that verify diagnosis codes, procedures codes and a standardized set of clinical data elements. The modularity of the system, coupled with standardized data formats, allowed the development of a Patient Information Protocol System (PIPS). PIPS, a userdefinable protocol processor, provides physicians with individualized data entry or review screens customized for their specific research protocols or practice habits. Physician feedback indicates that the PIMS/PIPS combination enhances their ability to collect and review specific patient information by filtering large amount of clinical data.

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.

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...

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

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

USGS Publications Warehouse

Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.

2012-01-01

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

ICD-10 procedure codes produce transition challenges

PubMed Central

Boyd, Andrew D.; Li, Jianrong ‘John’; Kenost, Colleen; Zaim, Samir Rachid; Krive, Jacob; Mittal, Manish; Satava, Richard A.; Burton, Michael; Smith, Jacob; Lussier, Yves A.

2018-01-01

The transition of procedure coding from ICD-9-CM-Vol-3 to ICD-10-PCS has generated problems for the medical community at large resulting from the lack of clarity required to integrate two non-congruent coding systems. We hypothesized that quantifying these issues with network topology analyses offers a better understanding of the issues, and therefore we developed solutions (online tools) to empower hospital administrators and researchers to address these challenges. Five topologies were identified: “identity”(I), “class-to-subclass”(C2S), “subclass-toclass”(S2C), “convoluted(C)”, and “no mapping”(NM). The procedure codes in the 2010 Illinois Medicaid dataset (3,290 patients, 116 institutions) were categorized as C=55%, C2S=40%, I=3%, NM=2%, and S2C=1%. Majority of the problematic and ambiguous mappings (convoluted) pertained to operations in ophthalmology cardiology, urology, gyneco-obstetrics, and dermatology. Finally, the algorithms were expanded into a user-friendly tool to identify problematic topologies and specify lists of procedural codes utilized by medical professionals and researchers for mitigating error-prone translations, simplifying research, and improving quality.http://www.lussiergroup.org/transition-to-ICD10PCS PMID:29888037

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

PubMed

Du, Tingsong; Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

PubMed Central

Hu, Yang; Ke, Xianting

2015-01-01

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

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 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.

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)…

Development of Cooperative Communication Techniques for a Network of Small Satellites and Cubesats in Deep Space

NASA Technical Reports Server (NTRS)

Babuscia, Alessandra; Cheung, Kar-Ming; Divsalar, Dariush; Lee, Charles

2014-01-01

This paper aims to address this problem by proposing cooperative communication approaches in which multiple CubeSats communicate cooperatively together to improve the link performance with respect to the case of a single satellite transmitting. Three approaches are proposed: a beam-forming approach, a coding approach, and a network approach. The approaches are applied to the specific case of a proposed constellation of CubeSats at the Lunar Lagrangian point L1 which aims to perform radio astronomy at very low frequencies (30 KHz -3 MHz). The paper describes the development of the approaches, the simulation and a graphical user interface developed in Matlab which allows to perform trade-offs across multiple constellation's configurations.

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.

The solvability of quantum k-pair network in a measurement-based way.

PubMed

Li, Jing; Xu, Gang; Chen, Xiu-Bo; Qu, Zhiguo; Niu, Xin-Xin; Yang, Yi-Xian

2017-12-01

Network coding is an effective means to enhance the communication efficiency. The characterization of network solvability is one of the most important topic in this field. However, for general network, the solvability conditions are still a challenge. In this paper, we consider the solvability of general quantum k-pair network in measurement-based framework. For the first time, a detailed account of measurement-based quantum network coding(MB-QNC) is specified systematically. Differing from existing coding schemes, single qubit measurements on a pre-shared graph state are the only allowed coding operations. Since no control operations are concluded, it makes MB-QNC schemes more feasible. Further, the sufficient conditions formulating by eigenvalue equations and stabilizer matrix are presented, which build an unambiguous relation among the solvability and the general network. And this result can also analyze the feasibility of sharing k EPR pairs task in large-scale networks. Finally, in the presence of noise, we analyze the advantage of MB-QNC in contrast to gate-based way. By an instance network [Formula: see text], we show that MB-QNC allows higher error thresholds. Specially, for X error, the error threshold is about 30% higher than 10% in gate-based way. In addition, the specific expressions of fidelity subject to some constraint conditions are given.

Optimal Near-Hitless Network Failure Recovery Using Diversity Coding

ERIC Educational Resources Information Center

Avci, Serhat Nazim

2013-01-01

Link failures in wide area networks are common and cause significant data losses. Mesh-based protection schemes offer high capacity efficiency but they are slow, require complex signaling, and instable. Diversity coding is a proactive coding-based recovery technique which offers near-hitless (sub-ms) restoration with a competitive spare capacity…

Fundamental differences between optimization code test problems in engineering applications

NASA Technical Reports Server (NTRS)

Eason, E. D.

1984-01-01

The purpose here is to suggest that there is at least one fundamental difference between the problems used for testing optimization codes and the problems that engineers often need to solve; in particular, the level of precision that can be practically achieved in the numerical evaluation of the objective function, derivatives, and constraints. This difference affects the performance of optimization codes, as illustrated by two examples. Two classes of optimization problem were defined. Class One functions and constraints can be evaluated to a high precision that depends primarily on the word length of the computer. Class Two functions and/or constraints can only be evaluated to a moderate or a low level of precision for economic or modeling reasons, regardless of the computer word length. Optimization codes have not been adequately tested on Class Two problems. There are very few Class Two test problems in the literature, while there are literally hundreds of Class One test problems. The relative performance of two codes may be markedly different for Class One and Class Two problems. Less sophisticated direct search type codes may be less likely to be confused or to waste many function evaluations on Class Two problems. The analysis accuracy and minimization performance are related in a complex way that probably varies from code to code. On a problem where the analysis precision was varied over a range, the simple Hooke and Jeeves code was more efficient at low precision while the Powell code was more efficient at high precision.

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.

Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

NASA Technical Reports Server (NTRS)

Stoenescu, Tudor M.; Woo, Simon S.

2009-01-01

In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

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.

A novel all-optical label processing based on multiple optical orthogonal codes sequences for optical packet switching networks

NASA Astrophysics Data System (ADS)

Zhang, Chongfu; Qiu, Kun; Xu, Bo; Ling, Yun

2008-05-01

This paper proposes an all-optical label processing scheme that uses the multiple optical orthogonal codes sequences (MOOCS)-based optical label for optical packet switching (OPS) (MOOCS-OPS) networks. In this scheme, each MOOCS is a permutation or combination of the multiple optical orthogonal codes (MOOC) selected from the multiple-groups optical orthogonal codes (MGOOC). Following a comparison of different optical label processing (OLP) schemes, the principles of MOOCS-OPS network are given and analyzed. Firstly, theoretical analyses are used to prove that MOOCS is able to greatly enlarge the number of available optical labels when compared to the previous single optical orthogonal code (SOOC) for OPS (SOOC-OPS) network. Then, the key units of the MOOCS-based optical label packets, including optical packet generation, optical label erasing, optical label extraction and optical label rewriting etc., are given and studied. These results are used to verify that the proposed MOOCS-OPS scheme is feasible.

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 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.

Sensory coding and cognitive processing of sound in Veterans with blast exposure

PubMed Central

Bressler, Scott; Goldberg, Hannah; Shinn-Cunningham, Barbara

2017-01-01

Recent anecdotal reports from VA audiology clinics as well as a few published studies have identified a sub-population of Service Members seeking treatment for problems communicating in everyday, noisy listening environments despite having normal to near-normal hearing thresholds. Because of their increased risk of exposure to dangerous levels of prolonged noise and transient explosive blast events, communication problems in these soldiers could be due to either hearing loss (traditional or “hidden”) in the auditory sensory periphery or from blast-induced injury to cortical networks associated with attention. We found that out of the 14 blast-exposed Service Members recruited for this study, 12 had hearing thresholds in the normal to near-normal range. A majority of these participants reported having problems specifically related to failures with selective attention. Envelope following responses (EFRs) measuring neural coding fidelity of the auditory brainstem to suprathreshold sounds were similar between blast-exposed and non-blast controls. Blast-exposed subjects performed substantially worse than non-blast controls in an auditory selective attention task in which listeners classified the melodic contour (rising, falling, or “zig-zagging”) of one of three simultaneous, competing tone sequences. Salient pitch and spatial differences made for easy segregation of the three concurrent melodies. Poor performance in the blast-exposed subjects was associated with weaker evoked response potentials (ERPs) in frontal EEG channels, as well as a failure of attention to enhance the neural responses evoked by a sequence when it was the target compared to when it was a distractor. These results suggest that communication problems in these listeners cannot be explained by compromised sensory representations in the auditory periphery, but rather point to lingering blast-induced damage to cortical networks implicated in the control of attention. Because all study participants also suffered from post-traumatic disorder (PTSD), follow-up studies are required to tease apart the contributions of PTSD and blast-induced injury on cognitive performance. PMID:27815131

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.

A neuromorphic network for generic multivariate data classification

PubMed Central

Schmuker, Michael; Pfeil, Thomas; Nawrot, Martin Paul

2014-01-01

Computational neuroscience has uncovered a number of computational principles used by nervous systems. At the same time, neuromorphic hardware has matured to a state where fast silicon implementations of complex neural networks have become feasible. En route to future technical applications of neuromorphic computing the current challenge lies in the identification and implementation of functional brain algorithms. Taking inspiration from the olfactory system of insects, we constructed a spiking neural network for the classification of multivariate data, a common problem in signal and data analysis. In this model, real-valued multivariate data are converted into spike trains using “virtual receptors” (VRs). Their output is processed by lateral inhibition and drives a winner-take-all circuit that supports supervised learning. VRs are conveniently implemented in software, whereas the lateral inhibition and classification stages run on accelerated neuromorphic hardware. When trained and tested on real-world datasets, we find that the classification performance is on par with a naïve Bayes classifier. An analysis of the network dynamics shows that stable decisions in output neuron populations are reached within less than 100 ms of biological time, matching the time-to-decision reported for the insect nervous system. Through leveraging a population code, the network tolerates the variability of neuronal transfer functions and trial-to-trial variation that is inevitably present on the hardware system. Our work provides a proof of principle for the successful implementation of a functional spiking neural network on a configurable neuromorphic hardware system that can readily be applied to real-world computing problems. PMID:24469794

Development Of A Parallel Performance Model For The THOR Neutral Particle Transport Code

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

Yessayan, Raffi; Azmy, Yousry; Schunert, Sebastian

The THOR neutral particle transport code enables simulation of complex geometries for various problems from reactor simulations to nuclear non-proliferation. It is undergoing a thorough V&V requiring computational efficiency. This has motivated various improvements including angular parallelization, outer iteration acceleration, and development of peripheral tools. For guiding future improvements to the code’s efficiency, better characterization of its parallel performance is useful. A parallel performance model (PPM) can be used to evaluate the benefits of modifications and to identify performance bottlenecks. Using INL’s Falcon HPC, the PPM development incorporates an evaluation of network communication behavior over heterogeneous links and a functionalmore » characterization of the per-cell/angle/group runtime of each major code component. After evaluating several possible sources of variability, this resulted in a communication model and a parallel portion model. The former’s accuracy is bounded by the variability of communication on Falcon while the latter has an error on the order of 1%.« less

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.

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.

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.

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

Virtual shelves in a digital library: a framework for access to networked information sources.

PubMed

Patrick, T B; Springer, G K; Mitchell, J A; Sievert, M E

1995-01-01

Develop a framework for collections-based access to networked information sources that addresses the problem of location-dependent access to information sources. This framework uses a metaphor of a virtual shelf. A virtual shelf is a general-purpose server that is dedicated to a particular information subject class. The identifier of one of these servers identifies its subject class. Location-independent call numbers are assigned to information sources. Call numbers are based on standard vocabulary codes. The call numbers are first mapped to the location-independent identifiers of virtual shelves. When access to an information resource is required, a location directory provides a second mapping of these location-independent server identifiers to actual network locations. The framework has been implemented in two different systems. One system is based on the Open System Foundation/Distributed Computing Environment and the other is based on the World Wide Web. This framework applies in new ways traditional methods of library classification and cataloging. It is compatible with two traditional styles of selecting information searching and browsing. Traditional methods may be combined with new paradigms of information searching that will be able to take advantage of the special properties of digital information. Cooperation between the library-informational science community and the informatics community can provide a means for a continuing application of the knowledge and techniques of library science to the new problems of networked information sources.

Development of authentication code for multi-access optical code division multiplexing based quantum key distribution

NASA Astrophysics Data System (ADS)

Taiwo, Ambali; Alnassar, Ghusoon; Bakar, M. H. Abu; Khir, M. F. Abdul; Mahdi, Mohd Adzir; Mokhtar, M.

2018-05-01

One-weight authentication code for multi-user quantum key distribution (QKD) is proposed. The code is developed for Optical Code Division Multiplexing (OCDMA) based QKD network. A unique address assigned to individual user, coupled with degrading probability of predicting the source of the qubit transmitted in the channel offer excellent secure mechanism against any form of channel attack on OCDMA based QKD network. Flexibility in design as well as ease of modifying the number of users are equally exceptional quality presented by the code in contrast to Optical Orthogonal Code (OOC) earlier implemented for the same purpose. The code was successfully applied to eight simultaneous users at effective key rate of 32 bps over 27 km transmission distance.

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

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.

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.

FOURTH SEMINAR TO THE MEMORY OF D.N. KLYSHKO: Algebraic solution of the synthesis problem for coded sequences

NASA Astrophysics Data System (ADS)

Leukhin, Anatolii N.

2005-08-01

The algebraic solution of a 'complex' problem of synthesis of phase-coded (PC) sequences with the zero level of side lobes of the cyclic autocorrelation function (ACF) is proposed. It is shown that the solution of the synthesis problem is connected with the existence of difference sets for a given code dimension. The problem of estimating the number of possible code combinations for a given code dimension is solved. It is pointed out that the problem of synthesis of PC sequences is related to the fundamental problems of discrete mathematics and, first of all, to a number of combinatorial problems, which can be solved, as the number factorisation problem, by algebraic methods by using the theory of Galois fields and groups.

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.

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.

Protograph LDPC Codes Over Burst Erasure Channels

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Dolinar, Sam; Jones, Christopher

2006-01-01

In this paper we design high rate protograph based LDPC codes suitable for binary erasure channels. To simplify the encoder and decoder implementation for high data rate transmission, the structure of codes are based on protographs and circulants. These LDPC codes can improve data link and network layer protocols in support of communication networks. Two classes of codes were designed. One class is designed for large block sizes with an iterative decoding threshold that approaches capacity of binary erasure channels. The other class is designed for short block sizes based on maximizing minimum stopping set size. For high code rates and short blocks the second class outperforms the first class.

Cloudy - simulating the non-equilibrium microphysics of gas and dust, and its observed spectrum

NASA Astrophysics Data System (ADS)

Ferland, Gary J.

2014-01-01

Cloudy is an open-source plasma/spectral simulation code, last described in the open-access journal Revista Mexicana (Ferland et al. 2013, 2013RMxAA..49..137F). The project goal is a complete simulation of the microphysics of gas and dust over the full range of density, temperature, and ionization that we encounter in astrophysics, together with a prediction of the observed spectrum. Cloudy is one of the more widely used theory codes in astrophysics with roughly 200 papers citing its documentation each year. It is developed by graduate students, postdocs, and an international network of collaborators. Cloudy is freely available on the web at trac.nublado.org, the user community can post questions on http://groups.yahoo.com/neo/groups/cloudy_simulations/info, and summer schools are organized to learn more about Cloudy and its use (http://cloud9.pa.uky.edu gary/cloudy/CloudySummerSchool/). The code’s widespread use is possible because of extensive automatic testing. It is exercised over its full range of applicability whenever the source is changed. Changes in predicted quantities are automatically detected along with any newly introduced problems. The code is designed to be autonomous and self-aware. It generates a report at the end of a calculation that summarizes any problems encountered along with suggestions of potentially incorrect boundary conditions. This self-monitoring is a core feature since the code is now often used to generate large MPI grids of simulations, making it impossible for a user to verify each calculation by hand. I will describe some challenges in developing a large physics code, with its many interconnected physical processes, many at the frontier of research in atomic or molecular physics, all in an open environment.

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.

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.

[Study on dilemma and strategy of community support network by community organization for prevention of isolated death in an urban area].

PubMed

Masuda, Yuzuri; Tadaka, Etsuko; Dai, Yuka; Itoi, Waka; Taguchi, Rie; Kawahara, Chie

2011-12-01

Isolated death of elderly is recognized as a severe social problem in public health and it is an urgent requirement that a supportive community network be organized so that its occurrence is minimized. The purpose of this research was to analyze actual issues of a supportive community network for elderly within the community and to obtain clues for useful actions to prevent isolated death of elderly individuals in the future. The subjects were 14 representatives of a supportive community network for elderly in A City, B Ward and C District (as a junior high school segment). The research was conducted with a qualitative inductively approach using the Focus Group Interview (FGI). Interviews were focused on difficulties and perspectives within their daily support activities in the community, and were held three times during October 2009 to March 2010. The FGI records were then analyzed with meaningful minimal words and sentences, categorized codes, and then those codes were classified into subcategories or categories. Three categories, Individual, Neighborhood and Community network for elderly resulted from the analysis. Regarding difficulties, "Refusing supports or indifference", "Isolation or Tojikomori in the youth generation", "Lack of family support", "Relationships among their residents weakening gradually", "Unfamiliar newcomers and residents", "Residence feels burden on association with neighborhood", "Limitation of support activities under personal security", "Lack of resources for persons and places of gathering" were identified. On the other hand, perspectives in the community network for elderly were "Building relationships personally", "Invitation to community meetings as companions", "Development of safety confirmation", "Helping each other in the neighborhood", "Stimulate enforcement of bonding in daily life", "Making arrangements for regional administration and residents for supportive activites", "Fostering the trust and connection of residence". To further promotion and effective activities for community network for elderly by community residents, it is necessary that information be exchanged among resident organizations regarding their activities in achievement of social cooperation.

Gene network polymorphism is the raw material of natural selection: the selfish gene network hypothesis.

PubMed

Boldogköi, Zsolt

2004-09-01

Population genetics, the mathematical theory of modern evolutionary biology, defines evolution as the alteration of the frequency of distinct gene variants (alleles) differing in fitness over the time. The major problem with this view is that in gene and protein sequences we can find little evidence concerning the molecular basis of phenotypic variance, especially those that would confer adaptive benefit to the bearers. Some novel data, however, suggest that a large amount of genetic variation exists in the regulatory region of genes within populations. In addition, comparison of homologous DNA sequences of various species shows that evolution appears to depend more strongly on gene expression than on the genes themselves. Furthermore, it has been demonstrated in several systems that genes form functional networks, whose products exhibit interrelated expression profiles. Finally, it has been found that regulatory circuits of development behave as evolutionary units. These data demonstrate that our view of evolution calls for a new synthesis. In this article I propose a novel concept, termed the selfish gene network hypothesis, which is based on an overall consideration of the above findings. The major statements of this hypothesis are as follows. (1) Instead of individual genes, gene networks (GNs) are responsible for the determination of traits and behaviors. (2) The primary source of microevolution is the intraspecific polymorphism in GNs and not the allelic variation in either the coding or the regulatory sequences of individual genes. (3) GN polymorphism is generated by the variation in the regulatory regions of the component genes and not by the variance in their coding sequences. (4) Evolution proceeds through continuous restructuring of the composition of GNs rather than fixing of specific alleles or GN variants.

Clinical results of HIS, RIS, PACS integration using data integration CASE tools

NASA Astrophysics Data System (ADS)

Taira, Ricky K.; Chan, Hing-Ming; Breant, Claudine M.; Huang, Lu J.; Valentino, Daniel J.

1995-05-01

Current infrastructure research in PACS is dominated by the development of communication networks (local area networks, teleradiology, ATM networks, etc.), multimedia display workstations, and hierarchical image storage architectures. However, limited work has been performed on developing flexible, expansible, and intelligent information processing architectures for the vast decentralized image and text data repositories prevalent in healthcare environments. Patient information is often distributed among multiple data management systems. Current large-scale efforts to integrate medical information and knowledge sources have been costly with limited retrieval functionality. Software integration strategies to unify distributed data and knowledge sources is still lacking commercially. Systems heterogeneity (i.e., differences in hardware platforms, communication protocols, database management software, nomenclature, etc.) is at the heart of the problem and is unlikely to be standardized in the near future. In this paper, we demonstrate the use of newly available CASE (computer- aided software engineering) tools to rapidly integrate HIS, RIS, and PACS information systems. The advantages of these tools include fast development time (low-level code is generated from graphical specifications), and easy system maintenance (excellent documentation, easy to perform changes, and centralized code repository in an object-oriented database). The CASE tools are used to develop and manage the `middle-ware' in our client- mediator-serve architecture for systems integration. Our architecture is scalable and can accommodate heterogeneous database and communication protocols.

Semantic graphs and associative memories

NASA Astrophysics Data System (ADS)

Pomi, Andrés; Mizraji, Eduardo

2004-12-01

Graphs have been increasingly utilized in the characterization of complex networks from diverse origins, including different kinds of semantic networks. Human memories are associative and are known to support complex semantic nets; these nets are represented by graphs. However, it is not known how the brain can sustain these semantic graphs. The vision of cognitive brain activities, shown by modern functional imaging techniques, assigns renewed value to classical distributed associative memory models. Here we show that these neural network models, also known as correlation matrix memories, naturally support a graph representation of the stored semantic structure. We demonstrate that the adjacency matrix of this graph of associations is just the memory coded with the standard basis of the concept vector space, and that the spectrum of the graph is a code invariant of the memory. As long as the assumptions of the model remain valid this result provides a practical method to predict and modify the evolution of the cognitive dynamics. Also, it could provide us with a way to comprehend how individual brains that map the external reality, almost surely with different particular vector representations, are nevertheless able to communicate and share a common knowledge of the world. We finish presenting adaptive association graphs, an extension of the model that makes use of the tensor product, which provides a solution to the known problem of branching in semantic nets.

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.

A network coding based routing protocol for underwater sensor networks.

PubMed

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.

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

RIACS

NASA Technical Reports Server (NTRS)

Oliger, Joseph

1997-01-01

Topics considered include: high-performance computing; cognitive and perceptual prostheses (computational aids designed to leverage human abilities); autonomous systems. Also included: development of a 3D unstructured grid code based on a finite volume formulation and applied to the Navier-stokes equations; Cartesian grid methods for complex geometry; multigrid methods for solving elliptic problems on unstructured grids; algebraic non-overlapping domain decomposition methods for compressible fluid flow problems on unstructured meshes; numerical methods for the compressible navier-stokes equations with application to aerodynamic flows; research in aerodynamic shape optimization; S-HARP: a parallel dynamic spectral partitioner; numerical schemes for the Hamilton-Jacobi and level set equations on triangulated domains; application of high-order shock capturing schemes to direct simulation of turbulence; multicast technology; network testbeds; supercomputer consolidation project.

CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways.

PubMed

Abaka, Gamze; Bıyıkoğlu, Türker; Erten, Cesim

2013-07-01

Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Supplementary data are available at Bioinformatics online.

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.

The WorkPlace distributed processing environment

NASA Technical Reports Server (NTRS)

Ames, Troy; Henderson, Scott

1993-01-01

Real time control problems require robust, high performance solutions. Distributed computing can offer high performance through parallelism and robustness through redundancy. Unfortunately, implementing distributed systems with these characteristics places a significant burden on the applications programmers. Goddard Code 522 has developed WorkPlace to alleviate this burden. WorkPlace is a small, portable, embeddable network interface which automates message routing, failure detection, and re-configuration in response to failures in distributed systems. This paper describes the design and use of WorkPlace, and its application in the construction of a distributed blackboard system.

Noninvasive fetal QRS detection using an echo state network and dynamic programming.

PubMed

Lukoševičius, Mantas; Marozas, Vaidotas

2014-08-01

We address a classical fetal QRS detection problem from abdominal ECG recordings with a data-driven statistical machine learning approach. Our goal is to have a powerful, yet conceptually clean, solution. There are two novel key components at the heart of our approach: an echo state recurrent neural network that is trained to indicate fetal QRS complexes, and several increasingly sophisticated versions of statistics-based dynamic programming algorithms, which are derived from and rooted in probability theory. We also employ a standard technique for preprocessing and removing maternal ECG complexes from the signals, but do not take this as the main focus of this work. The proposed approach is quite generic and can be extended to other types of signals and annotations. Open-source code is provided.

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.

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.

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.

Performance Analysis of MIMO Relay Network via Propagation Measurement in L-Shaped Corridor Environment

NASA Astrophysics Data System (ADS)

Lertwiram, Namzilp; Tran, Gia Khanh; Mizutani, Keiichi; Sakaguchi, Kei; Araki, Kiyomichi

Setting relays can address the shadowing problem between a transmitter (Tx) and a receiver (Rx). Moreover, the Multiple-Input Multiple-Output (MIMO) technique has been introduced to improve wireless link capacity. The MIMO technique can be applied in relay network to enhance system performance. However, the efficiency of relaying schemes and relay placement have not been well investigated with experiment-based study. This paper provides a propagation measurement campaign of a MIMO two-hop relay network in 5GHz band in an L-shaped corridor environment with various relay locations. Furthermore, this paper proposes a Relay Placement Estimation (RPE) scheme to identify the optimum relay location, i.e. the point at which the network performance is highest. Analysis results of channel capacity show that relaying technique is beneficial over direct transmission in strong shadowing environment while it is ineffective in non-shadowing environment. In addition, the optimum relay location estimated with the RPE scheme also agrees with the location where the network achieves the highest performance as identified by network capacity. Finally, the capacity analysis shows that two-way MIMO relay employing network coding has the best performance while cooperative relaying scheme is not effective due to shadowing effect weakening the signal strength of the direct link.

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data

PubMed Central

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks. PMID:29706880

A Dictionary Learning Approach for Signal Sampling in Task-Based fMRI for Reduction of Big Data.

PubMed

Ge, Bao; Li, Xiang; Jiang, Xi; Sun, Yifei; Liu, Tianming

2018-01-01

The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing structurally-guided dictionary learning and sparse coding of whole brain's fMRI data. We compared the proposed structurally guided sampling method with no sampling, random sampling and uniform sampling schemes, and experiments on the Human Connectome Project (HCP) task fMRI data demonstrated that the proposed method can achieve more than 15 times speed-up without sacrificing the accuracy in identifying task-evoked functional brain networks.

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.

Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks

PubMed Central

Guo, Wenzhong; Xiong, Naixue; Chao, Han-Chieh; Hussain, Sajid; Chen, Guolong

2011-01-01

In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms. PMID:22163971

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

Parallel computing for probabilistic fatigue analysis

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Lua, Yuan J.; Smith, Mark D.

1993-01-01

This paper presents the results of Phase I research to investigate the most effective parallel processing software strategies and hardware configurations for probabilistic structural analysis. We investigate the efficiency of both shared and distributed-memory architectures via a probabilistic fatigue life analysis problem. We also present a parallel programming approach, the virtual shared-memory paradigm, that is applicable across both types of hardware. Using this approach, problems can be solved on a variety of parallel configurations, including networks of single or multiprocessor workstations. We conclude that it is possible to effectively parallelize probabilistic fatigue analysis codes; however, special strategies will be needed to achieve large-scale parallelism to keep large number of processors busy and to treat problems with the large memory requirements encountered in practice. We also conclude that distributed-memory architecture is preferable to shared-memory for achieving large scale parallelism; however, in the future, the currently emerging hybrid-memory architectures will likely be optimal.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

This research program deals with the application of high-performance computing methods for the analysis of complete jet engines. We have entitled this program by applying the two dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition, and solution capabilities were successfully tested. We then focused attention on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion that results from these structural displacements. This is treated by a new arbitrary Lagrangian-Eulerian (ALE) technique that models the fluid mesh motion as that of a fictitious mass-spring network. New partitioned analysis procedures to treat this coupled three-component problem are developed. These procedures involved delayed corrections and subcycling. Preliminary results on the stability, accuracy, and MPP computational efficiency are reported.

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

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

Simulation of networks of spiking neurons: A review of tools and strategies

PubMed Central

Brette, Romain; Rudolph, Michelle; Carnevale, Ted; Hines, Michael; Beeman, David; Bower, James M.; Diesmann, Markus; Morrison, Abigail; Goodman, Philip H.; Harris, Frederick C.; Zirpe, Milind; Natschläger, Thomas; Pecevski, Dejan; Ermentrout, Bard; Djurfeldt, Mikael; Lansner, Anders; Rochel, Olivier; Vieville, Thierry; Muller, Eilif; Davison, Andrew P.; El Boustani, Sami

2009-01-01

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin–Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks. PMID:17629781

Multichannel Networked Phasemeter Readout and Analysis

NASA Technical Reports Server (NTRS)

Edmonds, Karina

2008-01-01

Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

Standardized Definitions for Code Verification Test Problems

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

Doebling, Scott William

This document contains standardized definitions for several commonly used code verification test problems. These definitions are intended to contain sufficient information to set up the test problem in a computational physics code. These definitions are intended to be used in conjunction with exact solutions to these problems generated using Exact- Pack, www.github.com/lanl/exactpack.

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.

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.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

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

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.

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 Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes

PubMed Central

Zhang, Ying; Chen, Wei; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming

2015-01-01

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes’ mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network. PMID:26633405

A Network Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes.

PubMed

Zhang, Ying; Chen, Wei; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming

2015-12-01

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes' mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network.

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

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.

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.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks.

PubMed

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-10-09

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms.

Joint Power Charging and Routing in Wireless Rechargeable Sensor Networks

PubMed Central

Jia, Jie; Chen, Jian; Deng, Yansha; Wang, Xingwei; Aghvami, Abdol-Hamid

2017-01-01

The development of wireless power transfer (WPT) technology has inspired the transition from traditional battery-based wireless sensor networks (WSNs) towards wireless rechargeable sensor networks (WRSNs). While extensive efforts have been made to improve charging efficiency, little has been done for routing optimization. In this work, we present a joint optimization model to maximize both charging efficiency and routing structure. By analyzing the structure of the optimization model, we first decompose the problem and propose a heuristic algorithm to find the optimal charging efficiency for the predefined routing tree. Furthermore, by coding the many-to-one communication topology as an individual, we further propose to apply a genetic algorithm (GA) for the joint optimization of both routing and charging. The genetic operations, including tree-based recombination and mutation, are proposed to obtain a fast convergence. Our simulation results show that the heuristic algorithm reduces the number of resident locations and the total moving distance. We also show that our proposed algorithm achieves a higher charging efficiency compared with existing algorithms. PMID:28991200

STBC AF relay for unmanned aircraft system

NASA Astrophysics Data System (ADS)

Adachi, Fumiyuki; Miyazaki, Hiroyuki; Endo, Chikara

2015-01-01

If a large scale disaster similar to the Great East Japan Earthquake 2011 happens, some areas may be isolated from the communications network. Recently, unmanned aircraft system (UAS) based wireless relay communication has been attracting much attention since it is able to quickly re-establish the connection between isolated areas and the network. However, the channel between ground station (GS) and unmanned aircraft (UA) is unreliable due to UA's swing motion and as consequence, the relay communication quality degrades. In this paper, we introduce space-time block coded (STBC) amplify-and-forward (AF) relay for UAS based wireless relay communication to improve relay communication quality. A group of UAs forms single frequency network (SFN) to perform STBC-AF cooperative relay. In STBC-AF relay, only conjugate operation, block exchange and amplifying are required at UAs. Therefore, STBC-AF relay improves the relay communication quality while alleviating the complexity problem at UAs. It is shown by computer simulation that STBC-AF relay can achieve better throughput performance than conventional AF relay.

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.

Virtual shelves in a digital library: a framework for access to networked information sources.

PubMed Central

Patrick, T B; Springer, G K; Mitchell, J A; Sievert, M E

1995-01-01

OBJECTIVE: Develop a framework for collections-based access to networked information sources that addresses the problem of location-dependent access to information sources. DESIGN: This framework uses a metaphor of a virtual shelf. A virtual shelf is a general-purpose server that is dedicated to a particular information subject class. The identifier of one of these servers identifies its subject class. Location-independent call numbers are assigned to information sources. Call numbers are based on standard vocabulary codes. The call numbers are first mapped to the location-independent identifiers of virtual shelves. When access to an information resource is required, a location directory provides a second mapping of these location-independent server identifiers to actual network locations. RESULTS: The framework has been implemented in two different systems. One system is based on the Open System Foundation/Distributed Computing Environment and the other is based on the World Wide Web. CONCLUSIONS: This framework applies in new ways traditional methods of library classification and cataloging. It is compatible with two traditional styles of selecting information searching and browsing. Traditional methods may be combined with new paradigms of information searching that will be able to take advantage of the special properties of digital information. Cooperation between the library-informational science community and the informatics community can provide a means for a continuing application of the knowledge and techniques of library science to the new problems of networked information sources. PMID:8581554

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.

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.

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.

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%.

Engineering large-scale agent-based systems with consensus

NASA Technical Reports Server (NTRS)

Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.

1994-01-01

The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.

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.

Benchmarking the SPHINX and CTH shock physics codes for three problems in ballistics

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

Wilson, L.T.; Hertel, E.; Schwalbe, L.

1998-02-01

The CTH Eulerian hydrocode, and the SPHINX smooth particle hydrodynamics (SPH) code were used to model a shock tube, two long rod penetrations into semi-infinite steel targets, and a long rod penetration into a spaced plate array. The results were then compared to experimental data. Both SPHINX and CTH modeled the one-dimensional shock tube problem well. Both codes did a reasonable job in modeling the outcome of the axisymmetric rod impact problem. Neither code correctly reproduced the depth of penetration in both experiments. In the 3-D problem, both codes reasonably replicated the penetration of the rod through the first plate.more » After this, however, the predictions of both codes began to diverge from the results seen in the experiment. In terms of computer resources, the run times are problem dependent, and are discussed in the text.« less

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.

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.

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.

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

Speech coding and compression using wavelets and lateral inhibitory networks

NASA Astrophysics Data System (ADS)

Ricart, Richard

1990-12-01

The purpose of this thesis is to introduce the concept of lateral inhibition as a generalized technique for compressing time/frequency representations of electromagnetic and acoustical signals, particularly speech. This requires at least a rudimentary treatment of the theory of frames- which generalizes most commonly known time/frequency distributions -the biology of hearing, and digital signal processing. As such, this material, along with the interrelationships of the disparate subjects, is presented in a tutorial style. This may leave the mathematician longing for more rigor, the neurophysiological psychologist longing for more substantive support of the hypotheses presented, and the engineer longing for a reprieve from the theoretical barrage. Despite the problems that arise when trying to appeal to too wide an audience, this thesis should be a cogent analysis of the compression of time/frequency distributions via lateral inhibitory networks.

Recognition of an obstacle in a flow using artificial neural networks.

PubMed

Carrillo, Mauricio; Que, Ulices; González, José A; López, Carlos

2017-08-01

In this work a series of artificial neural networks (ANNs) has been developed with the capacity to estimate the size and location of an obstacle obstructing the flow in a pipe. The ANNs learn the size and location of the obstacle by reading the profiles of the dynamic pressure q or the x component of the velocity v_{x} of the fluid at a certain distance from the obstacle. Data to train the ANN were generated using numerical simulations with a two-dimensional lattice Boltzmann code. We analyzed various cases varying both the diameter and the position of the obstacle on the y axis, obtaining good estimations using the R^{2} coefficient for the cases under study. Although the ANN showed problems with the classification of very small obstacles, the general results show a very good capacity for prediction.

Using network technology for studying the ionosphere

NASA Astrophysics Data System (ADS)

Yasyukevich, Yury; Zhivetiev, Ilya

2015-09-01

One of the key problems of ionosphere physics is the coupling between different ionospheric regions. We apply networks technology for studying the coupling of changing ionospheric dynamics in different regions. We used data from global ionosphere maps (GIM) of total electron content (TEC) produced by CODE for 2005-2010. Distribution of cross-correlation function maxima of TEC variations is not simple. This distribution allows us to reveal two levels of ionosphere coupling: "strong" (r>0.9) and "weak" (r>0.72). The ionosphere of the Arctic region upper 50° magnetic latitude is characterized by a "strong" coupling. In the Southern hemisphere, a similar region is bigger. "Weak" coupling is typical for the whole Southern hemisphere. In North America there is an area where TEC dynamics is "strongly" correlated inside and is not correlated with other ionospheric regions.

TOUGH Simulations of the Updegraff's Set of Fluid and Heat Flow Problems

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

Moridis, G.J.; Pruess

1992-11-01

The TOUGH code [Pruess, 1987] for two-phase flow of water, air, and heat in penneable media has been exercised on a suite of test problems originally selected and simulated by C. D. Updegraff [1989]. These include five 'verification' problems for which analytical or numerical solutions are available, and three 'validation' problems that model laboratory fluid and heat flow experiments. All problems could be run without any code modifications (*). Good and efficient numerical performance, as well as accurate results were obtained throughout. Additional code verification and validation problems from the literature are briefly summarized, and suggestions are given for propermore » applications of TOUGH and related codes.« less

A Project for Developing an Original Methodology Intended for Determination of the River Basin/Sub-Basin Boundaries and Codes in Western Mediterranean Basin in Turkey with Perspective of European Union Directives

NASA Astrophysics Data System (ADS)

Gökgöz, Türkay; Ozulu, Murat; Erdoǧan, Mustafa; Seyrek, Kemal

2016-04-01

From the view of integrated river basin management, basin/sub-basin boundaries should be determined and encoded systematically with sufficient accuracy and precision. Today basin/sub-basin boundaries are mostly derived from digital elevation models (DEM) in geographic information systems (GIS). The accuracy and precision of the basin/sub-basin boundaries depend primarily on the accuracy and resolution of the DEMs. In this regard, in Turkey, a survey was made for the first time within the scope of this project to identify current situation, problems and needs in General Directorates of State Hydraulic Works, Water Management, Forestry, Meteorology, Combating Desertification and Erosion, which are the major institutions with responsibility and authority. Another factor that determines the accuracy and precision of basin/sub-basin boundaries is the flow accumulation threshold value to be determined at a certain stage according to a specific methodology in deriving the basin/sub-basin boundaries from DEM. Generally, in Turkey, either the default value given by GIS tool is used directly without any geomorphological, hydrological and cartographic bases or it is determined by trial and error. Although there is a system of catchments and rivers network at 1:250,000 scale and a proper method has already been developed on systematic coding of the basin by the General Directorate of State Hydraulic Works, it is stated that a new system of catchments, rivers network and coding at larger scale (i.e. 1:25,000) is needed. In short, the basin/sub-basin boundaries and codes are not available currently at the required accuracy and precision for the fulfilment of the obligations described in European Union (EU) Water Framework Directive (WFD). In this case, it is clear that there is not yet any methodology to obtain such products. However, a series of projects should be completed such that the basin/sub-basin boundaries and codes are the fundamental data infrastructure. This task must be accomplished by the end of the negotiation process with the EU. For these reasons this subject is chosen as primary and important goal in this project issue and it is aimed to develop an original methodology for determining the boundaries and codes of the drainage basins/sub-basins at required accuracy and precision for the fulfilment of obligations described in the WFD. In Turkey, existing highest accuracy and reliable elevation and hydrography data will be used for the first time, in this project. Along with the widely known and used flow accumulation threshold approaches, the approach developed by Gökgöz et al. (2006) will be used as well. The practicability and suitability of the encoding method developed by the General Directorate of State Hydraulic Works and the Infrastructure for Spatial Information in Europe will be verified respectively. The resulting drainage network, basin/sub-basin boundaries and codes will be compared to CCM2 (Catchment Characterisation and Modelling), ECRINS1.5 (European Catchments and Rivers Network System) and Catchments and Rivers Network System of General Directorates of State Hydraulic Works. This project is being supported by The Scientific and Technological Research Council of Turkey, under the project number TUBITAK-115Y411.

The bioelectric code: An ancient computational medium for dynamic control of growth and form.

PubMed

Levin, Michael; Martyniuk, Christopher J

2018-02-01

What determines large-scale anatomy? DNA does not directly specify geometrical arrangements of tissues and organs, and a process of encoding and decoding for morphogenesis is required. Moreover, many species can regenerate and remodel their structure despite drastic injury. The ability to obtain the correct target morphology from a diversity of initial conditions reveals that the morphogenetic code implements a rich system of pattern-homeostatic processes. Here, we describe an important mechanism by which cellular networks implement pattern regulation and plasticity: bioelectricity. All cells, not only nerves and muscles, produce and sense electrical signals; in vivo, these processes form bioelectric circuits that harness individual cell behaviors toward specific anatomical endpoints. We review emerging progress in reading and re-writing anatomical information encoded in bioelectrical states, and discuss the approaches to this problem from the perspectives of information theory, dynamical systems, and computational neuroscience. Cracking the bioelectric code will enable much-improved control over biological patterning, advancing basic evolutionary developmental biology as well as enabling numerous applications in regenerative medicine and synthetic bioengineering. Copyright © 2017 Elsevier B.V. All rights reserved.

Theoretical evaluation of a V/STOL fighter model utilizing the PAN AIR code

NASA Technical Reports Server (NTRS)

Howell, G. A.; Bhateley, I. C.

1982-01-01

The PAN AIR computer code was investigated as a tool for predicting closely coupled aerodynamic and propulsive flowfields of arbitrary configurations. The NASA/Ames V/STOL fighter model, a configuration of complex geometry, was analyzed with the PAN AIR code. A successful solution for this configuration was obtained when the nozzle exit was treated as an impermeable surface and no wakes were included around the nozzle exit. When separated flow was simulated from the end of the nacelle, requiring the use of wake networks emanating from the nozzle exit, a number of problems were encountered. A circular body nacelle model was used to investigate various techniques for simulating the exhaust plume in PAN AIR. Several approaches were tested and eliminated because they could not correctly simulate the interference effects. Only one plume modeling technique gave good results. A PAN AIR computation that used a plume shape and inflow velocities obtained from the Navier-Stokes solution for the plume produced results for the effects of power that compared well with experimental data.

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

Multiple description distributed image coding with side information for mobile wireless transmission

NASA Astrophysics Data System (ADS)

Wu, Min; Song, Daewon; Chen, Chang Wen

2005-03-01

Multiple description coding (MDC) is a source coding technique that involves coding the source information into multiple descriptions, and then transmitting them over different channels in packet network or error-prone wireless environment to achieve graceful degradation if parts of descriptions are lost at the receiver. In this paper, we proposed a multiple description distributed wavelet zero tree image coding system for mobile wireless transmission. We provide two innovations to achieve an excellent error resilient capability. First, when MDC is applied to wavelet subband based image coding, it is possible to introduce correlation between the descriptions in each subband. We consider using such a correlation as well as potentially error corrupted description as side information in the decoding to formulate the MDC decoding as a Wyner Ziv decoding problem. If only part of descriptions is lost, however, their correlation information is still available, the proposed Wyner Ziv decoder can recover the description by using the correlation information and the error corrupted description as side information. Secondly, in each description, single bitstream wavelet zero tree coding is very vulnerable to the channel errors. The first bit error may cause the decoder to discard all subsequent bits whether or not the subsequent bits are correctly received. Therefore, we integrate the multiple description scalar quantization (MDSQ) with the multiple wavelet tree image coding method to reduce error propagation. We first group wavelet coefficients into multiple trees according to parent-child relationship and then code them separately by SPIHT algorithm to form multiple bitstreams. Such decomposition is able to reduce error propagation and therefore improve the error correcting capability of Wyner Ziv decoder. Experimental results show that the proposed scheme not only exhibits an excellent error resilient performance but also demonstrates graceful degradation over the packet loss rate.

Development of the ICD-10 simplified version and field test.

PubMed

Paoin, Wansa; Yuenyongsuwan, Maliwan; Yokobori, Yukiko; Endo, Hiroyoshi; Kim, Sukil

2018-05-01

The International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) has been used in various Asia-Pacific countries for more than 20 years. Although ICD-10 is a powerful tool, clinical coding processes are complex; therefore, many developing countries have not been able to implement ICD-10-based health statistics (WHO-FIC APN, 2007). This study aimed to simplify ICD-10 clinical coding processes, to modify index terms to facilitate computer searching and to provide a simplified version of ICD-10 for use in developing countries. The World Health Organization Family of International Classifications Asia-Pacific Network (APN) developed a simplified version of the ICD-10 and conducted field testing in Cambodia during February and March 2016. Ten hospitals were selected to participate. Each hospital sent a team to join a training workshop before using the ICD-10 simplified version to code 100 cases. All hospitals subsequently sent their coded records to the researchers. Overall, there were 1038 coded records with a total of 1099 ICD clinical codes assigned. The average accuracy rate was calculated as 80.71% (66.67-93.41%). Three types of clinical coding errors were found. These related to errors relating to the coder (14.56%), those resulting from the physician documentation (1.27%) and those considered system errors (3.46%). The field trial results demonstrated that the APN ICD-10 simplified version is feasible for implementation as an effective tool to implement ICD-10 clinical coding for hospitals. Developing countries may consider adopting the APN ICD-10 simplified version for ICD-10 code assignment in hospitals and health care centres. The simplified version can be viewed as an introductory tool which leads to the implementation of the full ICD-10 and may support subsequent ICD-11 adoption.

SpineCreator: a Graphical User Interface for the Creation of Layered Neural Models.

PubMed

Cope, A J; Richmond, P; James, S S; Gurney, K; Allerton, D J

2017-01-01

There is a growing requirement in computational neuroscience for tools that permit collaborative model building, model sharing, combining existing models into a larger system (multi-scale model integration), and are able to simulate models using a variety of simulation engines and hardware platforms. Layered XML model specification formats solve many of these problems, however they are difficult to write and visualise without tools. Here we describe a new graphical software tool, SpineCreator, which facilitates the creation and visualisation of layered models of point spiking neurons or rate coded neurons without requiring the need for programming. We demonstrate the tool through the reproduction and visualisation of published models and show simulation results using code generation interfaced directly into SpineCreator. As a unique application for the graphical creation of neural networks, SpineCreator represents an important step forward for neuronal modelling.

Genomics-Based Security Protocols: From Plaintext to Cipherprotein

NASA Technical Reports Server (NTRS)

Shaw, Harry; Hussein, Sayed; Helgert, Hermann

2011-01-01

The evolving nature of the internet will require continual advances in authentication and confidentiality protocols. Nature provides some clues as to how this can be accomplished in a distributed manner through molecular biology. Cryptography and molecular biology share certain aspects and operations that allow for a set of unified principles to be applied to problems in either venue. A concept for developing security protocols that can be instantiated at the genomics level is presented. A DNA (Deoxyribonucleic acid) inspired hash code system is presented that utilizes concepts from molecular biology. It is a keyed-Hash Message Authentication Code (HMAC) capable of being used in secure mobile Ad hoc networks. It is targeted for applications without an available public key infrastructure. Mechanics of creating the HMAC are presented as well as a prototype HMAC protocol architecture. Security concepts related to the implementation differences between electronic domain security and genomics domain security are discussed.

Aeroelasticity of morphing wings using neural networks

NASA Astrophysics Data System (ADS)

Natarajan, Anand

In this dissertation, neural networks are designed to effectively model static non-linear aeroelastic problems in adaptive structures and linear dynamic aeroelastic systems with time varying stiffness. The use of adaptive materials in aircraft wings allows for the change of the contour or the configuration of a wing (morphing) in flight. The use of smart materials, to accomplish these deformations, can imply that the stiffness of the wing with a morphing contour changes as the contour changes. For a rapidly oscillating body in a fluid field, continuously adapting structural parameters may render the wing to behave as a time variant system. Even the internal spars/ribs of the aircraft wing which define the wing stiffness can be made adaptive, that is, their stiffness can be made to vary with time. The immediate effect on the structural dynamics of the wing, is that, the wing motion is governed by a differential equation with time varying coefficients. The study of this concept of a time varying torsional stiffness, made possible by the use of active materials and adaptive spars, in the dynamic aeroelastic behavior of an adaptable airfoil is performed here. Another type of aeroelastic problem of an adaptive structure that is investigated here, is the shape control of an adaptive bump situated on the leading edge of an airfoil. Such a bump is useful in achieving flow separation control for lateral directional maneuverability of the aircraft. Since actuators are being used to create this bump on the wing surface, the energy required to do so needs to be minimized. The adverse pressure drag as a result of this bump needs to be controlled so that the loss in lift over the wing is made minimal. The design of such a "spoiler bump" on the surface of the airfoil is an optimization problem of maximizing pressure drag due to flow separation while minimizing the loss in lift and energy required to deform the bump. One neural network is trained using the CFD code FLUENT to represent the aerodynamic loading over the bump. A second neural network is trained for calculating the actuator loads, bump displacement and lift, drag forces over the airfoil using the finite element solver, ANSYS and the previously trained neural network. This non-linear aeroelastic model of the deforming bump on an airfoil surface using neural networks can serve as a fore-runner for other non-linear aeroelastic problems.

A border-ownership model based on computational electromagnetism.

PubMed

Zainal, Zaem Arif; Satoh, Shunji

2018-03-01

The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the side of the object: so-called border ownership (BO). BO coding is a key process for extracting the objects from the background, allowing one to organize a cluttered scene. We propose that the problem is solvable simultaneously by application of a theorem of electromagnetism, i.e., "conservative vector fields have zero rotation, or "curl." We hypothesize that (i) the BO signal is definable as a vector electric field with arrowheads pointing to the inner side of perceived objects, and (ii) its corresponding scalar field carries information related to perceived order in depth of occluding/occluded objects. A simple model was developed based on this computational theory. Model results qualitatively agree with object-side selectivity of BO-coding neurons, and with perceptions of object order. The model update rule can be reproduced as a plausible neural network that presents new interpretations of existing physiological results. Results of this study also suggest that T-junction detectors are unnecessary to calculate depth order. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

GOMA 6.0 :

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

Schunk, Peter Randall; Rao, Rekha Ranjana; Chen, Ken S

Goma 6.0 is a finite element program which excels in analyses of multiphysical processes, particularly those involving the major branches of mechanics (viz. fluid/solid mechanics, energy transport and chemical species transport). Goma is based on a full-Newton-coupled algorithm which allows for simultaneous solution of the governing principles, making the code ideally suited for problems involving closely coupled bulk mechanics and interfacial phenomena. Example applications include, but are not limited to, coating and polymer processing flows, super-alloy processing, welding/soldering, electrochemical processes, and solid-network or solution film drying. This document serves as a users guide and reference.

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.

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.

Joint Source-Channel Decoding of Variable-Length Codes with Soft Information: A Survey

NASA Astrophysics Data System (ADS)

Guillemot, Christine; Siohan, Pierre

2005-12-01

Multimedia transmission over time-varying wireless channels presents a number of challenges beyond existing capabilities conceived so far for third-generation networks. Efficient quality-of-service (QoS) provisioning for multimedia on these channels may in particular require a loosening and a rethinking of the layer separation principle. In that context, joint source-channel decoding (JSCD) strategies have gained attention as viable alternatives to separate decoding of source and channel codes. A statistical framework based on hidden Markov models (HMM) capturing dependencies between the source and channel coding components sets the foundation for optimal design of techniques of joint decoding of source and channel codes. The problem has been largely addressed in the research community, by considering both fixed-length codes (FLC) and variable-length source codes (VLC) widely used in compression standards. Joint source-channel decoding of VLC raises specific difficulties due to the fact that the segmentation of the received bitstream into source symbols is random. This paper makes a survey of recent theoretical and practical advances in the area of JSCD with soft information of VLC-encoded sources. It first describes the main paths followed for designing efficient estimators for VLC-encoded sources, the key component of the JSCD iterative structure. It then presents the main issues involved in the application of the turbo principle to JSCD of VLC-encoded sources as well as the main approaches to source-controlled channel decoding. This survey terminates by performance illustrations with real image and video decoding systems.

Long-distance quantum communication over noisy networks without long-time quantum memory

NASA Astrophysics Data System (ADS)

Mazurek, Paweł; Grudka, Andrzej; Horodecki, Michał; Horodecki, Paweł; Łodyga, Justyna; Pankowski, Łukasz; PrzysieŻna, Anna

2014-12-01

The problem of sharing entanglement over large distances is crucial for implementations of quantum cryptography. A possible scheme for long-distance entanglement sharing and quantum communication exploits networks whose nodes share Einstein-Podolsky-Rosen (EPR) pairs. In Perseguers et al. [Phys. Rev. A 78, 062324 (2008), 10.1103/PhysRevA.78.062324] the authors put forward an important isomorphism between storing quantum information in a dimension D and transmission of quantum information in a D +1 -dimensional network. We show that it is possible to obtain long-distance entanglement in a noisy two-dimensional (2D) network, even when taking into account that encoding and decoding of a state is exposed to an error. For 3D networks we propose a simple encoding and decoding scheme based solely on syndrome measurements on 2D Kitaev topological quantum memory. Our procedure constitutes an alternative scheme of state injection that can be used for universal quantum computation on 2D Kitaev code. It is shown that the encoding scheme is equivalent to teleporting the state, from a specific node into a whole two-dimensional network, through some virtual EPR pair existing within the rest of network qubits. We present an analytic lower bound on fidelity of the encoding and decoding procedure, using as our main tool a modified metric on space-time lattice, deviating from a taxicab metric at the first and the last time slices.

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.

Processes involved in solving mathematical problems

NASA Astrophysics Data System (ADS)

Shahrill, Masitah; Putri, Ratu Ilma Indra; Zulkardi, Prahmana, Rully Charitas Indra

2018-04-01

This study examines one of the instructional practices features utilized within the Year 8 mathematics lessons in Brunei Darussalam. The codes from the TIMSS 1999 Video Study were applied and strictly followed, and from the 183 mathematics problems recorded, there were 95 problems with a solution presented during the public segments of the video-recorded lesson sequences of the four sampled teachers. The analyses involved firstly, identifying the processes related to mathematical problem statements, and secondly, examining the different processes used in solving the mathematical problems for each problem publicly completed during the lessons. The findings revealed that for three of the teachers, their problem statements coded as `using procedures' ranged from 64% to 83%, while the remaining teacher had 40% of his problem statements coded as `making connections.' The processes used when solving the problems were mainly `using procedures', and none of the problems were coded as `giving results only'. Furthermore, all four teachers made use of making the relevant connections in solving the problems given to their respective students.

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.

The World in a Tomato: Revisiting the Use of "Codes" in Freire's Problem-Posing Education.

ERIC Educational Resources Information Center

Barndt, Deborah

1998-01-01

Gives examples of the use of Freire's notion of codes or generative themes in problem-posing literacy education. Describes how these applications expand Freire's conceptions by involving students in code production, including multicultural perspectives, and rethinking codes as representations. (SK)

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.

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

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

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.

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.

Diagnostic reasoning and underlying knowledge of students with preclinical patient contacts in PBL.

PubMed

Diemers, Agnes D; van de Wiel, Margje W J; Scherpbier, Albert J J A; Baarveld, Frank; Dolmans, Diana H J M

2015-12-01

Medical experts have access to elaborate and integrated knowledge networks consisting of biomedical and clinical knowledge. These coherent knowledge networks enable them to generate more accurate diagnoses in a shorter time. However, students' knowledge networks are less organised and students have difficulties linking theory and practice and transferring acquired knowledge. Therefore we wanted to explore the development and transfer of knowledge of third-year preclinical students on a problem-based learning (PBL) course with real patient contacts. Before and after a 10-week PBL course with real patients, third-year medical students were asked to think out loud while diagnosing four types of paper patient problems (two course cases and two transfer cases), and explain the underlying pathophysiological mechanisms of the patient features. Diagnostic accuracy and time needed to think through the cases were measured. The think-aloud protocols were transcribed verbatim and different types of knowledge were coded and quantitatively analysed. The written pathophysiological explanations were translated into networks of concepts. Both the concepts and the links between concepts in students' networks were compared to model networks. Over the course diagnostic accuracy increased, case-processing time decreased, and students used less biomedical and clinical knowledge during diagnostic reasoning. The quality of the pathophysiological explanations increased: the students used more concepts, especially more model concepts, and they used fewer wrong concepts and links. The findings differed across course and transfer cases. The effects were generally less strong for transfer cases. Students' improved diagnostic accuracy and the improved quality of their knowledge networks suggest that integration of biomedical and clinical knowledge took place during a 10-week course. The differences between course and transfer cases demonstrate that transfer is complex and time-consuming. We therefore suggest offering students many varied patient contacts with the same underlying pathophysiological mechanism and encouraging students to link biomedical and clinical knowledge. © 2015 John Wiley & Sons Ltd.

Querying graphs in protein-protein interactions networks using feedback vertex set.

PubMed

Blin, Guillaume; Sikora, Florian; Vialette, Stéphane

2010-01-01

Recent techniques increase rapidly the amount of our knowledge on interactions between proteins. The interpretation of these new information depends on our ability to retrieve known substructures in the data, the Protein-Protein Interactions (PPIs) networks. In an algorithmic point of view, it is an hard task since it often leads to NP-hard problems. To overcome this difficulty, many authors have provided tools for querying patterns with a restricted topology, i.e., paths or trees in PPI networks. Such restriction leads to the development of fixed parameter tractable (FPT) algorithms, which can be practicable for restricted sizes of queries. Unfortunately, Graph Homomorphism is a W[1]-hard problem, and hence, no FPT algorithm can be found when patterns are in the shape of general graphs. However, Dost et al. gave an algorithm (which is not implemented) to query graphs with a bounded treewidth in PPI networks (the treewidth of the query being involved in the time complexity). In this paper, we propose another algorithm for querying pattern in the shape of graphs, also based on dynamic programming and the color-coding technique. To transform graphs queries into trees without loss of informations, we use feedback vertex set coupled to a node duplication mechanism. Hence, our algorithm is FPT for querying graphs with a bounded size of their feedback vertex set. It gives an alternative to the treewidth parameter, which can be better or worst for a given query. We provide a python implementation which allows us to validate our implementation on real data. Especially, we retrieve some human queries in the shape of graphs into the fly PPI network.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

NASA Astrophysics Data System (ADS)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

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.

A network approach to policy framing: A case study of the National Aboriginal and Torres Strait Islander Health Plan.

PubMed

Browne, Jennifer; de Leeuw, Evelyne; Gleeson, Deborah; Adams, Karen; Atkinson, Petah; Hayes, Rick

2017-01-01

Aboriginal health policy in Australia represents a unique policy subsystem comprising a diverse network of Aboriginal-specific and "mainstream" organisations, often with competing interests. This paper describes the network structure of organisations attempting to influence national Aboriginal health policy and examines how the different subgroups within the network approached the policy discourse. Public submissions made as part of a policy development process for the National Aboriginal and Torres Strait Islander Health Plan were analysed using a novel combination of network analysis and qualitative framing analysis. Other organisational actors in the network in each submission were identified, and relationships between them determined; these were used to generate a network map depicting the ties between actors. A qualitative framing analysis was undertaken, using inductive coding of the policy discourses in the submissions. The frames were overlaid with the network map to identify the relationship between the structure of the network and the way in which organisations framed Aboriginal health problems. Aboriginal organisations were central to the network and strongly connected with each other. The network consisted of several densely connected subgroups, whose central nodes were closely connected to one another. Each subgroup deployed a particular policy frame, with a frame of "system dysfunction" also adopted by all but one subgroup. Analysis of submissions revealed that many of the stakeholders in Aboriginal health policy actors are connected to one another. These connections help to drive the policy discourse. The combination of network and framing analysis illuminates competing interests within a network, and can assist advocacy organisations to identify which network members are most influential. Copyright © 2016 Elsevier Ltd. All rights reserved.

An adaptable neural-network model for recursive nonlinear traffic prediction and modeling of MPEG video sources.

PubMed

Doulamis, A D; Doulamis, N D; Kollias, S D

2003-01-01

Multimedia services and especially digital video is expected to be the major traffic component transmitted over communication networks [such as internet protocol (IP)-based networks]. For this reason, traffic characterization and modeling of such services are required for an efficient network operation. The generated models can be used as traffic rate predictors, during the network operation phase (online traffic modeling), or as video generators for estimating the network resources, during the network design phase (offline traffic modeling). In this paper, an adaptable neural-network architecture is proposed covering both cases. The scheme is based on an efficient recursive weight estimation algorithm, which adapts the network response to current conditions. In particular, the algorithm updates the network weights so that 1) the network output, after the adaptation, is approximately equal to current bit rates (current traffic statistics) and 2) a minimal degradation over the obtained network knowledge is provided. It can be shown that the proposed adaptable neural-network architecture simulates a recursive nonlinear autoregressive model (RNAR) similar to the notation used in the linear case. The algorithm presents low computational complexity and high efficiency in tracking traffic rates in contrast to conventional retraining schemes. Furthermore, for the problem of offline traffic modeling, a novel correlation mechanism is proposed for capturing the burstness of the actual MPEG video traffic. The performance of the model is evaluated using several real-life MPEG coded video sources of long duration and compared with other linear/nonlinear techniques used for both cases. The results indicate that the proposed adaptable neural-network architecture presents better performance than other examined techniques.

A Cooperative Downloading Method for VANET Using Distributed Fountain Code.

PubMed

Liu, Jianhang; Zhang, Wenbin; Wang, Qi; Li, Shibao; Chen, Haihua; Cui, Xuerong; Sun, Yi

2016-10-12

Cooperative downloading is one of the effective methods to improve the amount of downloaded data in vehicular ad hoc networking (VANET). However, the poor channel quality and short encounter time bring about a high packet loss rate, which decreases transmission efficiency and fails to satisfy the requirement of high quality of service (QoS) for some applications. Digital fountain code (DFC) can be utilized in the field of wireless communication to increase transmission efficiency. For cooperative forwarding, however, processing delay from frequent coding and decoding as well as single feedback mechanism using DFC cannot adapt to the environment of VANET. In this paper, a cooperative downloading method for VANET using concatenated DFC is proposed to solve the problems above. The source vehicle and cooperative vehicles encodes the raw data using hierarchical fountain code before they send to the client directly or indirectly. Although some packets may be lost, the client can recover the raw data, so long as it receives enough encoded packets. The method avoids data retransmission due to packet loss. Furthermore, the concatenated feedback mechanism in the method reduces the transmission delay effectively. Simulation results indicate the benefits of the proposed scheme in terms of increasing amount of downloaded data and data receiving rate.

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 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.

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.

Distributed computations in a dynamic, heterogeneous Grid environment

NASA Astrophysics Data System (ADS)

Dramlitsch, Thomas

2003-06-01

In order to face the rapidly increasing need for computational resources of various scientific and engineering applications one has to think of new ways to make more efficient use of the worlds current computational resources. In this respect, the growing speed of wide area networks made a new kind of distributed computing possible: Metacomputing or (distributed) Grid computing. This is a rather new and uncharted field in computational science. The rapidly increasing speed of networks even outperforms the average increase of processor speed: Processor speeds double on average each 18 month whereas network bandwidths double every 9 months. Due to this development of local and wide area networks Grid computing will certainly play a key role in the future of parallel computing. This type of distributed computing, however, distinguishes from the traditional parallel computing in many ways since it has to deal with many problems not occurring in classical parallel computing. Those problems are for example heterogeneity, authentication and slow networks to mention only a few. Some of those problems, e.g. the allocation of distributed resources along with the providing of information about these resources to the application have been already attacked by the Globus software. Unfortunately, as far as we know, hardly any application or middle-ware software takes advantage of this information, since most parallelizing algorithms for finite differencing codes are implicitly designed for single supercomputer or cluster execution. We show that although it is possible to apply classical parallelizing algorithms in a Grid environment, in most cases the observed efficiency of the executed code is very poor. In this work we are closing this gap. In our thesis, we will - show that an execution of classical parallel codes in Grid environments is possible but very slow - analyze this situation of bad performance, nail down bottlenecks in communication, remove unnecessary overhead and other reasons for low performance - develop new and advanced algorithms for parallelisation that are aware of a Grid environment in order to generelize the traditional parallelization schemes - implement and test these new methods, replace and compare with the classical ones - introduce dynamic strategies that automatically adapt the running code to the nature of the underlying Grid environment. The higher the performance one can achieve for a single application by manual tuning for a Grid environment, the lower the chance that those changes are widely applicable to other programs. In our analysis as well as in our implementation we tried to keep the balance between high performance and generality. None of our changes directly affect code on the application level which makes our algorithms applicable to a whole class of real world applications. The implementation of our work is done within the Cactus framework using the Globus toolkit, since we think that these are the most reliable and advanced programming frameworks for supporting computations in Grid environments. On the other hand, however, we tried to be as general as possible, i.e. all methods and algorithms discussed in this thesis are independent of Cactus or Globus. Die immer dichtere und schnellere Vernetzung von Rechnern und Rechenzentren über Hochgeschwindigkeitsnetzwerke ermöglicht eine neue Art des wissenschaftlich verteilten Rechnens, bei der geographisch weit auseinanderliegende Rechenkapazitäten zu einer Gesamtheit zusammengefasst werden können. Dieser so entstehende virtuelle Superrechner, der selbst aus mehreren Grossrechnern besteht, kann dazu genutzt werden Probleme zu berechnen, für die die einzelnen Grossrechner zu klein sind. Die Probleme, die numerisch mit heutigen Rechenkapazitäten nicht lösbar sind, erstrecken sich durch sämtliche Gebiete der heutigen Wissenschaft, angefangen von Astrophysik, Molekülphysik, Bioinformatik, Meteorologie, bis hin zur Zahlentheorie und Fluiddynamik um nur einige Gebiete zu nennen. Je nach Art der Problemstellung und des Lösungsverfahrens gestalten sich solche "Meta-Berechnungen" mehr oder weniger schwierig. Allgemein kann man sagen, dass solche Berechnungen um so schwerer und auch um so uneffizienter werden, je mehr Kommunikation zwischen den einzelnen Prozessen (oder Prozessoren) herrscht. Dies ist dadurch begründet, dass die Bandbreiten bzw. Latenzzeiten zwischen zwei Prozessoren auf demselben Grossrechner oder Cluster um zwei bis vier Grössenordnungen höher bzw. niedriger liegen als zwischen Prozessoren, welche hunderte von Kilometern entfernt liegen. Dennoch bricht nunmehr eine Zeit an, in der es möglich ist Berechnungen auf solch virtuellen Supercomputern auch mit kommunikationsintensiven Programmen durchzuführen. Eine grosse Klasse von kommunikations- und berechnungsintensiven Programmen ist diejenige, die die Lösung von Differentialgleichungen mithilfe von finiten Differenzen zum Inhalt hat. Gerade diese Klasse von Programmen und deren Betrieb in einem virtuellen Superrechner wird in dieser vorliegenden Dissertation behandelt. Methoden zur effizienteren Durchführung von solch verteilten Berechnungen werden entwickelt, analysiert und implementiert. Der Schwerpunkt liegt darin vorhandene, klassische Parallelisierungsalgorithmen zu analysieren und so zu erweitern, dass sie vorhandene Informationen (z.B. verfügbar durch das Globus Toolkit) über Maschinen und Netzwerke zur effizienteren Parallelisierung nutzen. Soweit wir wissen werden solche Zusatzinformationen kaum in relevanten Programmen genutzt, da der Grossteil aller Parallelisierungsalgorithmen implizit für die Ausführung auf Grossrechnern oder Clustern entwickelt wurde.

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

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.

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

Subspace-Aware Index Codes

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

Kailkhura, Bhavya; Theagarajan, Lakshmi Narasimhan; Varshney, Pramod K.

In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications (e.g., multimedia), the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unawaremore » cases. In conclusion, our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.« less

Subspace-Aware Index Codes

DOE PAGES

Kailkhura, Bhavya; Theagarajan, Lakshmi Narasimhan; Varshney, Pramod K.

2017-04-12

In this paper, we generalize the well-known index coding problem to exploit the structure in the source-data to improve system throughput. In many applications (e.g., multimedia), the data to be transmitted may lie (or can be well approximated) in a low-dimensional subspace. We exploit this low-dimensional structure of the data using an algebraic framework to solve the index coding problem (referred to as subspace-aware index coding) as opposed to the traditional index coding problem which is subspace-unaware. Also, we propose an efficient algorithm based on the alternating minimization approach to obtain near optimal index codes for both subspace-aware and -unawaremore » cases. In conclusion, our simulations indicate that under certain conditions, a significant throughput gain (about 90%) can be achieved by subspace-aware index codes over conventional subspace-unaware index codes.« less

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 Novel Code System for Revealing Sources of Students' Difficulties with Stoichiometry

ERIC Educational Resources Information Center

Gulacar, Ozcan; Overton, Tina L.; Bowman, Charles R.; Fynewever, Herb

2013-01-01

A coding scheme is presented and used to evaluate solutions of seventeen students working on twenty five stoichiometry problems in a think-aloud protocol. The stoichiometry problems are evaluated as a series of sub-problems (e.g., empirical formulas, mass percent, or balancing chemical equations), and the coding scheme was used to categorize each…

Sixteen years of ICPC use in Norwegian primary care: looking through the facts

PubMed Central

2010-01-01

Background The International Classification for Primary Care (ICPC) standard aims to facilitate simultaneous and longitudinal comparisons of clinical primary care practice within and across country borders; it is also used for administrative purposes. This study evaluates the use of the original ICPC-1 and the more complete ICPC-2 Norwegian versions in electronic patient records. Methods We performed a retrospective study of approximately 1.5 million ICPC codes and diagnoses that were collected over a 16-year period at 12 primary care sites in Norway. In the first phase of this period (transition phase, 1992-1999) physicians were allowed to not use an ICPC code in their practice while in the second phase (regular phase, 2000-2008) the use of an ICPC code was mandatory. The ICPC codes and diagnoses defined a problem event for each patient in the PROblem-oriented electronic MEDical record (PROMED). The main outcome measure of our analysis was the percentage of problem events in PROMEDs with inappropriate (or missing) ICPC codes and of diagnoses that did not map the latest ICPC-2 classification. Specific problem areas (pneumonia, anaemia, tonsillitis and diabetes) were examined in the same context. Results Codes were missing in 6.2% of the problem events; incorrect codes were observed in 4.0% of the problem events and text mismatch between the diagnoses and the expected ICPC-2 diagnoses text in 53.8% of the problem events. Missing codes were observed only during the transition phase while incorrect and inappropriate codes were used all over the 16-year period. The physicians created diagnoses that did not exist in ICPC. These 'new' diagnoses were used with varying frequency; many of them were used only once. Inappropriate ICPC-2 codes were also observed in the selected problem areas and for both phases. Conclusions Our results strongly suggest that physicians did not adhere to the ICPC standard due to its incompleteness, i.e. lack of many clinically important diagnoses. This indicates that ICPC is inappropriate for the classification of problem events and the clinical practice in primary care. PMID:20181271

The random energy model in a magnetic field and joint source channel coding

NASA Astrophysics Data System (ADS)

Merhav, Neri

2008-09-01

We demonstrate that there is an intimate relationship between the magnetic properties of Derrida’s random energy model (REM) of spin glasses and the problem of joint source-channel coding in Information Theory. In particular, typical patterns of erroneously decoded messages in the coding problem have “magnetization” properties that are analogous to those of the REM in certain phases, where the non-uniformity of the distribution of the source in the coding problem plays the role of an external magnetic field applied to the REM. We also relate the ensemble performance (random coding exponents) of joint source-channel codes to the free energy of the REM in its different phases.

A Content Analysis of Displayed Alcohol References on a Social Networking Web Site

PubMed Central

Moreno, Megan A; Briner, Leslie R; Williams, Amanda; Brockman, Libby; Walker, Leslie; Christakis, Dimitri A

2010-01-01

Purpose Exposure to alcohol use in media is associated with adolescent alcohol use. Adolescents frequently display alcohol references on Internet media such as social networking websites (SNSs). The purpose of this study was to conduct a theoretically-based content analysis of older adolescents’ displayed alcohol references on a SNS. Methods We evaluated 400 randomly selected public MySpace profiles of self-reported 17 to 20-year-olds from zip codes representing urban, suburban and rural communities in one Washington county. Content was evaluated for alcohol references suggesting: 1) explicit versus figurative alcohol use, 2) alcohol-related motivations, associations and consequences, including references that met CRAFFT problem drinking criteria. We compared profiles from four target zip codes for prevalence and frequency of alcohol display. Results Of 400 profiles, 225 profiles (56.3%) contained 341 references to alcohol. Profile owners who displayed alcohol references were mostly male (54.2%) and White (70.7%). The most frequent reference category was explicit use (49.3%), the most commonly displayed alcohol use motivation was peer pressure (4.7%). Few references met CRAFFT problem drinking criteria (3.2%). There were no differences in prevalence or frequency of alcohol display among the four sociodemographic communities. Conclusions Despite alcohol use being illegal and potentially stigmatizing in this population, explicit alcohol use is frequently referenced on adolescents’ MySpace profiles across several sociodemographic communities. Motivations, associations and consequences regarding alcohol use referenced on MySpace appear consistent with previous studies of adolescent alcohol use. These references may be a potent source of influence on adolescents, particularly given that they are created and displayed by peers. PMID:20638009

Enhancing social networks: a qualitative study of health and social care practice in UK mental health services.

PubMed

Webber, Martin; Reidy, Hannah; Ansari, David; Stevens, Martin; Morris, David

2015-03-01

People with severe mental health problems such as psychosis have access to less social capital, defined as resources within social networks, than members of the general population. However, a lack of theoretically and empirically informed models hampers the development of social interventions which seek to enhance an individual's social networks. This paper reports the findings of a qualitative study, which used ethnographic field methods in six sites in England to investigate how workers helped people recovering from psychosis to enhance their social networks. This study drew upon practice wisdom and lived experience to provide data for intervention modelling. Data were collected from 73 practitioners and 51 people who used their services in two phases. Data were selected and coded using a grounded theory approach to depict the key themes that appeared to underpin the generation of social capital within networks. Findings are presented in four over-arching themes - worker skills, attitudes and roles; connecting people processes; role of the agency; and barriers to network development. The sub-themes which were identified included worker attitudes; person-centred approach; equality of worker-individual relationship; goal setting; creating new networks and relationships; engagement through activities; practical support; existing relationships; the individual taking responsibility; identifying and overcoming barriers; and moving on. Themes were consistent with recovery models used within mental health services and will provide the basis for the development of an intervention model to enhance individuals' access to social capital within networks. © 2014 John Wiley & Sons Ltd.

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

A comparison of skyshine computational methods.

PubMed

Hertel, Nolan E; Sweezy, Jeremy E; Shultis, J Kenneth; Warkentin, J Karl; Rose, Zachary J

2005-01-01

A variety of methods employing radiation transport and point-kernel codes have been used to model two skyshine problems. The first problem is a 1 MeV point source of photons on the surface of the earth inside a 2 m tall and 1 m radius silo having black walls. The skyshine radiation downfield from the point source was estimated with and without a 30-cm-thick concrete lid on the silo. The second benchmark problem is to estimate the skyshine radiation downfield from 12 cylindrical canisters emplaced in a low-level radioactive waste trench. The canisters are filled with ion-exchange resin with a representative radionuclide loading, largely 60Co, 134Cs and 137Cs. The solution methods include use of the MCNP code to solve the problem by directly employing variance reduction techniques, the single-scatter point kernel code GGG-GP, the QADMOD-GP point kernel code, the COHORT Monte Carlo code, the NAC International version of the SKYSHINE-III code, the KSU hybrid method and the associated KSU skyshine codes.

Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration

NASA Technical Reports Server (NTRS)

Yen, H. W.; Morrison, R. J.

1984-01-01

Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.

Integrating Information in Biological Ontologies and Molecular Networks to Infer Novel Terms.

PubMed

Li, Le; Yip, Kevin Y

2016-12-15

Currently most terms and term-term relationships in Gene Ontology (GO) are defined manually, which creates cost, consistency and completeness issues. Recent studies have demonstrated the feasibility of inferring GO automatically from biological networks, which represents an important complementary approach to GO construction. These methods (NeXO and CliXO) are unsupervised, which means 1) they cannot use the information contained in existing GO, 2) the way they integrate biological networks may not optimize the accuracy, and 3) they are not customized to infer the three different sub-ontologies of GO. Here we present a semi-supervised method called Unicorn that extends these previous methods to tackle the three problems. Unicorn uses a sub-tree of an existing GO sub-ontology as training part to learn parameters in integrating multiple networks. Cross-validation results show that Unicorn reliably inferred the left-out parts of each specific GO sub-ontology. In addition, by training Unicorn with an old version of GO together with biological networks, it successfully re-discovered some terms and term-term relationships present only in a new version of GO. Unicorn also successfully inferred some novel terms that were not contained in GO but have biological meanings well-supported by the literature. Source code of Unicorn is available at http://yiplab.cse.cuhk.edu.hk/unicorn/.

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

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Predicting Causes of Data Quality Issues in a Clinical Data Research Network.

PubMed

Khare, Ritu; Ruth, Byron J; Miller, Matthew; Tucker, Joshua; Utidjian, Levon H; Razzaghi, Hanieh; Patibandla, Nandan; Burrows, Evanette K; Bailey, L Charles

2018-01-01

Clinical data research networks (CDRNs) invest substantially in identifying and investigating data quality problems. While identification is largely automated, the investigation and resolution are carried out manually at individual institutions. In the PEDSnet CDRN, we found that only approximately 35% of the identified data quality issues are resolvable as they are caused by errors in the extract-transform-load (ETL) code. Nonetheless, with no prior knowledge of issue causes, partner institutions end up spending significant time investigating issues that represent either inherent data characteristics or false alarms. This work investigates whether the causes (ETL, Characteristic, or False alarm) can be predicted before spending time investigating issues. We trained a classifier on the metadata from 10,281 real-world data quality issues, and achieved a cause prediction F1-measure of up to 90%. While initially tested on PEDSnet, the proposed methodology is applicable to other CDRNs facing similar bottlenecks in handling data quality results.

"Magnetic Reconnection Code: Applications to Sawtooth Oscillations, Error-Field Induced Islands, and the Dynamo Effect" - Final Technical Report

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

Fitzpatrick, Richard

2007-09-24

Dr. Fitzpatrick has written an MHD code in order to investigate the interaction of tearing modes with flow and external magnetic perturbations, which has been successfully benchmarked against both linear and nonlinear theory and used to investigate error-field penetration in flowing plasmas. The same code was used to investigate the so-called Taylor problem. He employed the University of Chicago's FLASH code to further investigate the Taylor problem, discovering a new aspect of the problem. Dr. Fitzpatrick has written a 2-D Hall MHD code and used it to investigate the collisionless Taylor problem. Dr. Waelbroeck has performed an investigation of themore » scaling of the error-field penetration threshold in collisionless plasmas. Paul Watson and Dr. Fitzpatrick have written a fully-implicit extended-MHD code using the PETSC framework. Five publications have resulted from this grant work.« less

CELFE/NASTRAN Code for the Analysis of Structures Subjected to High Velocity Impact

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1978-01-01

CELFE (Coupled Eulerian Lagrangian Finite Element)/NASTRAN Code three-dimensional finite element code has the capability for analyzing of structures subjected to high velocity impact. The local response is predicted by CELFE and, for large problems, the far-field impact response is predicted by NASTRAN. The coupling of the CELFE code with NASTRAN (CELFE/NASTRAN code) and the application of the code to selected three-dimensional high velocity impact problems are described.

User's manual for three dimensional FDTD version B code for scattering from frequency-dependent dielectric materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1992-01-01

The Penn State Finite Difference Time Domain Electromagnetic Code Version B is a three dimensional numerical electromagnetic scattering code based upon the Finite Difference Time Domain Technique (FDTD). The supplied version of the code is one version of our current three dimensional FDTD code set. This manual provides a description of the code and corresponding results for several scattering problems. The manual is organized into 14 sections: introduction, description of the FDTD method, operation, resource requirements, Version B code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include file, a discussion of radar cross section computations, a discussion of some scattering results, a sample problem setup section, a new problem checklist, references and figure titles.

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…

Mapping chemical structure-activity information of HAART-drug cocktails over complex networks of AIDS epidemiology and socioeconomic data of U.S. counties.

PubMed

Herrera-Ibatá, Diana María; Pazos, Alejandro; Orbegozo-Medina, Ricardo Alfredo; Romero-Durán, Francisco Javier; González-Díaz, Humberto

2015-06-01

Using computational algorithms to design tailored drug cocktails for highly active antiretroviral therapy (HAART) on specific populations is a goal of major importance for both pharmaceutical industry and public health policy institutions. New combinations of compounds need to be predicted in order to design HAART cocktails. On the one hand, there are the biomolecular factors related to the drugs in the cocktail (experimental measure, chemical structure, drug target, assay organisms, etc.); on the other hand, there are the socioeconomic factors of the specific population (income inequalities, employment levels, fiscal pressure, education, migration, population structure, etc.) to study the relationship between the socioeconomic status and the disease. In this context, machine learning algorithms, able to seek models for problems with multi-source data, have to be used. In this work, the first artificial neural network (ANN) model is proposed for the prediction of HAART cocktails, to halt AIDS on epidemic networks of U.S. counties using information indices that codify both biomolecular and several socioeconomic factors. The data was obtained from at least three major sources. The first dataset included assays of anti-HIV chemical compounds released to ChEMBL. The second dataset is the AIDSVu database of Emory University. AIDSVu compiled AIDS prevalence for >2300 U.S. counties. The third data set included socioeconomic data from the U.S. Census Bureau. Three scales or levels were employed to group the counties according to the location or population structure codes: state, rural urban continuum code (RUCC) and urban influence code (UIC). An analysis of >130,000 pairs (network links) was performed, corresponding to AIDS prevalence in 2310 counties in U.S. vs. drug cocktails made up of combinations of ChEMBL results for 21,582 unique drugs, 9 viral or human protein targets, 4856 protocols, and 10 possible experimental measures. The best model found with the original data was a linear neural network (LNN) with AUROC>0.80 and accuracy, specificity, and sensitivity≈77% in training and external validation series. The change of the spatial and population structure scale (State, UIC, or RUCC codes) does not affect the quality of the model. Unbalance was detected in all the models found comparing positive/negative cases and linear/non-linear model accuracy ratios. Using synthetic minority over-sampling technique (SMOTE), data pre-processing and machine-learning algorithms implemented into the WEKA software, more balanced models were found. In particular, a multilayer perceptron (MLP) with AUROC=97.4% and precision, recall, and F-measure >90% was found. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification.

PubMed

Guo, Wei-Feng; Zhang, Shao-Wu; Shi, Qian-Qian; Zhang, Cheng-Ming; Zeng, Tao; Chen, Luonan

2018-01-19

The advances in target control of complex networks not only can offer new insights into the general control dynamics of complex systems, but also be useful for the practical application in systems biology, such as discovering new therapeutic targets for disease intervention. In many cases, e.g. drug target identification in biological networks, we usually require a target control on a subset of nodes (i.e., disease-associated genes) with minimum cost, and we further expect that more driver nodes consistent with a certain well-selected network nodes (i.e., prior-known drug-target genes). Therefore, motivated by this fact, we pose and address a new and practical problem called as target control problem with objectives-guided optimization (TCO): how could we control the interested variables (or targets) of a system with the optional driver nodes by minimizing the total quantity of drivers and meantime maximizing the quantity of constrained nodes among those drivers. Here, we design an efficient algorithm (TCOA) to find the optional driver nodes for controlling targets in complex networks. We apply our TCOA to several real-world networks, and the results support that our TCOA can identify more precise driver nodes than the existing control-fucus approaches. Furthermore, we have applied TCOA to two bimolecular expert-curate networks. Source code for our TCOA is freely available from http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm or https://github.com/WilfongGuo/guoweifeng . In the previous theoretical research for the full control, there exists an observation and conclusion that the driver nodes tend to be low-degree nodes. However, for target control the biological networks, we find interestingly that the driver nodes tend to be high-degree nodes, which is more consistent with the biological experimental observations. Furthermore, our results supply the novel insights into how we can efficiently target control a complex system, and especially many evidences on the practical strategic utility of TCOA to incorporate prior drug information into potential drug-target forecasts. Thus applicably, our method paves a novel and efficient way to identify the drug targets for leading the phenotype transitions of underlying biological networks.

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.

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.

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.

An approach for coupled-code multiphysics core simulations from a common input

DOE PAGES

Schmidt, Rodney; Belcourt, Kenneth; Hooper, Russell; ...

2014-12-10

This study describes an approach for coupled-code multiphysics reactor core simulations that is being developed by the Virtual Environment for Reactor Applications (VERA) project in the Consortium for Advanced Simulation of Light-Water Reactors (CASL). In this approach a user creates a single problem description, called the “VERAIn” common input file, to define and setup the desired coupled-code reactor core simulation. A preprocessing step accepts the VERAIn file and generates a set of fully consistent input files for the different physics codes being coupled. The problem is then solved using a single-executable coupled-code simulation tool applicable to the problem, which ismore » built using VERA infrastructure software tools and the set of physics codes required for the problem of interest. The approach is demonstrated by performing an eigenvalue and power distribution calculation of a typical three-dimensional 17 × 17 assembly with thermal–hydraulic and fuel temperature feedback. All neutronics aspects of the problem (cross-section calculation, neutron transport, power release) are solved using the Insilico code suite and are fully coupled to a thermal–hydraulic analysis calculated by the Cobra-TF (CTF) code. The single-executable coupled-code (Insilico-CTF) simulation tool is created using several VERA tools, including LIME (Lightweight Integrating Multiphysics Environment for coupling codes), DTK (Data Transfer Kit), Trilinos, and TriBITS. Parallel calculations are performed on the Titan supercomputer at Oak Ridge National Laboratory using 1156 cores, and a synopsis of the solution results and code performance is presented. Finally, ongoing development of this approach is also briefly described.« less

Importance biasing scheme implemented in the PRIZMA code

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

Kandiev, I.Z.; Malyshkin, G.N.

1997-12-31

PRIZMA code is intended for Monte Carlo calculations of linear radiation transport problems. The code has wide capabilities to describe geometry, sources, material composition, and to obtain parameters specified by user. There is a capability to calculate path of particle cascade (including neutrons, photons, electrons, positrons and heavy charged particles) taking into account possible transmutations. Importance biasing scheme was implemented to solve the problems which require calculation of functionals related to small probabilities (for example, problems of protection against radiation, problems of detection, etc.). The scheme enables to adapt trajectory building algorithm to problem peculiarities.

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

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.

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

Problems, solutions and recommendations for implementing CODES (Crash Outcome Data Evaluation System)

DOT National Transportation Integrated Search

2001-02-01

Problems, solutions and recommendations for implementation have been contributed by 16 of the 27 CODES states and organized as appropriate under the administrative, linkage and application requirements for a Crash Outcome Data Evaluation System (CODE...

Code Verification Results of an LLNL ASC Code on Some Tri-Lab Verification Test Suite Problems

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

Anderson, S R; Bihari, B L; Salari, K

As scientific codes become more complex and involve larger numbers of developers and algorithms, chances for algorithmic implementation mistakes increase. In this environment, code verification becomes essential to building confidence in the code implementation. This paper will present first results of a new code verification effort within LLNL's B Division. In particular, we will show results of code verification of the LLNL ASC ARES code on the test problems: Su Olson non-equilibrium radiation diffusion, Sod shock tube, Sedov point blast modeled with shock hydrodynamics, and Noh implosion.

libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.

PubMed

Ji, Xinglai; Xu, Ying

2006-01-01

Estimation of kinetic parameters in a biochemical pathway or network represents a common problem in systems studies of biological processes. We have implemented a C library, named libSRES, to facilitate a fast implementation of computer software for study of non-linear biochemical pathways. This library implements a (mu, lambda)-ES evolutionary optimization algorithm that uses stochastic ranking as the constraint handling technique. Considering the amount of computing time it might require to solve a parameter-estimation problem, an MPI version of libSRES is provided for parallel implementation, as well as a simple user interface. libSRES is freely available and could be used directly in any C program as a library function. We have extensively tested the performance of libSRES on various pathway parameter-estimation problems and found its performance to be satisfactory. The source code (in C) is free for academic users at http://csbl.bmb.uga.edu/~jix/science/libSRES/

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

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.

Transportation Network Analysis and Decomposition Methods

DOT National Transportation Integrated Search

1978-03-01

The report outlines research in transportation network analysis using decomposition techniques as a basis for problem solutions. Two transportation network problems were considered in detail: a freight network flow problem and a scheduling problem fo...

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.

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.

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.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Nonlinear Transient Problems Using Structure Compatible Heat Transfer Code

NASA Technical Reports Server (NTRS)

Hou, Gene

2000-01-01

The report documents the recent effort to enhance a transient linear heat transfer code so as to solve nonlinear problems. The linear heat transfer code was originally developed by Dr. Kim Bey of NASA Largely and called the Structure-Compatible Heat Transfer (SCHT) code. The report includes four parts. The first part outlines the formulation of the heat transfer problem of concern. The second and the third parts give detailed procedures to construct the nonlinear finite element equations and the required Jacobian matrices for the nonlinear iterative method, Newton-Raphson method. The final part summarizes the results of the numerical experiments on the newly enhanced SCHT code.

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

Verification and benchmark testing of the NUFT computer code

NASA Astrophysics Data System (ADS)

Lee, K. H.; Nitao, J. J.; Kulshrestha, A.

1993-10-01

This interim report presents results of work completed in the ongoing verification and benchmark testing of the NUFT (Nonisothermal Unsaturated-saturated Flow and Transport) computer code. NUFT is a suite of multiphase, multicomponent models for numerical solution of thermal and isothermal flow and transport in porous media, with application to subsurface contaminant transport problems. The code simulates the coupled transport of heat, fluids, and chemical components, including volatile organic compounds. Grid systems may be cartesian or cylindrical, with one-, two-, or fully three-dimensional configurations possible. In this initial phase of testing, the NUFT code was used to solve seven one-dimensional unsaturated flow and heat transfer problems. Three verification and four benchmarking problems were solved. In the verification testing, excellent agreement was observed between NUFT results and the analytical or quasianalytical solutions. In the benchmark testing, results of code intercomparison were very satisfactory. From these testing results, it is concluded that the NUFT code is ready for application to field and laboratory problems similar to those addressed here. Multidimensional problems, including those dealing with chemical transport, will be addressed in a subsequent report.

Network planning under uncertainties

NASA Astrophysics Data System (ADS)

Ho, Kwok Shing; Cheung, Kwok Wai

2008-11-01

One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a generic framework for solving the network planning problem under uncertainties. In addition to reviewing the various network planning problems involving uncertainties, we also propose that a unified framework based on robust optimization can be used to solve a rather large segment of network planning problem under uncertainties. Robust optimization is first introduced in the operations research literature and is a framework that incorporates information about the uncertainty sets for the parameters in the optimization model. Even though robust optimization is originated from tackling the uncertainty in the optimization process, it can serve as a comprehensive and suitable framework for tackling generic network planning problems under uncertainties. In this paper, we begin by explaining the main ideas behind the robust optimization approach. Then we demonstrate the capabilities of the proposed framework by giving out some examples of how the robust optimization framework can be applied to the current common network planning problems under uncertain environments. Next, we list some practical considerations for solving the network planning problem under uncertainties with the proposed framework. Finally, we conclude this article with some thoughts on the future directions for applying this framework to solve other network planning problems.

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

LSENS, a general chemical kinetics and sensitivity analysis code for homogeneous gas-phase reactions. 2: Code description and usage

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Bittker, David A.

1994-01-01

LSENS, the Lewis General Chemical Kinetics Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 2 of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part 2 describes the code, how to modify it, and its usage, including preparation of the problem data file required to execute LSENS. Code usage is illustrated by several example problems, which further explain preparation of the problem data file and show how to obtain desired accuracy in the computed results. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions. Part 1 (NASA RP-1328) derives the governing equations describes the numerical solution procedures for the types of problems that can be solved by lSENS. Part 3 (NASA RP-1330) explains the kinetics and kinetics-plus-sensitivity-analysis problems supplied with LSENS and presents sample results.

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.

User's manual for two dimensional FDTD version TEA and TMA codes for scattering from frequency-independent dielectic materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Versions TEA and TMA are two dimensional numerical electromagnetic scattering codes based upon the Finite Difference Time Domain Technique (FDTD) first proposed by Yee in 1966. The supplied version of the codes are two versions of our current two dimensional FDTD code set. This manual provides a description of the codes and corresponding results for the default scattering problem. The manual is organized into eleven sections: introduction, Version TEA and TMA code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include files (TEACOM.FOR TMACOM.FOR), a section briefly discussing scattering width computations, a section discussing the scattering results, a sample problem set section, a new problem checklist, references and figure titles.

User's manual for two dimensional FDTD version TEA and TMA codes for scattering from frequency-independent dielectric materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Versions TEA and TMA are two dimensional electromagnetic scattering codes based on the Finite Difference Time Domain Technique (FDTD) first proposed by Yee in 1966. The supplied version of the codes are two versions of our current FDTD code set. This manual provides a description of the codes and corresponding results for the default scattering problem. The manual is organized into eleven sections: introduction, Version TEA and TMA code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include files (TEACOM.FOR TMACOM.FOR), a section briefly discussing scattering width computations, a section discussing the scattering results, a sample problem setup section, a new problem checklist, references, and figure titles.

User's manual for three dimensional FDTD version C code for scattering from frequency-independent dielectric and magnetic materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Version C is a three dimensional numerical electromagnetic scattering code based upon the Finite Difference Time Domain Technique (FDTD). The supplied version of the code is one version of our current three dimensional FDTD code set. This manual provides a description of the code and corresponding results for several scattering problems. The manual is organized into fourteen sections: introduction, description of the FDTD method, operation, resource requirements, Version C code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include file (COMMONC.FOR), a section briefly discussing Radar Cross Section (RCS) computations, a section discussing some scattering results, a sample problem setup section, a new problem checklist, references and figure titles.

User's manual for three dimensional FDTD version D code for scattering from frequency-dependent dielectric and magnetic materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Version D is a three dimensional numerical electromagnetic scattering code based upon the Finite Difference Time Domain Technique (FDTD). The supplied version of the code is one version of our current three dimensional FDTD code set. This manual provides a description of the code and corresponding results for several scattering problems. The manual is organized into fourteen sections: introduction, description of the FDTD method, operation, resource requirements, Version D code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include file (COMMOND.FOR), a section briefly discussing Radar Cross Section (RCS) computations, a section discussing some scattering results, a sample problem setup section, a new problem checklist, references and figure titles.

User's manual for three dimensional FDTD version A code for scattering from frequency-independent dielectric materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1992-01-01

The Penn State Finite Difference Time Domain (FDTD) Electromagnetic Scattering Code Version A is a three dimensional numerical electromagnetic scattering code based on the Finite Difference Time Domain technique. The supplied version of the code is one version of our current three dimensional FDTD code set. The manual provides a description of the code and the corresponding results for the default scattering problem. The manual is organized into 14 sections: introduction, description of the FDTD method, operation, resource requirements, Version A code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include file (COMMONA.FOR), a section briefly discussing radar cross section (RCS) computations, a section discussing the scattering results, a sample problem setup section, a new problem checklist, references, and figure titles.

User's manual for three dimensional FDTD version B code for scattering from frequency-dependent dielectric materials

NASA Technical Reports Server (NTRS)

Beggs, John H.; Luebbers, Raymond J.; Kunz, Karl S.

1991-01-01

The Penn State Finite Difference Time Domain Electromagnetic Scattering Code Version B is a three dimensional numerical electromagnetic scattering code based upon the Finite Difference Time Domain Technique (FDTD). The supplied version of the code is one version of our current three dimensional FDTD code set. This manual provides a description of the code and corresponding results for several scattering problems. The manual is organized into fourteen sections: introduction, description of the FDTD method, operation, resource requirements, Version B code capabilities, a brief description of the default scattering geometry, a brief description of each subroutine, a description of the include file (COMMONB.FOR), a section briefly discussing Radar Cross Section (RCS) computations, a section discussing some scattering results, a sample problem setup section, a new problem checklist, references and figure titles.

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

fastBMA: scalable network inference and transitive reduction.

PubMed

Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

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

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

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

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.

Using domain decomposition in the multigrid NAS parallel benchmark on the Fujitsu VPP500

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

Wang, J.C.H.; Lung, H.; Katsumata, Y.

1995-12-01

In this paper, we demonstrate how domain decomposition can be applied to the multigrid algorithm to convert the code for MPP architectures. We also discuss the performance and scalability of this implementation on the new product line of Fujitsu`s vector parallel computer, VPP500. This computer has Fujitsu`s well-known vector processor as the PE each rated at 1.6 C FLOPS. The high speed crossbar network rated at 800 MB/s provides the inter-PE communication. The results show that the physical domain decomposition is the best way to solve MG problems on VPP500.

Large scale analysis of signal reachability.

PubMed

Todor, Andrei; Gabr, Haitham; Dobra, Alin; Kahveci, Tamer

2014-06-15

Major disorders, such as leukemia, have been shown to alter the transcription of genes. Understanding how gene regulation is affected by such aberrations is of utmost importance. One promising strategy toward this objective is to compute whether signals can reach to the transcription factors through the transcription regulatory network (TRN). Due to the uncertainty of the regulatory interactions, this is a #P-complete problem and thus solving it for very large TRNs remains to be a challenge. We develop a novel and scalable method to compute the probability that a signal originating at any given set of source genes can arrive at any given set of target genes (i.e., transcription factors) when the topology of the underlying signaling network is uncertain. Our method tackles this problem for large networks while providing a provably accurate result. Our method follows a divide-and-conquer strategy. We break down the given network into a sequence of non-overlapping subnetworks such that reachability can be computed autonomously and sequentially on each subnetwork. We represent each interaction using a small polynomial. The product of these polynomials express different scenarios when a signal can or cannot reach to target genes from the source genes. We introduce polynomial collapsing operators for each subnetwork. These operators reduce the size of the resulting polynomial and thus the computational complexity dramatically. We show that our method scales to entire human regulatory networks in only seconds, while the existing methods fail beyond a few tens of genes and interactions. We demonstrate that our method can successfully characterize key reachability characteristics of the entire transcriptions regulatory networks of patients affected by eight different subtypes of leukemia, as well as those from healthy control samples. All the datasets and code used in this article are available at bioinformatics.cise.ufl.edu/PReach/scalable.htm. © The Author 2014. Published by Oxford University Press.

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.

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.

The CRONOS Code for Astrophysical Magnetohydrodynamics

NASA Astrophysics Data System (ADS)

Kissmann, R.; Kleimann, J.; Krebl, B.; Wiengarten, T.

2018-06-01

We describe the magnetohydrodynamics (MHD) code CRONOS, which has been used in astrophysics and space-physics studies in recent years. CRONOS has been designed to be easily adaptable to the problem in hand, where the user can expand or exchange core modules or add new functionality to the code. This modularity comes about through its implementation using a C++ class structure. The core components of the code include solvers for both hydrodynamical (HD) and MHD problems. These problems are solved on different rectangular grids, which currently support Cartesian, spherical, and cylindrical coordinates. CRONOS uses a finite-volume description with different approximate Riemann solvers that can be chosen at runtime. Here, we describe the implementation of the code with a view toward its ongoing development. We illustrate the code’s potential through several (M)HD test problems and some astrophysical applications.

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.

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.

Development of an open source package for the processing of sun-sky photometric data in the European Skyrad Users network (ESR)

NASA Astrophysics Data System (ADS)

Estelles, V.; Smyth, T.; Campanelli, M.; Utrillas, M. P.

2009-04-01

The European SkyRad users network (ESR) is a joint initiative from the Institute of Atmospheric and Climate Sciences (ISAC) at the National Research Council (CNR) in Italy, the Group of Solar Radiation (GRSV) at the University of Valencia (UV) in Spain, and the Plymouth Marine Laboratory (PML) in the United Kingdom. It was started as a Protocol of Agreement between the three institutions, in 2003. The main objective was to collaborate on the improvement of some technical aspects of the Skyrad.pack algorithm. Currently the network is addressed at European research groups that are users of sun - sky photometers and mainly focus their research on the study of atmospheric aerosols and their application to remote sensing or climatological studies. There exist well known international networks such as AERONET (Aerosol Robotic Network) or SKYNET (SKYrad NETwork, in Asia) but they have some characteristics that actually prevent many European research groups to get involved with them. These limitations mean that a number of European groups are working independently, with no coordination. The resultant databases are not made public or the employed methodology is not homogeneous. In turn, it means that a great amount of data is being lost for critical regional studies in Europe. One of these limitations is related to the supported instrumentation. International networks usually adopt a given model of sun photometer as a standard. The ESR is a multi instrumental network using both Prede POM and Cimel CE318 sun - sky photometers. Another limitation is related to the calibration. In the case of AERONET, a centralized and stringent calibration protocol is adopted. This protocol is designed in order to offer a well tracked and quality assured calibration and data elaboration; it is in fact the key stone for the homogeneity of the network results. But centralization raises other problems. The instruments must be periodically sent every 6 - 12 months to United States or France; therefore, 1) the instrument absence generates considerable data gaps, 2) it is also a chance for equipment damage during the transport, and 3) the proprietary group must cope with the economical cost of these international insured deliveries. Moreover, the protocol constrains the network capability to handle a large amount of instruments. In fact, AERONET is very reluctant at the moment to accept new sites in Europe. ESR has developed an improved version of the Langley plot technique (SKYIL) that allows the users to perform a continuous in situ calibration. Previous results show that the obtained uncertainties in the calibration factors (1.0 - 2.5%) are very similar to the uncertainty values for field instruments in AERONET (1.0 - 2.0%). A third difference that could make ESR more appealing to some European research groups is related to the algorithms itself. The core inversion code (Skyrad.pack), the calibration codes and all the automatization scripts are free open source codes that can be further customized by the users. Therefore, an advanced user could easily access and modify the algorithms for new improvements. As a conclusion, the ESR users network has been conceived as a flexible network and collaborative platform for European groups whose main research is focused on atmospheric aerosols characterization and model development. The package we have developed for the network is an open source product that is available for public use, both for Cimel CE318 and Prede POM instruments.

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.

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

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

PubMed

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

On the linear programming bound for linear Lee codes.

PubMed

Astola, Helena; Tabus, Ioan

2016-01-01

Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.

Synconset Waves and Chains: Spiking Onsets in Synchronous Populations Predict and Are Predicted by Network Structure

PubMed Central

Raghavan, Mohan; Amrutur, Bharadwaj; Narayanan, Rishikesh; Sikdar, Sujit Kumar

2013-01-01

Synfire waves are propagating spike packets in synfire chains, which are feedforward chains embedded in random networks. Although synfire waves have proved to be effective quantification for network activity with clear relations to network structure, their utilities are largely limited to feedforward networks with low background activity. To overcome these shortcomings, we describe a novel generalisation of synfire waves, and define ‘synconset wave’ as a cascade of first spikes within a synchronisation event. Synconset waves would occur in ‘synconset chains’, which are feedforward chains embedded in possibly heavily recurrent networks with heavy background activity. We probed the utility of synconset waves using simulation of single compartment neuron network models with biophysically realistic conductances, and demonstrated that the spread of synconset waves directly follows from the network connectivity matrix and is modulated by top-down inputs and the resultant oscillations. Such synconset profiles lend intuitive insights into network organisation in terms of connection probabilities between various network regions rather than an adjacency matrix. To test this intuition, we develop a Bayesian likelihood function that quantifies the probability that an observed synfire wave was caused by a given network. Further, we demonstrate it's utility in the inverse problem of identifying the network that caused a given synfire wave. This method was effective even in highly subsampled networks where only a small subset of neurons were accessible, thus showing it's utility in experimental estimation of connectomes in real neuronal-networks. Together, we propose synconset chains/waves as an effective framework for understanding the impact of network structure on function, and as a step towards developing physiology-driven network identification methods. Finally, as synconset chains extend the utilities of synfire chains to arbitrary networks, we suggest utilities of our framework to several aspects of network physiology including cell assemblies, population codes, and oscillatory synchrony. PMID:24116018

Phonological Coding Abilities: Identification of Impairments Related to Phonologically Based Reading Problems.

ERIC Educational Resources Information Center

Swank, Linda K.

1994-01-01

Relationships between phonological coding abilities and reading outcomes have implications for differential diagnosis of language-based reading problems. The theoretical construct of specific phonological coding ability is explained, including phonological encoding, phonological awareness and metaphonology, lexical access, working memory, and…

A strong shock tube problem calculated by different numerical schemes

NASA Astrophysics Data System (ADS)

Lee, Wen Ho; Clancy, Sean P.

1996-05-01

Calculated results are presented for the solution of a very strong shock tube problem on a coarse mesh using (1) MESA code, (2) UNICORN code, (3) Schulz hydro, and (4) modified TVD scheme. The first two codes are written in Eulerian coordinates, whereas methods (3) and (4) are in Lagrangian coordinates. MESA and UNICORN codes are both of second order and use different monotonic advection method to avoid the Gibbs phenomena. Code (3) uses typical artificial viscosity for inviscid flow, whereas code (4) uses a modified TVD scheme. The test problem is a strong shock tube problem with a pressure ratio of 109 and density ratio of 103 in an ideal gas. For no mass-matching case, Schulz hydro is better than TVD scheme. In the case of mass-matching, there is no difference between them. MESA and UNICORN results are nearly the same. However, the computed positions such as the contact discontinuity (i.e. the material interface) are not as accurate as the Lagrangian methods.

Enhanced Verification Test Suite for Physics Simulation Codes

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

Kamm, J R; Brock, J S; Brandon, S T

2008-10-10

This document discusses problems with which to augment, in quantity and in quality, the existing tri-laboratory suite of verification problems used by Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and Sandia National Laboratories (SNL). The purpose of verification analysis is demonstrate whether the numerical results of the discretization algorithms in physics and engineering simulation codes provide correct solutions of the corresponding continuum equations. The key points of this document are: (1) Verification deals with mathematical correctness of the numerical algorithms in a code, while validation deals with physical correctness of a simulation in a regime of interest.more » This document is about verification. (2) The current seven-problem Tri-Laboratory Verification Test Suite, which has been used for approximately five years at the DOE WP laboratories, is limited. (3) Both the methodology for and technology used in verification analysis have evolved and been improved since the original test suite was proposed. (4) The proposed test problems are in three basic areas: (a) Hydrodynamics; (b) Transport processes; and (c) Dynamic strength-of-materials. (5) For several of the proposed problems we provide a 'strong sense verification benchmark', consisting of (i) a clear mathematical statement of the problem with sufficient information to run a computer simulation, (ii) an explanation of how the code result and benchmark solution are to be evaluated, and (iii) a description of the acceptance criterion for simulation code results. (6) It is proposed that the set of verification test problems with which any particular code be evaluated include some of the problems described in this document. Analysis of the proposed verification test problems constitutes part of a necessary--but not sufficient--step that builds confidence in physics and engineering simulation codes. More complicated test cases, including physics models of greater sophistication or other physics regimes (e.g., energetic material response, magneto-hydrodynamics), would represent a scientifically desirable complement to the fundamental test cases discussed in this report. The authors believe that this document can be used to enhance the verification analyses undertaken at the DOE WP Laboratories and, thus, to improve the quality, credibility, and usefulness of the simulation codes that are analyzed with these problems.« less

Optimal aggregation of binary classifiers for multiclass cancer diagnosis using gene expression profiles.

PubMed

Yukinawa, Naoto; Oba, Shigeyuki; Kato, Kikuya; Ishii, Shin

2009-01-01

Multiclass classification is one of the fundamental tasks in bioinformatics and typically arises in cancer diagnosis studies by gene expression profiling. There have been many studies of aggregating binary classifiers to construct a multiclass classifier based on one-versus-the-rest (1R), one-versus-one (11), or other coding strategies, as well as some comparison studies between them. However, the studies found that the best coding depends on each situation. Therefore, a new problem, which we call the "optimal coding problem," has arisen: how can we determine which coding is the optimal one in each situation? To approach this optimal coding problem, we propose a novel framework for constructing a multiclass classifier, in which each binary classifier to be aggregated has a weight value to be optimally tuned based on the observed data. Although there is no a priori answer to the optimal coding problem, our weight tuning method can be a consistent answer to the problem. We apply this method to various classification problems including a synthesized data set and some cancer diagnosis data sets from gene expression profiling. The results demonstrate that, in most situations, our method can improve classification accuracy over simple voting heuristics and is better than or comparable to state-of-the-art multiclass predictors.

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

Implicit time-integration method for simultaneous solution of a coupled non-linear system

NASA Astrophysics Data System (ADS)

Watson, Justin Kyle

Historically large physical problems have been divided into smaller problems based on the physics involved. This is no different in reactor safety analysis. The problem of analyzing a nuclear reactor for design basis accidents is performed by a handful of computer codes each solving a portion of the problem. The reactor thermal hydraulic response to an event is determined using a system code like TRAC RELAP Advanced Computational Engine (TRACE). The core power response to the same accident scenario is determined using a core physics code like Purdue Advanced Core Simulator (PARCS). Containment response to the reactor depressurization in a Loss Of Coolant Accident (LOCA) type event is calculated by a separate code. Sub-channel analysis is performed with yet another computer code. This is just a sample of the computer codes used to solve the overall problems of nuclear reactor design basis accidents. Traditionally each of these codes operates independently from each other using only the global results from one calculation as boundary conditions to another. Industry's drive to uprate power for reactors has motivated analysts to move from a conservative approach to design basis accident towards a best estimate method. To achieve a best estimate calculation efforts have been aimed at coupling the individual physics models to improve the accuracy of the analysis and reduce margins. The current coupling techniques are sequential in nature. During a calculation time-step data is passed between the two codes. The individual codes solve their portion of the calculation and converge to a solution before the calculation is allowed to proceed to the next time-step. This thesis presents a fully implicit method of simultaneous solving the neutron balance equations, heat conduction equations and the constitutive fluid dynamics equations. It discusses the problems involved in coupling different physics phenomena within multi-physics codes and presents a solution to these problems. The thesis also outlines the basic concepts behind the nodal balance equations, heat transfer equations and the thermal hydraulic equations, which will be coupled to form a fully implicit nonlinear system of equations. The coupling of separate physics models to solve a larger problem and improve accuracy and efficiency of a calculation is not a new idea, however implementing them in an implicit manner and solving the system simultaneously is. Also the application to reactor safety codes is new and has not be done with thermal hydraulics and neutronics codes on realistic applications in the past. The coupling technique described in this thesis is applicable to other similar coupled thermal hydraulic and core physics reactor safety codes. This technique is demonstrated using coupled input decks to show that the system is solved correctly and then verified by using two derivative test problems based on international benchmark problems the OECD/NRC Three mile Island (TMI) Main Steam Line Break (MSLB) problem (representative of pressurized water reactor analysis) and the OECD/NRC Peach Bottom (PB) Turbine Trip (TT) benchmark (representative of boiling water reactor analysis).

LSENS, A General Chemical Kinetics and Sensitivity Analysis Code for Homogeneous Gas-Phase Reactions. Part 2; Code Description and Usage

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Bittker, David A.

1994-01-01

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part II of a series of three reference publications that describe LSENS, provide a detailed guide to its usage, and present many example problems. Part II describes the code, how to modify it, and its usage, including preparation of the problem data file required to execute LSENS. Code usage is illustrated by several example problems, which further explain preparation of the problem data file and show how to obtain desired accuracy in the computed results. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions. Part I (NASA RP-1328) derives the governing equations and describes the numerical solution procedures for the types of problems that can be solved by LSENS. Part III (NASA RP-1330) explains the kinetics and kinetics-plus-sensitivity-analysis problems supplied with LSENS and presents sample results.

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.

E/M coding problems plague physicians, coders.

PubMed

King, Mitchell S; Lipsky, Martin S; Sharp, Lisa

2002-01-01

As the government turns its high beams on fraudulent billing, physician E/M coding is raising questions. With several studies spotlighting the difficulty physicians have in applying CPT E/M codes, the authors wanted to know if credentialed coders had the same problem. Here's what they found.

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.

Improving data transparency in clinical trials using blockchain smart contracts.

PubMed

Nugent, Timothy; Upton, David; Cimpoesu, Mihai

2016-01-01

The scientific credibility of findings from clinical trials can be undermined by a range of problems including missing data, endpoint switching, data dredging, and selective publication. Together, these issues have contributed to systematically distorted perceptions regarding the benefits and risks of treatments. While these issues have been well documented and widely discussed within the profession, legislative intervention has seen limited success. Recently, a method was described for using a blockchain to prove the existence of documents describing pre-specified endpoints in clinical trials. Here, we extend the idea by using smart contracts - code, and data, that resides at a specific address in a blockchain, and whose execution is cryptographically validated by the network - to demonstrate how trust in clinical trials can be enforced and data manipulation eliminated. We show that blockchain smart contracts provide a novel technological solution to the data manipulation problem, by acting as trusted administrators and providing an immutable record of trial history.

Using Grid Cells for Navigation

PubMed Central

Bush, Daniel; Barry, Caswell; Manson, Daniel; Burgess, Neil

2015-01-01

Summary Mammals are able to navigate to hidden goal locations by direct routes that may traverse previously unvisited terrain. Empirical evidence suggests that this “vector navigation” relies on an internal representation of space provided by the hippocampal formation. The periodic spatial firing patterns of grid cells in the hippocampal formation offer a compact combinatorial code for location within large-scale space. Here, we consider the computational problem of how to determine the vector between start and goal locations encoded by the firing of grid cells when this vector may be much longer than the largest grid scale. First, we present an algorithmic solution to the problem, inspired by the Fourier shift theorem. Second, we describe several potential neural network implementations of this solution that combine efficiency of search and biological plausibility. Finally, we discuss the empirical predictions of these implementations and their relationship to the anatomy and electrophysiology of the hippocampal formation. PMID:26247860

Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid

1999-01-01

The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.

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.

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.

ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning

NASA Astrophysics Data System (ADS)

Sadeh, I.; Abdalla, F. B.; Lahav, O.

2016-10-01

We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister & Lahav, which now includes generation of full probability distribution functions (PDFs). ANNz2 utilizes multiple machine learning methods, such as artificial neural networks and boosted decision/regression trees. The objective of the algorithm is to optimize the performance of the photo-z estimation, to properly derive the associated uncertainties, and to produce both single-value solutions and PDFs. In addition, estimators are made available, which mitigate possible problems of non-representative or incomplete spectroscopic training samples. ANNz2 has already been used as part of the first weak lensing analysis of the Dark Energy Survey, and is included in the experiment's first public data release. Here we illustrate the functionality of the code using data from the tenth data release of the Sloan Digital Sky Survey and the Baryon Oscillation Spectroscopic Survey. The code is available for download at http://github.com/IftachSadeh/ANNZ.

The Task and Relational Dimensions of Online Social Support.

PubMed

Beck, Stephenson J; Paskewitz, Emily A; Anderson, Whitney A; Bourdeaux, Renee; Currie-Mueller, Jenna

2017-03-01

Online support groups are attractive to individuals suffering from various types of mental and physical illness due to their accessibility, convenience, and comfort level. Individuals coping with depression, in particular, may seek social support online to avoid the stigma that accompanies face-to-face support groups. We explored how task and relational messages created social support in online depression support groups using Cutrona and Suhr's social support coding scheme and Bales's Interaction Process Analysis coding scheme. A content analysis revealed emotional support as the most common type of social support within the group, although the majority of messages were task rather than relational. Informational support consisted primarily of task messages, whereas network and esteem support were primarily relational messages. Specific types of task and relational messages were associated with different support types. Results indicate task messages dominated online depression support groups, suggesting the individuals who participate in these groups are interested in solving problems but may also experience emotional support when their uncertainty is reduced via task messages.

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.

Technologies for network-centric C4ISR

NASA Astrophysics Data System (ADS)

Dunkelberger, Kirk A.

2003-07-01

Three technologies form the heart of any network-centric command, control, communication, intelligence, surveillance, and reconnaissance (C4ISR) system: distributed processing, reconfigurable networking, and distributed resource management. Distributed processing, enabled by automated federation, mobile code, intelligent process allocation, dynamic multiprocessing groups, check pointing, and other capabilities creates a virtual peer-to-peer computing network across the force. Reconfigurable networking, consisting of content-based information exchange, dynamic ad-hoc routing, information operations (perception management) and other component technologies forms the interconnect fabric for fault tolerant inter processor and node communication. Distributed resource management, which provides the means for distributed cooperative sensor management, foe sensor utilization, opportunistic collection, symbiotic inductive/deductive reasoning and other applications provides the canonical algorithms for network-centric enterprises and warfare. This paper introduces these three core technologies and briefly discusses a sampling of their component technologies and their individual contributions to network-centric enterprises and warfare. Based on the implied requirements, two new algorithms are defined and characterized which provide critical building blocks for network centricity: distributed asynchronous auctioning and predictive dynamic source routing. The first provides a reliable, efficient, effective approach for near-optimal assignment problems; the algorithm has been demonstrated to be a viable implementation for ad-hoc command and control, object/sensor pairing, and weapon/target assignment. The second is founded on traditional dynamic source routing (from mobile ad-hoc networking), but leverages the results of ad-hoc command and control (from the contributed auctioning algorithm) into significant increases in connection reliability through forward prediction. Emphasis is placed on the advantages gained from the closed-loop interaction of the multiple technologies in the network-centric application environment.

A Coding Scheme for Analysing Problem-Solving Processes of First-Year Engineering Students

ERIC Educational Resources Information Center

Grigg, Sarah J.; Benson, Lisa C.

2014-01-01

This study describes the development and structure of a coding scheme for analysing solutions to well-structured problems in terms of cognitive processes and problem-solving deficiencies for first-year engineering students. A task analysis approach was used to assess students' problem solutions using the hierarchical structure from a…

Astronomy education and the Astrophysics Source Code Library

NASA Astrophysics Data System (ADS)

Allen, Alice; Nemiroff, Robert J.

2016-01-01

The Astrophysics Source Code Library (ASCL) is an online registry of source codes used in refereed astrophysics research. It currently lists nearly 1,200 codes and covers all aspects of computational astrophysics. How can this resource be of use to educators and to the graduate students they mentor? The ASCL serves as a discovery tool for codes that can be used for one's own research. Graduate students can also investigate existing codes to see how common astronomical problems are approached numerically in practice, and use these codes as benchmarks for their own solutions to these problems. Further, they can deepen their knowledge of software practices and techniques through examination of others' codes.

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.

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines

PubMed Central

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-01-01

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization. PMID:26343660

Multi-Sensor Detection with Particle Swarm Optimization for Time-Frequency Coded Cooperative WSNs Based on MC-CDMA for Underground Coal Mines.

PubMed

Xu, Jingjing; Yang, Wei; Zhang, Linyuan; Han, Ruisong; Shao, Xiaotao

2015-08-27

In this paper, a wireless sensor network (WSN) technology adapted to underground channel conditions is developed, which has important theoretical and practical value for safety monitoring in underground coal mines. According to the characteristics that the space, time and frequency resources of underground tunnel are open, it is proposed to constitute wireless sensor nodes based on multicarrier code division multiple access (MC-CDMA) to make full use of these resources. To improve the wireless transmission performance of source sensor nodes, it is also proposed to utilize cooperative sensors with good channel conditions from the sink node to assist source sensors with poor channel conditions. Moreover, the total power of the source sensor and its cooperative sensors is allocated on the basis of their channel conditions to increase the energy efficiency of the WSN. To solve the problem that multiple access interference (MAI) arises when multiple source sensors transmit monitoring information simultaneously, a kind of multi-sensor detection (MSD) algorithm with particle swarm optimization (PSO), namely D-PSO, is proposed for the time-frequency coded cooperative MC-CDMA WSN. Simulation results show that the average bit error rate (BER) performance of the proposed WSN in an underground coal mine is improved significantly by using wireless sensor nodes based on MC-CDMA, adopting time-frequency coded cooperative transmission and D-PSO algorithm with particle swarm optimization.

The Use of Automated SNOMED CT Clinical Coding in Clinical Decision Support Systems for Preventive Care.

PubMed

Al-Hablani, Bader

2017-01-01

The objective of this study is to discuss and analyze the use of automated SNOMED CT clinical coding in clinical decision support systems (CDSSs) for preventive care. The central question that this study seeks to answer is whether the utilization of SNOMED CT in CDSSs can improve preventive care. PubMed, Google Scholar, and Cochrane Library were searched for articles published in English between 2001 and 2012 on SNOMED CT, CDSS, and preventive care. Outcome measures were the sensitivity or specificity of SNOMED CT coded data and the positive predictive value or negative predictive value of SNOMED CT coded data. Additionally, we documented the publication year, research question, study design, results, and conclusions of these studies. The reviewed studies suggested that SNOMED CT successfully represents clinical terms and negated clinical terms. The use of SNOMED CT in CDSS can be considered to provide an answer to the problem of medical errors as well as for preventive care in general. Enhancement of the modifiers and synonyms found in SNOMED CT will be necessary to improve the expected outcome of the integration of SNOMED CT with CDSS. Moreover, the application of the tree-augmented naïve (TAN) Bayesian network method can be considered the best technique to search SNOMED CT data and, consequently, to help improve preventive health services.

The Use of Automated SNOMED CT Clinical Coding in Clinical Decision Support Systems for Preventive Care

PubMed Central

Al-Hablani, Bader

2017-01-01

Objective The objective of this study is to discuss and analyze the use of automated SNOMED CT clinical coding in clinical decision support systems (CDSSs) for preventive care. The central question that this study seeks to answer is whether the utilization of SNOMED CT in CDSSs can improve preventive care. Method PubMed, Google Scholar, and Cochrane Library were searched for articles published in English between 2001 and 2012 on SNOMED CT, CDSS, and preventive care. Outcome Measures Outcome measures were the sensitivity or specificity of SNOMED CT coded data and the positive predictive value or negative predictive value of SNOMED CT coded data. Additionally, we documented the publication year, research question, study design, results, and conclusions of these studies. Results The reviewed studies suggested that SNOMED CT successfully represents clinical terms and negated clinical terms. Conclusion The use of SNOMED CT in CDSS can be considered to provide an answer to the problem of medical errors as well as for preventive care in general. Enhancement of the modifiers and synonyms found in SNOMED CT will be necessary to improve the expected outcome of the integration of SNOMED CT with CDSS. Moreover, the application of the tree-augmented naïve (TAN) Bayesian network method can be considered the best technique to search SNOMED CT data and, consequently, to help improve preventive health services. PMID:28566995

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.

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.

Parallel computing on Unix workstation arrays

NASA Astrophysics Data System (ADS)

Reale, F.; Bocchino, F.; Sciortino, S.

1994-12-01

We have tested arrays of general-purpose Unix workstations used as MIMD systems for massive parallel computations. In particular we have solved numerically a demanding test problem with a 2D hydrodynamic code, generally developed to study astrophysical flows, by exucuting it on arrays either of DECstations 5000/200 on Ethernet LAN, or of DECstations 3000/400, equipped with powerful Alpha processors, on FDDI LAN. The code is appropriate for data-domain decomposition, and we have used a library for parallelization previously developed in our Institute, and easily extended to work on Unix workstation arrays by using the PVM software toolset. We have compared the parallel efficiencies obtained on arrays of several processors to those obtained on a dedicated MIMD parallel system, namely a Meiko Computing Surface (CS-1), equipped with Intel i860 processors. We discuss the feasibility of using non-dedicated parallel systems and conclude that the convenience depends essentially on the size of the computational domain as compared to the relative processor power and network bandwidth. We point out that for future perspectives a parallel development of processor and network technology is important, and that the software still offers great opportunities of improvement, especially in terms of latency times in the message-passing protocols. In conditions of significant gain in terms of speedup, such workstation arrays represent a cost-effective approach to massive parallel computations.

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.

Mapping the distribution of packing topologies within protein interiors shows predominant preference for specific packing motifs

PubMed Central

2011-01-01

Background Mapping protein primary sequences to their three dimensional folds referred to as the 'second genetic code' remains an unsolved scientific problem. A crucial part of the problem concerns the geometrical specificity in side chain association leading to densely packed protein cores, a hallmark of correctly folded native structures. Thus, any model of packing within proteins should constitute an indispensable component of protein folding and design. Results In this study an attempt has been made to find, characterize and classify recurring patterns in the packing of side chain atoms within a protein which sustains its native fold. The interaction of side chain atoms within the protein core has been represented as a contact network based on the surface complementarity and overlap between associating side chain surfaces. Some network topologies definitely appear to be preferred and they have been termed 'packing motifs', analogous to super secondary structures in proteins. Study of the distribution of these motifs reveals the ubiquitous presence of typical smaller graphs, which appear to get linked or coalesce to give larger graphs, reminiscent of the nucleation-condensation model in protein folding. One such frequently occurring motif, also envisaged as the unit of clustering, the three residue clique was invariably found in regions of dense packing. Finally, topological measures based on surface contact networks appeared to be effective in discriminating sequences native to a specific fold amongst a set of decoys. Conclusions Out of innumerable topological possibilities, only a finite number of specific packing motifs are actually realized in proteins. This small number of motifs could serve as a basis set in the construction of larger networks. Of these, the triplet clique exhibits distinct preference both in terms of composition and geometry. PMID:21605466

FORTRAN Automated Code Evaluation System (faces) system documentation, version 2, mod 0. [error detection codes/user manuals (computer programs)

NASA Technical Reports Server (NTRS)

1975-01-01

A system is presented which processes FORTRAN based software systems to surface potential problems before they become execution malfunctions. The system complements the diagnostic capabilities of compilers, loaders, and execution monitors rather than duplicating these functions. Also, it emphasizes frequent sources of FORTRAN problems which require inordinate manual effort to identify. The principle value of the system is extracting small sections of unusual code from the bulk of normal sequences. Code structures likely to cause immediate or future problems are brought to the user's attention. These messages stimulate timely corrective action of solid errors and promote identification of 'tricky' code. Corrective action may require recoding or simply extending software documentation to explain the unusual technique.

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.

What the success of brain imaging implies about the neural code

PubMed Central

Guest, Olivia; Love, Bradley C

2017-01-01

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. DOI: http://dx.doi.org/10.7554/eLife.21397.001 PMID:28103186

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

Collaborative learning in networks.

PubMed

Mason, Winter; Watts, Duncan J

2012-01-17

Complex problems in science, business, and engineering typically require some tradeoff between exploitation of known solutions and exploration for novel ones, where, in many cases, information about known solutions can also disseminate among individual problem solvers through formal or informal networks. Prior research on complex problem solving by collectives has found the counterintuitive result that inefficient networks, meaning networks that disseminate information relatively slowly, can perform better than efficient networks for problems that require extended exploration. In this paper, we report on a series of 256 Web-based experiments in which groups of 16 individuals collectively solved a complex problem and shared information through different communication networks. As expected, we found that collective exploration improved average success over independent exploration because good solutions could diffuse through the network. In contrast to prior work, however, we found that efficient networks outperformed inefficient networks, even in a problem space with qualitative properties thought to favor inefficient networks. We explain this result in terms of individual-level explore-exploit decisions, which we find were influenced by the network structure as well as by strategic considerations and the relative payoff between maxima. We conclude by discussing implications for real-world problem solving and possible extensions.