Design framework for entanglement-distribution switching networks

NASA Astrophysics Data System (ADS)

Drost, Robert J.; Brodsky, Michael

2016-09-01

The distribution of quantum entanglement appears to be an important component of applications of quantum communications and networks. The ability to centralize the sourcing of entanglement in a quantum network can provide for improved efficiency and enable a variety of network structures. A necessary feature of an entanglement-sourcing network node comprising several sources of entangled photons is the ability to reconfigurably route the generated pairs of photons to network neighbors depending on the desired entanglement sharing of the network users at a given time. One approach to such routing is the use of a photonic switching network. The requirements for an entanglement distribution switching network are less restrictive than for typical conventional applications, leading to design freedom that can be leveraged to optimize additional criteria. In this paper, we present a mathematical framework defining the requirements of an entanglement-distribution switching network. We then consider the design of such a switching network using a number of 2 × 2 crossbar switches, addressing the interconnection of these switches and efficient routing algorithms. In particular, we define a worst-case loss metric and consider 6 × 6, 8 × 8, and 10 × 10 network designs that optimize both this metric and the number of crossbar switches composing the network. We pay particular attention to the 10 × 10 network, detailing novel results proving the optimality of the proposed design. These optimized network designs have great potential for use in practical quantum networks, thus advancing the concept of quantum networks toward reality.

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

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

Agarwal, Sapan; Quach, Tu -Thach; Parekh, Ojas

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-basedmore » architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.« less

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

DOE PAGES

Agarwal, Sapan; Quach, Tu -Thach; Parekh, Ojas; ...

2016-01-06

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-basedmore » architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.« less

Dynamic Testing and Automatic Repair of Reconfigurable Wiring Harnesses

DTIC Science & Technology

2006-11-27

Switch An M ×N grid of switches configured to provide a M -input, N -output routing network. Permutation Network A permutation network performs an...wiring reduces the effective advantage of their reduced switch count, particularly when considering that regular grids (crossbar switches being a...are connected to. The outline circuit shown in Fig. 20 shows how a suitable ‘discovery probe’ might be implemented. The circuit shows a UART

Memristor-based programmable logic array (PLA) and analysis as Memristive networks.

PubMed

Lee, Kwan-Hee; Lee, Sang-Jin; Kim, Seok-Man; Cho, Kyoungrok

2013-05-01

A Memristor theorized by Chua in 1971 has the potential to dramatically influence the way electronic circuits are designed. It is a two terminal device whose resistance state is based on the history of charge flow brought about as the result of the voltage being applied across its terminals and hence can be thought of as a special case of a reconfigurable resistor. Nanoscale devices using dense and regular fabrics such as Memristor cross-bar is promising new architecture for System-on-Chip (SoC) implementations in terms of not only the integration density that the technology can offer but also both improved performance and reduced power dissipation. Memristor has the capacity to switch between high and low resistance states in a cross-bar circuit configuration. The cross-bars are formed from an array of vertical conductive nano-wires cross a second array of horizontal conductive wires. Memristors are realized at the intersection of the two wires in the array through appropriate processing technology such that any particular wire in the vertical array can be connected to a wire in the horizontal array by switching the resistance of a particular intersection to a low state while other cross-points remain in a high resistance state. However the approach introduces a number of challenges. The lack of voltage gain prevents logic being cascaded and voltage level degradation affects robustness of the operation. Moreover the cross-bars introduce sneak current paths when two or more cross points are connected through the switched Memristor. In this paper, we propose Memristor-based programmable logic array (PLA) architecture and develop an analytical model to analyze the logic level on the memristive networks. The proposed PLA architecture has 12 inputs maximum and can be cascaded for more input variables with R(off)/R(on) ratio in the range from 55 to 160 of Memristors.

Scalable Wrap-Around Shuffle Exchange Network with Deflection Routing

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

1997-01-01

The invention in one embodiment is a communication network including plural non-blocking crossbar nodes, first apparatus for connecting the nodes in a first layer of connecting links, and second apparatus for connecting links independent of the first layer, whereby each layer is connected to the other layer at each point of the nodes. Preferably, each one of the layers of connecting links corresponds to one recirculating network topology that closes in on itself.

A functional hybrid memristor crossbar-array/CMOS system for data storage and neuromorphic applications.

PubMed

Kim, Kuk-Hwan; Gaba, Siddharth; Wheeler, Dana; Cruz-Albrecht, Jose M; Hussain, Tahir; Srinivasa, Narayan; Lu, Wei

2012-01-11

Crossbar arrays based on two-terminal resistive switches have been proposed as a leading candidate for future memory and logic applications. Here we demonstrate a high-density, fully operational hybrid crossbar/CMOS system composed of a transistor- and diode-less memristor crossbar array vertically integrated on top of a CMOS chip by taking advantage of the intrinsic nonlinear characteristics of the memristor element. The hybrid crossbar/CMOS system can reliably store complex binary and multilevel 1600 pixel bitmap images using a new programming scheme. © 2011 American Chemical Society

Neuromorphic crossbar circuit with nanoscale filamentary-switching binary memristors for speech recognition.

PubMed

Truong, Son Ngoc; Ham, Seok-Jin; Min, Kyeong-Sik

2014-01-01

In this paper, a neuromorphic crossbar circuit with binary memristors is proposed for speech recognition. The binary memristors which are based on filamentary-switching mechanism can be found more popularly and are easy to be fabricated than analog memristors that are rare in materials and need a more complicated fabrication process. Thus, we develop a neuromorphic crossbar circuit using filamentary-switching binary memristors not using interface-switching analog memristors. The proposed binary memristor crossbar can recognize five vowels with 4-bit 64 input channels. The proposed crossbar is tested by 2,500 speech samples and verified to be able to recognize 89.2% of the tested samples. From the statistical simulation, the recognition rate of the binary memristor crossbar is estimated to be degraded very little from 89.2% to 80%, though the percentage variation in memristance is increased very much from 0% to 15%. In contrast, the analog memristor crossbar loses its recognition rate significantly from 96% to 9% for the same percentage variation in memristance.

Synaptic characteristics with strong analog potentiation, depression, and short-term to long-term memory transition in a Pt/CeO2/Pt crossbar array structure

NASA Astrophysics Data System (ADS)

Kim, Hyung Jun; Park, Daehoon; Yang, Paul; Beom, Keonwon; Kim, Min Ju; Shin, Chansun; Kang, Chi Jung; Yoon, Tae-Sik

2018-06-01

A crossbar array of Pt/CeO2/Pt memristors exhibited the synaptic characteristics such as analog, reversible, and strong resistance change with a ratio of ∼103, corresponding to wide dynamic range of synaptic weight modulation as potentiation and depression with respect to the voltage polarity. In addition, it presented timing-dependent responses such as paired-pulse facilitation and the short-term to long-term memory transition by increasing amplitude, width, and repetition number of voltage pulse and reducing the interval time between pulses. The memory loss with a time was fitted with a stretched exponential relaxation model, revealing the relation of memory stability with the input stimuli strength. The resistance change was further enhanced but its stability got worse as increasing measurement temperature, indicating that the resistance was changed as a result of voltage- and temperature-dependent electrical charging and discharging to alter the energy barrier for charge transport. These detailed synaptic characteristics demonstrated the potential of crossbar array of Pt/CeO2/Pt memristors as artificial synapses in highly connected neuron-synapse network.

Synaptic characteristics with strong analog potentiation, depression, and short-term to long-term memory transition in a Pt/CeO2/Pt crossbar array structure.

PubMed

Kim, Hyung Jun; Park, Daehoon; Yang, Paul; Beom, Keonwon; Kim, Min Ju; Shin, Chansun; Kang, Chi Jung; Yoon, Tae-Sik

2018-06-29

A crossbar array of Pt/CeO 2 /Pt memristors exhibited the synaptic characteristics such as analog, reversible, and strong resistance change with a ratio of ∼10 3 , corresponding to wide dynamic range of synaptic weight modulation as potentiation and depression with respect to the voltage polarity. In addition, it presented timing-dependent responses such as paired-pulse facilitation and the short-term to long-term memory transition by increasing amplitude, width, and repetition number of voltage pulse and reducing the interval time between pulses. The memory loss with a time was fitted with a stretched exponential relaxation model, revealing the relation of memory stability with the input stimuli strength. The resistance change was further enhanced but its stability got worse as increasing measurement temperature, indicating that the resistance was changed as a result of voltage- and temperature-dependent electrical charging and discharging to alter the energy barrier for charge transport. These detailed synaptic characteristics demonstrated the potential of crossbar array of Pt/CeO 2 /Pt memristors as artificial synapses in highly connected neuron-synapse network.

Read margin analysis of crossbar arrays using the cell-variability-aware simulation method

NASA Astrophysics Data System (ADS)

Sun, Wookyung; Choi, Sujin; Shin, Hyungsoon

2018-02-01

This paper proposes a new concept of read margin analysis of crossbar arrays using cell-variability-aware simulation. The size of the crossbar array should be considered to predict the read margin characteristic of the crossbar array because the read margin depends on the number of word lines and bit lines. However, an excessively high-CPU time is required to simulate large arrays using a commercial circuit simulator. A variability-aware MATLAB simulator that considers independent variability sources is developed to analyze the characteristics of the read margin according to the array size. The developed MATLAB simulator provides an effective method for reducing the simulation time while maintaining the accuracy of the read margin estimation in the crossbar array. The simulation is also highly efficient in analyzing the characteristic of the crossbar memory array considering the statistical variations in the cell characteristics.

Three-dimensional crossbar interconnection using planar-integrated free-space optics and digital mirror-device

NASA Astrophysics Data System (ADS)

Lohmann, U.; Jahns, J.; Limmer, S.; Fey, D.

2011-01-01

We consider the implementation of a dynamic crossbar interconnect using planar-integrated free-space optics (PIFSO) and a digital mirror-device™ (DMD). Because of the 3D nature of free-space optics, this approach is able to solve geometrical problems with crossings of the signal paths that occur in waveguide optical and electrical interconnection, especially for large number of connections. The DMD device allows one to route the signals dynamically. Due to the large number of individual mirror elements in the DMD, different optical path configurations are possible, thus offering the chance for optimizing the network configuration. The optimization is achieved by using an evolutionary algorithm for finding best values for a skewless parallel interconnection. Here, we present results and experimental examples for the use of the PIFSO/DMD-setup.

Numerical study of read scheme in one-selector one-resistor crossbar array

NASA Astrophysics Data System (ADS)

Kim, Sungho; Kim, Hee-Dong; Choi, Sung-Jin

2015-12-01

A comprehensive numerical circuit analysis of read schemes of a one selector-one resistance change memory (1S1R) crossbar array is carried out. Three schemes-the ground, V/2, and V/3 schemes-are compared with each other in terms of sensing margin and power consumption. Without the aid of a complex analytical approach or SPICE-based simulation, a simple numerical iteration method is developed to simulate entire current flows and node voltages within a crossbar array. Understanding such phenomena is essential in successfully evaluating the electrical specifications of selectors for suppressing intrinsic drawbacks of crossbar arrays, such as sneaky current paths and series line resistance problems. This method provides a quantitative tool for the accurate analysis of crossbar arrays and provides guidelines for developing an optimal read scheme, array configuration, and selector device specifications.

A robust and scalable neuromorphic communication system by combining synaptic time multiplexing and MIMO-OFDM.

PubMed

Srinivasa, Narayan; Zhang, Deying; Grigorian, Beayna

2014-03-01

This paper describes a novel architecture for enabling robust and efficient neuromorphic communication. The architecture combines two concepts: 1) synaptic time multiplexing (STM) that trades space for speed of processing to create an intragroup communication approach that is firing rate independent and offers more flexibility in connectivity than cross-bar architectures and 2) a wired multiple input multiple output (MIMO) communication with orthogonal frequency division multiplexing (OFDM) techniques to enable a robust and efficient intergroup communication for neuromorphic systems. The MIMO-OFDM concept for the proposed architecture was analyzed by simulating large-scale spiking neural network architecture. Analysis shows that the neuromorphic system with MIMO-OFDM exhibits robust and efficient communication while operating in real time with a high bit rate. Through combining STM with MIMO-OFDM techniques, the resulting system offers a flexible and scalable connectivity as well as a power and area efficient solution for the implementation of very large-scale spiking neural architectures in hardware.

Belt attachment and system

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

Schneider, Abraham D.; Davidson, Erick M.

Disclosed herein is a belt assembly including a flexible belt with an improved belt attachment. The belt attachment includes two crossbars spaced along the length of the belt. The crossbars retain bearings that allow predetermined movement in six degrees of freedom. The crossbars are connected by a rigid body that attaches to the bearings. Implements that are attached to the rigid body are simply supported but restrained in pitching rotation.

Belt attachment and system

DOEpatents

Schneider, Abraham D.; Davidson, Erick M.

2016-02-02

Disclosed herein is a belt assembly including a flexible belt with an improved belt attachment. The belt attachment includes two crossbars spaced along the length of the belt. The crossbars retain bearings that allow predetermined movement in six degrees of freedom. The crossbars are connected by a rigid body that attaches to the bearings. Implements that are attached to the rigid body are simply supported but restrained in pitching rotation.

Two-dimensional self-organization of an ordered Au silicide nanowire network on a Si(110)-16 x 2 surface.

PubMed

Hong, Ie-Hong; Yen, Shang-Chieh; Lin, Fu-Shiang

2009-08-17

A well-ordered two-dimensional (2D) network consisting of two crossed Au silicide nanowire (NW) arrays is self-organized on a Si(110)-16 x 2 surface by the direct-current heating of approximately 1.5 monolayers of Au on the surface at 1100 K. Such a highly regular crossbar nanomesh exhibits both a perfect long-range spatial order and a high integration density over a mesoscopic area, and these two self-ordering crossed arrays of parallel-aligned NWs have distinctly different sizes and conductivities. NWs are fabricated with widths and pitches as small as approximately 2 and approximately 5 nm, respectively. The difference in the conductivities of two crossed-NW arrays opens up the possibility for their utilization in nanodevices of crossbar architecture. Scanning tunneling microscopy/spectroscopy studies show that the 2D self-organization of this perfect Au silicide nanomesh can be achieved through two different directional electromigrations of Au silicide NWs along different orientations of two nonorthogonal 16 x 2 domains, which are driven by the electrical field of direct-current heating. Prospects for this Au silicide nanomesh are also discussed.

Bench-top soldering aid for PC boards

NASA Technical Reports Server (NTRS)

Manton, N. R.; Schroff, R. A.

1978-01-01

Multiple-board rack allows technician to insert components into several boards, flip them all in single motion, and then systematically solder leads on reverse side. Two adjustable crossbars allow boards of any size up to 10 by 24 inches. Operator can rotate racks and adjust angle of boards from standing or sitting position.

Study of optoelectronic switch for satellite-switched time-division multiple access

NASA Technical Reports Server (NTRS)

Su, Shing-Fong; Jou, Liz; Lenart, Joe

1987-01-01

The use of optoelectronic switching for satellite switched time division multiple access will improve the isolation and reduce the crosstalk of an IF switch matrix. The results are presented of a study on optoelectronic switching. Tasks include literature search, system requirements study, candidate switching architecture analysis, and switch model optimization. The results show that the power divided and crossbar switching architectures are good candidates for an IF switch matrix.

An amorphous titanium dioxide metal insulator metal selector device for resistive random access memory crossbar arrays with tunable voltage margin

NASA Astrophysics Data System (ADS)

Cortese, Simone; Khiat, Ali; Carta, Daniela; Light, Mark E.; Prodromakis, Themistoklis

2016-01-01

Resistive random access memory (ReRAM) crossbar arrays have become one of the most promising candidates for next-generation non volatile memories. To become a mature technology, the sneak path current issue must be solved without compromising all the advantages that crossbars offer in terms of electrical performances and fabrication complexity. Here, we present a highly integrable access device based on nickel and sub-stoichiometric amorphous titanium dioxide (TiO2-x), in a metal insulator metal crossbar structure. The high voltage margin of 3 V, amongst the highest reported for monolayer selector devices, and the good current density of 104 A/cm2 make it suitable to sustain ReRAM read and write operations, effectively tackling sneak currents in crossbars without compromising fabrication complexity in a 1 Selector 1 Resistor (1S1R) architecture. Furthermore, the voltage margin is found to be tunable by an annealing step without affecting the device's characteristics.

Spacecraft IF switch matrix for wideband service applications in 30/20 GHz communications satellite systems: Proof-of-concept model, executive summary

NASA Technical Reports Server (NTRS)

Ho, P. T.; Coban, E.; Pelose, J.

1983-01-01

The design and development of a unique coupler crossbar 20 x 20 microwave switch matrix are described. The test results of the proof of concept model that meets the requirements for a high speed satellite switched, time division multiple access (SS-TDMA) system are presented.

All oxide semiconductor-based bidirectional vertical p-n-p selectors for 3D stackable crossbar-array electronics

PubMed Central

Bae, Yoon Cheol; Lee, Ah Rahm; Baek, Gwang Ho; Chung, Je Bock; Kim, Tae Yoon; Park, Jea Gun; Hong, Jin Pyo

2015-01-01

Three-dimensional (3D) stackable memory devices including nano-scaled crossbar array are central for the realization of high-density non-volatile memory electronics. However, an essential sneak path issue affecting device performance in crossbar array remains a bottleneck and a grand challenge. Therefore, a suitable bidirectional selector as a two-way switch is required to facilitate a major breakthrough in the 3D crossbar array memory devices. Here, we show the excellent selectivity of all oxide p-/n-type semiconductor-based p-n-p open-based bipolar junction transistors as selectors in crossbar memory array. We report that bidirectional nonlinear characteristics of oxide p-n-p junctions can be highly enhanced by manipulating p-/n-type oxide semiconductor characteristics. We also propose an associated Zener tunneling mechanism that explains the unique features of our p-n-p selector. Our experimental findings are further extended to confirm the profound functionality of oxide p-n-p selectors integrated with several bipolar resistive switching memory elements working as storage nodes. PMID:26289565

Memristor-Based Synapse Design and Training Scheme for Neuromorphic Computing Architecture

DTIC Science & Technology

2012-06-01

system level built upon the conventional Von Neumann computer architecture [2][3]. Developing the neuromorphic architecture at chip level by...SCHEME FOR NEUROMORPHIC COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-11-2-0046 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...creation of memristor-based neuromorphic computing architecture. Rather than the existing crossbar-based neuron network designs, we focus on memristor

Petaflops router

DOEpatents

Baker, Zachary Kent; Power, John Fredrick; Tripp, Justin Leonard; Dunham, Mark Edward; Stettler, Matthew W; Jones, John Alexander

2014-10-14

Disclosed is a method and system for performing operations on at least one input data vector in order to produce at least one output vector to permit easy, scalable and fast programming of a petascale equivalent supercomputer. A PetaFlops Router may comprise one or more PetaFlops Nodes, which may be connected to each other and/or external data provider/consumers via a programmable crossbar switch external to the PetaFlops Node. Each PetaFlops Node has a FPGA and a programmable intra-FPGA crossbar switch that permits input and output variables to be configurably connected to various physical operators contained in the FPGA as desired by a user. This allows a user to specify the instruction set of the system on a per-application basis. Further, the intra-FPGA crossbar switch permits the output of one operation to be delivered as an input to a second operation. By configuring the external crossbar switch, the output of a first operation on a first PetaFlops Node may be used as the input for a second operation on a second PetaFlops Node. An embodiment may provide an ability for the system to recognize and generate pipelined functions. Streaming operators may be connected together at run-time and appropriately staged to allow data to flow through a series of functions. This allows the system to provide high throughput and parallelism when possible. The PetaFlops Router may implement the user desired instructions by appropriately configuring the intra-FPGA crossbar switch on each PetaFlops Node and the external crossbar switch.

Quantum error correction in crossbar architectures

NASA Astrophysics Data System (ADS)

Helsen, Jonas; Steudtner, Mark; Veldhorst, Menno; Wehner, Stephanie

2018-07-01

A central challenge for the scaling of quantum computing systems is the need to control all qubits in the system without a large overhead. A solution for this problem in classical computing comes in the form of so-called crossbar architectures. Recently we made a proposal for a large-scale quantum processor (Li et al arXiv:1711.03807 (2017)) to be implemented in silicon quantum dots. This system features a crossbar control architecture which limits parallel single-qubit control, but allows the scheme to overcome control scaling issues that form a major hurdle to large-scale quantum computing systems. In this work, we develop a language that makes it possible to easily map quantum circuits to crossbar systems, taking into account their architecture and control limitations. Using this language we show how to map well known quantum error correction codes such as the planar surface and color codes in this limited control setting with only a small overhead in time. We analyze the logical error behavior of this surface code mapping for estimated experimental parameters of the crossbar system and conclude that logical error suppression to a level useful for real quantum computation is feasible.

A hybrid nanomemristor/transistor logic circuit capable of self-programming

PubMed Central

Borghetti, Julien; Li, Zhiyong; Straznicky, Joseph; Li, Xuema; Ohlberg, Douglas A. A.; Wu, Wei; Stewart, Duncan R.; Williams, R. Stanley

2009-01-01

Memristor crossbars were fabricated at 40 nm half-pitch, using nanoimprint lithography on the same substrate with Si metal-oxide-semiconductor field effect transistor (MOS FET) arrays to form fully integrated hybrid memory resistor (memristor)/transistor circuits. The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. As an illustrative demonstration, the compound Boolean logic operation (A AND B) OR (C AND D) was performed with kilohertz frequency inputs, using resistor-based logic in a memristor crossbar with FET inverter/amplifier outputs. By routing the output signal of a logic operation back onto a target memristor inside the array, the crossbar was conditionally configured by setting the state of a nonvolatile switch. Such conditional programming illuminates the way for a variety of self-programmed logic arrays, and for electronic synaptic computing. PMID:19171903

A hybrid nanomemristor/transistor logic circuit capable of self-programming.

PubMed

Borghetti, Julien; Li, Zhiyong; Straznicky, Joseph; Li, Xuema; Ohlberg, Douglas A A; Wu, Wei; Stewart, Duncan R; Williams, R Stanley

2009-02-10

Memristor crossbars were fabricated at 40 nm half-pitch, using nanoimprint lithography on the same substrate with Si metal-oxide-semiconductor field effect transistor (MOS FET) arrays to form fully integrated hybrid memory resistor (memristor)/transistor circuits. The digitally configured memristor crossbars were used to perform logic functions, to serve as a routing fabric for interconnecting the FETs and as the target for storing information. As an illustrative demonstration, the compound Boolean logic operation (A AND B) OR (C AND D) was performed with kilohertz frequency inputs, using resistor-based logic in a memristor crossbar with FET inverter/amplifier outputs. By routing the output signal of a logic operation back onto a target memristor inside the array, the crossbar was conditionally configured by setting the state of a nonvolatile switch. Such conditional programming illuminates the way for a variety of self-programmed logic arrays, and for electronic synaptic computing.

Double-Barrier Memristive Devices for Unsupervised Learning and Pattern Recognition.

PubMed

Hansen, Mirko; Zahari, Finn; Ziegler, Martin; Kohlstedt, Hermann

2017-01-01

The use of interface-based resistive switching devices for neuromorphic computing is investigated. In a combined experimental and numerical study, the important device parameters and their impact on a neuromorphic pattern recognition system are studied. The memristive cells consist of a layer sequence Al/Al 2 O 3 /Nb x O y /Au and are fabricated on a 4-inch wafer. The key functional ingredients of the devices are a 1.3 nm thick Al 2 O 3 tunnel barrier and a 2.5 mm thick Nb x O y memristive layer. Voltage pulse measurements are used to study the electrical conditions for the emulation of synaptic functionality of single cells for later use in a recognition system. The results are evaluated and modeled in the framework of the plasticity model of Ziegler et al. Based on this model, which is matched to experimental data from 84 individual devices, the network performance with regard to yield, reliability, and variability is investigated numerically. As the network model, a computing scheme for pattern recognition and unsupervised learning based on the work of Querlioz et al. (2011), Sheridan et al. (2014), Zahari et al. (2015) is employed. This is a two-layer feedforward network with a crossbar array of memristive devices, leaky integrate-and-fire output neurons including a winner-takes-all strategy, and a stochastic coding scheme for the input pattern. As input pattern, the full data set of digits from the MNIST database is used. The numerical investigation indicates that the experimentally obtained yield, reliability, and variability of the memristive cells are suitable for such a network. Furthermore, evidence is presented that their strong I - V non-linearity might avoid the need for selector devices in crossbar array structures.

Observation of a Unipolar Field-aligned Current System Associated With IMF By-triggered Theta Auroras

NASA Astrophysics Data System (ADS)

Hairston, M. R.; Watanabe, M.

2016-12-01

We investigate the existence of a specific field-aligned current (FAC) system predicted by numerical magnetohydrodynamic simulations in a past study. The FAC system is expected to occur when a drifting theta aurora is formed in response to a stepwise transition of interplanetary magnetic field (IMF) By during strongly northward IMF periods. When the IMF By changes from positive to negative, a crossbar forms in the Northern Hemisphere that moves dawnward, while in the Southern Hemisphere the crossbar moves in the opposite direction. The crossbar motion reverses when the IMF By changes from negative to positive. The FAC system appears on the trailing side of the drifting crossbar of the theta aurora as it moves either dawnward or duskward. When the theta aurora is drifting dawnward, the FACs flow into the ionosphere. The FAC polarity reverses when the theta aurora is drifting duskward. Using low-altitude satellite data, we confirmed the real existence of the above model-predicted FAC system.

Implementation of digital equality comparator circuit on memristive memory crossbar array using material implication logic

NASA Astrophysics Data System (ADS)

Haron, Adib; Mahdzair, Fazren; Luqman, Anas; Osman, Nazmie; Junid, Syed Abdul Mutalib Al

2018-03-01

One of the most significant constraints of Von Neumann architecture is the limited bandwidth between memory and processor. The cost to move data back and forth between memory and processor is considerably higher than the computation in the processor itself. This architecture significantly impacts the Big Data and data-intensive application such as DNA analysis comparison which spend most of the processing time to move data. Recently, the in-memory processing concept was proposed, which is based on the capability to perform the logic operation on the physical memory structure using a crossbar topology and non-volatile resistive-switching memristor technology. This paper proposes a scheme to map digital equality comparator circuit on memristive memory crossbar array. The 2-bit, 4-bit, 8-bit, 16-bit, 32-bit, and 64-bit of equality comparator circuit are mapped on memristive memory crossbar array by using material implication logic in a sequential and parallel method. The simulation results show that, for the 64-bit word size, the parallel mapping exhibits 2.8× better performance in total execution time than sequential mapping but has a trade-off in terms of energy consumption and area utilization. Meanwhile, the total crossbar area can be reduced by 1.2× for sequential mapping and 1.5× for parallel mapping both by using the overlapping technique.

Arbitration in crossbar interconnect for low latency

DOEpatents

Ohmacht, Martin; Sugavanam, Krishnan

2013-02-05

A system and method and computer program product for reducing the latency of signals communicated through a crossbar switch, the method including using at slave arbitration logic devices associated with Slave devices for which access is requested from one or more Master devices, two or more priority vector signals cycled among their use every clock cycle for selecting one of the requesting Master devices and updates the respective priority vector signal used every clock cycle. Similarly, each Master for which access is requested from one or more Slave devices, can have two or more priority vectors and can cycle among their use every clock cycle to further reduce latency and increase throughput performance via the crossbar.

Variation and Defect Tolerance for Nano Crossbars

NASA Astrophysics Data System (ADS)

Tunc, Cihan

With the extreme shrinking in CMOS technology, quantum effects and manufacturing issues are getting more crucial. Hence, additional shrinking in CMOS feature size seems becoming more challenging, difficult, and costly. On the other hand, emerging nanotechnology has attracted many researchers since additional scaling down has been demonstrated by manufacturing nanowires, Carbon nanotubes as well as molecular switches using bottom-up manufacturing techniques. In addition to the progress in manufacturing, developments in architecture show that emerging nanoelectronic devices will be promising for the future system designs. Using nano crossbars, which are composed of two sets of perpendicular nanowires with programmable intersections, it is possible to implement logic functions. In addition, nano crossbars present some important features as regularity, reprogrammability, and interchangeability. Combining these features, researchers have presented different effective architectures. Although bottom-up nanofabrication can greatly reduce manufacturing costs, due to low controllability in the manufacturing process, some critical issues occur. Bottom- up nanofabrication process results in high variation compared to conventional top- down lithography used in CMOS technology. In addition, an increased failure rate is expected. Variation and defect tolerance methods used for conventional CMOS technology seem inadequate for adapting to emerging nano technology because the variation and the defect rate for emerging nano technology is much more than current CMOS technology. Therefore, variations and defect tolerance methods for emerging nano technology are necessary for a successful transition. In this work, in order to tolerate variations for crossbars, we introduce a framework that is established based on reprogrammability and interchangeability features of nano crossbars. This framework is shown to be applicable for both FET-based and diode-based nano crossbars. We present a characterization testing method which requires minimal number of test vectors. We formulate the variation optimization problem using Simulated Annealing with different optimization goals. Furthermore, we extend the framework for defect tolerance. Experimental results and comparison of proposed framework with exhaustive methods confirm its effectiveness for both variation and defect tolerance.

A non-destructive crossbar architecture of multi-level memory-based resistor

NASA Astrophysics Data System (ADS)

Sahebkarkhorasani, Seyedmorteza

Nowadays, researchers are trying to shrink the memory cell in order to increase the capacity of the memory system and reduce the hardware costs. In recent years, there has been a revolution in electronics by using fundamentals of physics to build a new memory for computer application in order to increase the capacity and decrease the power consumption. Increasing the capacity of the memory causes a growth in the chip area. From 1971 to 2012 semiconductor manufacturing process improved from 6mum to 22 mum. In May 2008, S.Williams stated that "it is time to stop shrinking". In his paper, he declared that the process of shrinking memory element has recently become very slow and it is time to use another alternative in order to create memory elements [9]. In this project, we present a new design of a memory array using the new element named Memristor [3]. Memristor is a two-terminal passive electrical element that relates the charge and magnetic flux to each other. The device remained unknown since 1971 when it was discovered by Chua and introduced as the fourth fundamental passive element like capacitor, inductor and resistor [3]. Memristor has a dynamic resistance and it can retain its previous value even after disconnecting the power supply. Due to this interesting behavior of the Memristor, it can be a good replacement for all of the Non-Volatile Memories (NVMs) in the near future. Combination of this newly introduced element with the nanowire crossbar architecture would be a great structure which is called Crossbar Memristor. Some frameworks have recently been introduced in literature that utilized Memristor crossbar array, but there are many challenges to implement the Memristor crossbar array due to fabrication and device limitations. In this work, we proposed a simple design of Memristor crossbar array architecture which uses input feedback in order to preserve its data after each read operation.

A multiply-add engine with monolithically integrated 3D memristor crossbar/CMOS hybrid circuit.

PubMed

Chakrabarti, B; Lastras-Montaño, M A; Adam, G; Prezioso, M; Hoskins, B; Payvand, M; Madhavan, A; Ghofrani, A; Theogarajan, L; Cheng, K-T; Strukov, D B

2017-02-14

Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore's law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applications. Hybrid CMOS/memristor circuits with CMOL (CMOS + "Molecular") architecture have been proposed to combine the extremely high density of the memristive devices with the robustness of CMOS technology, leading to terabit-scale memory and extremely efficient computing paradigm. In this work, we demonstrate a hybrid 3D CMOL circuit with 2 layers of memristive crossbars monolithically integrated on a pre-fabricated CMOS substrate. The integrated crossbars can be fully operated through the underlying CMOS circuitry. The memristive devices in both layers exhibit analog switching behavior with controlled tunability and stable multi-level operation. We perform dot-product operations with the 2D and 3D memristive crossbars to demonstrate the applicability of such 3D CMOL hybrid circuits as a multiply-add engine. To the best of our knowledge this is the first demonstration of a functional 3D CMOL hybrid circuit.

A multiply-add engine with monolithically integrated 3D memristor crossbar/CMOS hybrid circuit

PubMed Central

Chakrabarti, B.; Lastras-Montaño, M. A.; Adam, G.; Prezioso, M.; Hoskins, B.; Cheng, K.-T.; Strukov, D. B.

2017-01-01

Silicon (Si) based complementary metal-oxide semiconductor (CMOS) technology has been the driving force of the information-technology revolution. However, scaling of CMOS technology as per Moore’s law has reached a serious bottleneck. Among the emerging technologies memristive devices can be promising for both memory as well as computing applications. Hybrid CMOS/memristor circuits with CMOL (CMOS + “Molecular”) architecture have been proposed to combine the extremely high density of the memristive devices with the robustness of CMOS technology, leading to terabit-scale memory and extremely efficient computing paradigm. In this work, we demonstrate a hybrid 3D CMOL circuit with 2 layers of memristive crossbars monolithically integrated on a pre-fabricated CMOS substrate. The integrated crossbars can be fully operated through the underlying CMOS circuitry. The memristive devices in both layers exhibit analog switching behavior with controlled tunability and stable multi-level operation. We perform dot-product operations with the 2D and 3D memristive crossbars to demonstrate the applicability of such 3D CMOL hybrid circuits as a multiply-add engine. To the best of our knowledge this is the first demonstration of a functional 3D CMOL hybrid circuit. PMID:28195239

Field-programmable logic devices with optical input-output.

PubMed

Szymanski, T H; Saint-Laurent, M; Tyan, V; Au, A; Supmonchai, B

2000-02-10

A field-programmable logic device (FPLD) with optical I/O is described. FPLD's with optical I/O can have their functionality specified in the field by means of downloading a control-bit stream and can be used in a wide range of applications, such as optical signal processing, optical image processing, and optical interconnects. Our device implements six state-of-the-art dynamically programmable logic arrays (PLA's) on a 2 mm x 2 mm die. The devices were fabricated through the Lucent Technologies-Advanced Research Projects Agency-Consortium for Optical and Optoelectronic Technologies in Computing (Lucent/ARPA/COOP) workshop by use of 0.5-microm complementary metal-oxide semiconductor-self-electro-optic device technology and were delivered in 1998. All devices are fully functional: The electronic data paths have been verified at 200 MHz, and optical tests are pending. The device has been programmed to implement a two-stage optical switching network with six 4 x 4 crossbar switches, which can realize more than 190 x 10(6) unique programmable input-output permutations. The same device scaled to a 2 cm x 2 cm substrate could support as many as 4000 optical I/O and 1 Tbit/s of optical I/O bandwidth and offer fully programmable digital functionality with approximately 110,000 programmable logic gates. The proposed optoelectronic FPLD is also ideally suited to realizing dense, statically reconfigurable crossbar switches. We describe an attractive application area for such devices: a rearrangeable three-stage optical switch for a wide-area-network backbone, switching 1000 traffic streams at the OC-48 data rate and supporting several terabits of traffic.

Interfacing a high performance disk array file server to a Gigabit LAN

NASA Technical Reports Server (NTRS)

Seshan, Srinivasan; Katz, Randy H.

1993-01-01

Our previous prototype, RAID-1, identified several bottlenecks in typical file server architectures. The most important bottleneck was the lack of a high-bandwidth path between disk, memory, and the network. Workstation servers, such as the Sun-4/280, have very slow access to peripherals on busses far from the CPU. For the RAID-2 system, we addressed this problem by designing a crossbar interconnect, Xbus board, that provides a 40MB/s path between disk, memory, and the network interfaces. However, this interconnect does not provide the system CPU with low latency access to control the various interfaces. To provide a high data rate to clients on the network, we were forced to carefully and efficiently design the network software. A block diagram of the system hardware architecture is given. In the following subsections, we describe pieces of the RAID-2 file server hardware that had a significant impact on the design of the network interface.

Spatial Light Modulators as Optical Crossbar Switches

NASA Technical Reports Server (NTRS)

Juday, Richard

2003-01-01

A proposed method of implementing cross connections in an optical communication network is based on the use of a spatial light modulator (SLM) to form controlled diffraction patterns that connect inputs (light sources) and outputs (light sinks). Sources would typically include optical fibers and/or light-emitting diodes; sinks would typically include optical fibers and/or photodetectors. The sources and/or sinks could be distributed in two dimensions; that is, on planes. Alternatively or in addition, sources and/or sinks could be distributed in three dimensions -- for example, on curved surfaces or in more complex (including random) three-dimensional patterns.

Nanoscale content-addressable memory

NASA Technical Reports Server (NTRS)

Davis, Bryan (Inventor); Principe, Jose C. (Inventor); Fortes, Jose (Inventor)

2009-01-01

A combined content addressable memory device and memory interface is provided. The combined device and interface includes one or more one molecular wire crossbar memories having spaced-apart key nanowires, spaced-apart value nanowires adjacent to the key nanowires, and configurable switches between the key nanowires and the value nanowires. The combination further includes a key microwire-nanowire grid (key MNG) electrically connected to the spaced-apart key nanowires, and a value microwire-nanowire grid (value MNG) electrically connected to the spaced-apart value nanowires. A key or value MNGs selects multiple nanowires for a given key or value.

Neural network for control of rearrangeable Clos networks.

PubMed

Park, Y K; Cherkassky, V

1994-09-01

Rapid evolution in the field of communication networks requires high speed switching technologies. This involves a high degree of parallelism in switching control and routing performed at the hardware level. The multistage crossbar networks have always been attractive to switch designers. In this paper a neural network approach to controlling a three-stage Clos network in real time is proposed. This controller provides optimal routing of communication traffic requests on a call-by-call basis by rearranging existing connections, with a minimum length of rearrangement sequence so that a new blocked call request can be accommodated. The proposed neural network controller uses Paull's rearrangement algorithm, along with the special (least used) switch selection rule in order to minimize the length of rearrangement sequences. The functional behavior of our model is verified by simulations and it is shown that the convergence time required for finding an optimal solution is constant, regardless of the switching network size. The performance is evaluated for random traffic with various traffic loads. Simulation results show that applying the least used switch selection rule increases the efficiency in switch rearrangements, reducing the network convergence time. The implementation aspects are also discussed to show the feasibility of the proposed approach.

Flexible crossbar-structured resistive memory arrays on plastic substrates via inorganic-based laser lift-off.

PubMed

Kim, Seungjun; Son, Jung Hwan; Lee, Seung Hyun; You, Byoung Kuk; Park, Kwi-Il; Lee, Hwan Keon; Byun, Myunghwan; Lee, Keon Jae

2014-11-26

Crossbar-structured memory comprising 32 × 32 arrays with one selector-one resistor (1S-1R) components are initially fabricated on a rigid substrate. They are transferred without mechanical damage via an inorganic-based laser lift-off (ILLO) process as a result of laser-material interaction. Addressing tests of the transferred memory arrays are successfully performed to verify mitigation of cross-talk on a plastic substrate. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Crossbar H-mode drift-tube linac design with alternative phase focusing for muon linac

NASA Astrophysics Data System (ADS)

Otani, M.; Futatsukawa, K.; Hasegawa, K.; Kitamura, R.; Kondo, Y.; Kurennoy, S.

2017-07-01

We have developed a Crossbar H-mode (CH) drift-tube linac (DTL) design with an alternative phase focusing (APF) scheme for a muon linac, in order to measure the anomalous magnetic moment and electric dipole moment (EDM) of muons at the Japan Proton Accelerator Research Complex (J-PARC). The CH-DTL accelerates muons from β = v/c = 0.08 to 0.28 at an operational frequency of 324 MHz. The design and results are described in this paper.

Super non-linear RRAM with ultra-low power for 3D vertical nano-crossbar arrays.

PubMed

Luo, Qing; Xu, Xiaoxin; Liu, Hongtao; Lv, Hangbing; Gong, Tiancheng; Long, Shibing; Liu, Qi; Sun, Haitao; Banerjee, Writam; Li, Ling; Gao, Jianfeng; Lu, Nianduan; Liu, Ming

2016-08-25

Vertical crossbar arrays provide a cost-effective approach for high density three-dimensional (3D) integration of resistive random access memory. However, an individual selector device is not allowed to be integrated with the memory cell separately. The development of V-RRAM has impeded the lack of satisfactory self-selective cells. In this study, we have developed a high performance bilayer self-selective device using HfO2 as the memory switching layer and a mixed ionic and electron conductor as the selective layer. The device exhibits high non-linearity (>10(3)) and ultra-low half-select leakage (<0.1 pA). A four layer vertical crossbar array was successfully demonstrated based on the developed self-selective device. High uniformity, ultra-low leakage, sub-nA operation, self-compliance, and excellent read/write disturbance immunity were achieved. The robust array level performance shows attractive potential for low power and high density 3D data storage applications.

Memristor-CMOS hybrid integrated circuits for reconfigurable logic.

PubMed

Xia, Qiangfei; Robinett, Warren; Cumbie, Michael W; Banerjee, Neel; Cardinali, Thomas J; Yang, J Joshua; Wu, Wei; Li, Xuema; Tong, William M; Strukov, Dmitri B; Snider, Gregory S; Medeiros-Ribeiro, Gilberto; Williams, R Stanley

2009-10-01

Hybrid reconfigurable logic circuits were fabricated by integrating memristor-based crossbars onto a foundry-built CMOS (complementary metal-oxide-semiconductor) platform using nanoimprint lithography, as well as materials and processes that were compatible with the CMOS. Titanium dioxide thin-film memristors served as the configuration bits and switches in a data routing network and were connected to gate-level CMOS components that acted as logic elements, in a manner similar to a field programmable gate array. We analyzed the chips using a purpose-built testing system, and demonstrated the ability to configure individual devices, use them to wire up various logic gates and a flip-flop, and then reconfigure devices.

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.

A high performance linear equation solver on the VPP500 parallel supercomputer

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

Nakanishi, Makoto; Ina, Hiroshi; Miura, Kenichi

1994-12-31

This paper describes the implementation of two high performance linear equation solvers developed for the Fujitsu VPP500, a distributed memory parallel supercomputer system. The solvers take advantage of the key architectural features of VPP500--(1) scalability for an arbitrary number of processors up to 222 processors, (2) flexible data transfer among processors provided by a crossbar interconnection network, (3) vector processing capability on each processor, and (4) overlapped computation and transfer. The general linear equation solver based on the blocked LU decomposition method achieves 120.0 GFLOPS performance with 100 processors in the LIN-PACK Highly Parallel Computing benchmark.

Highball: A high speed, reserved-access, wide area network

NASA Technical Reports Server (NTRS)

Mills, David L.; Boncelet, Charles G.; Elias, John G.; Schragger, Paul A.; Jackson, Alden W.

1990-01-01

A network architecture called Highball and a preliminary design for a prototype, wide-area data network designed to operate at speeds of 1 Gbps and beyond are described. It is intended for applications requiring high speed burst transmissions where some latency between requesting a transmission and granting the request can be anticipated and tolerated. Examples include real-time video and disk-disk transfers, national filestore access, remote sensing, and similar applications. The network nodes include an intelligent crossbar switch, but have no buffering capabilities; thus, data must be queued at the end nodes. There are no restrictions on the network topology, link speeds, or end-end protocols. The end system, nodes, and links can operate at any speed up to the limits imposed by the physical facilities. An overview of an initial design approach is presented and is intended as a benchmark upon which a detailed design can be developed. It describes the network architecture and proposed access protocols, as well as functional descriptions of the hardware and software components that could be used in a prototype implementation. It concludes with a discussion of additional issues to be resolved in continuing stages of this project.

Reprogrammable logic in memristive crossbar for in-memory computing

NASA Astrophysics Data System (ADS)

Cheng, Long; Zhang, Mei-Yun; Li, Yi; Zhou, Ya-Xiong; Wang, Zhuo-Rui; Hu, Si-Yu; Long, Shi-Bing; Liu, Ming; Miao, Xiang-Shui

2017-12-01

Memristive stateful logic has emerged as a promising next-generation in-memory computing paradigm to address escalating computing-performance pressures in traditional von Neumann architecture. Here, we present a nonvolatile reprogrammable logic method that can process data between different rows and columns in a memristive crossbar array based on material implication (IMP) logic. Arbitrary Boolean logic can be executed with a reprogrammable cell containing four memristors in a crossbar array. In the fabricated Ti/HfO2/W memristive array, some fundamental functions, such as universal NAND logic and data transfer, were experimentally implemented. Moreover, using eight memristors in a 2  ×  4 array, a one-bit full adder was theoretically designed and verified by simulation to exhibit the feasibility of our method to accomplish complex computing tasks. In addition, some critical logic-related performances were further discussed, such as the flexibility of data processing, cascading problem and bit error rate. Such a method could be a step forward in developing IMP-based memristive nonvolatile logic for large-scale in-memory computing architecture.

Development of a microwave 20 x 20 switch matrix for 30/20 GHz SS-TDMA application

NASA Technical Reports Server (NTRS)

Cory, B. J.; Berkowitz, M.; Wallis, R.; Schiavone, A.; Shieh, D.; Campbell, J.

1982-01-01

The design and fabrication of a 3-8 GHz, 20 x 20 Satellite Switched-Time Division Multiple Access IF switch matrix applicable to a 30/20 GHz communications satellite are described. An assessment of switch architecture in 1980 concluded that the GaAs FET-based coupled crossbar switch matrix, incorporating high speed CMOS LSI logic for switch crosspoint addressing, would be the optimum technology available for communications satellite switching by 1982. This assessment was based on such factors as switching speed, bandwidth, off-state isolation, and reliability, over a 10-year mission life. A proof-of-concept model's construction and testing are presented.

Time-multiplexed, optically-addressed, gigabit optical crossbar switch

NASA Technical Reports Server (NTRS)

Lang, Robert J. (Inventor); Cheng, Li-Jen (Inventor); Maserjian, Joseph (Inventor)

1994-01-01

A time-multiplexed, optically-addressed, crossbar switch (38) is provided using a two-dimensional, optically-addressed, reflective spatial light modulator (O-SLM) (20). Since the optical addressing is time-multiplexed, only N addressing lines are required for an N.times.N crossbar, rather than the N.sup.2 lines needed in the prior art. This reduction in addressing lines makes possible the development of enormous crossbar switches, such as 100.times.100, for the first time. In addition, since data paths remain entirely in the optics domain, data speeds can reach the multi-gigabit level. In the switch, a row (40) of N inputs (42) at the read wavelength is spread over one axis of the O-SLM. The light is refocused along the other axis to an output array (48) of detectors (50), so that each input has the potential to talk to any one output. The O-SLM is normally off, i.e., non-reflective, so that the output is, in the absence of an input signal, zero. A one-dimensional array (52) of lasers (54) at the write wavelength is imaged onto the O-SLM. Each laser scans across an entire row of the O-SLM; where the laser is on, it turns on a portion of the O-SLM and establishes a connection between a particular input and a particular output. A full row is scanned in a time much shorter than the response time of the O-SLM, so that state of the O-SLM is capacitively stored and dynamically refreshed. The scanning is accomplished by tuning the wavelength of the laser and passing it through a grating, which sweeps the beam in space.

Scalable polylithic on-package integratable apparatus and method

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

Khare, Surhud; Somasekhar, Dinesh; Borkar, Shekhar Y.

Described is an apparatus which comprises: a first die including: a processing core; a crossbar switch coupled to the processing core; and a first edge interface coupled to the crossbar switch; and a second die including: a first edge interface positioned at a periphery of the second die and coupled to the first edge interface of the first die, wherein the first edge interface of the first die and the first edge interface of the second die are positioned across each other; a clock synchronization circuit coupled to the second edge interface; and a memory interface coupled to the clockmore » synchronization circuit.« less

An intelligent allocation algorithm for parallel processing

NASA Technical Reports Server (NTRS)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Optimal wavelength-space crossbar switches for supercomputer optical interconnects.

PubMed

Roudas, Ioannis; Hemenway, B Roe; Grzybowski, Richard R; Karinou, Fotini

2012-08-27

We propose a most economical design of the Optical Shared MemOry Supercomputer Interconnect System (OSMOSIS) all-optical, wavelength-space crossbar switch fabric. It is shown, by analysis and simulation, that the total number of on-off gates required for the proposed N × N switch fabric can scale asymptotically as N ln N if the number of input/output ports N can be factored into a product of small primes. This is of the same order of magnitude as Shannon's lower bound for switch complexity, according to which the minimum number of two-state switches required for the construction of a N × N permutation switch is log2 (N!).

Pattern Classification with Memristive Crossbar Circuits

DTIC Science & Technology

2016-03-31

Fig. 2a), with a Pt/Al2O3/ TiO2 -x/Ti/Pt memristor at each crosspoint, was fabricated using a standard lift-off patterning. The Al2O3/ TiO2 -x stack...Form SiO2/Si Pt (60 nm) TiO2 -x (30 nm) Ti (15 nm) Al2O3 (4 nm) Ta (5 nm) Pt (60 nm) VW- VR VW+ Voltage (V) -2.0 -1.5 -1.0 -0.5 0.0 0.5...circuit with integrated Al2O3/ TiO2 -x resistive switching devices: (a) micrograph of a 12×12-crosspoint crossbar; (b) typical quasi-dc I-V curves of

Resistor-logic demultiplexers for nanoelectronics based on constant-weight codes.

PubMed

Kuekes, Philip J; Robinett, Warren; Roth, Ron M; Seroussi, Gadiel; Snider, Gregory S; Stanley Williams, R

2006-02-28

The voltage margin of a resistor-logic demultiplexer can be improved significantly by basing its connection pattern on a constant-weight code. Each distinct code determines a unique demultiplexer, and therefore a large family of circuits is defined. We consider using these demultiplexers for building nanoscale crossbar memories, and determine the voltage margin of the memory system based on a particular code. We determine a purely code-theoretic criterion for selecting codes that will yield memories with large voltage margins, which is to minimize the ratio of the maximum to the minimum Hamming distance between distinct codewords. For the specific example of a 64 × 64 crossbar, we discuss what codes provide optimal performance for a memory.

Spacecraft in switch matrix for wide band service applicatons in 30/20 GHz communications satellite systems

NASA Technical Reports Server (NTRS)

Cory, B. J.

1982-01-01

Bandwidth, switching speed, off-state isolation, and reliability over a ten-year mission were factors in determining the optimum available technology for satellite communications switching in 1982. A proof of concept model for a 20 x 20 coupled crossbar switch matrix designed with FET devices for microwave switching and with high speed CMOS LIS for switch crosspoint addressing was fabricated and tested. Results show the design is feasible for application in a multichannel SS-TDMA communications system. Expandibility can readily be achieved with this design. A conceptual design study for a 100 x 100 switch matrix utilizing a coupled crossbar architecture implemented with a monolithic microwave integrated circuits revealed technology needs for high capacity switch matrices.

Crossbar nanoarchitectonics of the crosslinked self-assembled monolayer

PubMed Central

2014-01-01

A bottom-up approach was devised to build a crossbar device using the crosslinked SAM of the 5,5′-bis (mercaptomethyl)-2,2′-bipyridine-Ni2+ (BPD- Ni2+) on a gold surface. To avoid metal diffusion through the organic film, the author used (i) nanoscale bottom electrodes to reduce the probability of defects on the bottom electrodes and (ii) molecular crosslinked technology to avoid metal diffusion through the SAMs. The properties of the crosslinked self-assembled monolayer were determined by XPS. I-V characteristics of the device show thermally activated hopping transport. The implementation of this type of architecture will open up new vistas for a new class of devices for transport, storage, and computing. PMID:24994952

Configurable Crossbar Switch for Deterministic, Low-latency Inter-blade Communications in a MicroTCA Platform

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

Karamooz, Saeed; Breeding, John Eric; Justice, T Alan

As MicroTCA expands into applications beyond the telecommunications industry from which it originated, it faces new challenges in the area of inter-blade communications. The ability to achieve deterministic, low-latency communications between blades is critical to realizing a scalable architecture. In the past, legacy bus architectures accomplished inter-blade communications using dedicated parallel buses across the backplane. Because of limited fabric resources on its backplane, MicroTCA uses the carrier hub (MCH) for this purpose. Unfortunately, MCH products from commercial vendors are limited to standard bus protocols such as PCI Express, Serial Rapid IO and 10/40GbE. While these protocols have exceptional throughput capability,more » they are neither deterministic nor necessarily low-latency. To overcome this limitation, an MCH has been developed based on the Xilinx Virtex-7 690T FPGA. This MCH provides the system architect/developer complete flexibility in both the interface protocol and routing of information between blades. In this paper, we present the application of this configurable MCH concept to the Machine Protection System under development for the Spallation Neutron Sources's proton accelerator. Specifically, we demonstrate the use of the configurable MCH as a 12x4-lane crossbar switch using the Aurora protocol to achieve a deterministic, low-latency data link. In this configuration, the crossbar has an aggregate bandwidth of 48 GB/s.« less

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

PubMed

James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha

2017-06-01

Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.

Nanoelectronics from the bottom up.

PubMed

Lu, Wei; Lieber, Charles M

2007-11-01

Electronics obtained through the bottom-up approach of molecular-level control of material composition and structure may lead to devices and fabrication strategies not possible with top-down methods. This review presents a brief summary of bottom-up and hybrid bottom-up/top-down strategies for nanoelectronics with an emphasis on memories based on the crossbar motif. First, we will discuss representative electromechanical and resistance-change memory devices based on carbon nanotube and core-shell nanowire structures, respectively. These device structures show robust switching, promising performance metrics and the potential for terabit-scale density. Second, we will review architectures being developed for circuit-level integration, hybrid crossbar/CMOS circuits and array-based systems, including experimental demonstrations of key concepts such lithography-independent, chemically coded stochastic demultipluxers. Finally, bottom-up fabrication approaches, including the opportunity for assembly of three-dimensional, vertically integrated multifunctional circuits, will be critically discussed.

Application of nanomaterials in two-terminal resistive-switching memory devices

PubMed Central

Ouyang, Jianyong

2010-01-01

Nanometer materials have been attracting strong attention due to their interesting structure and properties. Many important practical applications have been demonstrated for nanometer materials based on their unique properties. This article provides a review on the fabrication, electrical characterization, and memory application of two-terminal resistive-switching devices using nanomaterials as the active components, including metal and semiconductor nanoparticles (NPs), nanotubes, nanowires, and graphenes. There are mainly two types of device architectures for the two-terminal devices with NPs. One has a triple-layer structure with a metal film sandwiched between two organic semiconductor layers, and the other has a single polymer film blended with NPs. These devices can be electrically switched between two states with significant different resistances, i.e. the ‘ON’ and ‘OFF’ states. These render the devices important application as two-terminal non-volatile memory devices. The electrical behavior of these devices can be affected by the materials in the active layer and the electrodes. Though the mechanism for the electrical switches has been in argument, it is generally believed that the resistive switches are related to charge storage on the NPs. Resistive switches were also observed on crossbars formed by nanotubes, nanowires, and graphene ribbons. The resistive switches are due to nanoelectromechanical behavior of the materials. The Coulombic interaction of transient charges on the nanomaterials affects the configurable gap of the crossbars, which results into significant change in current through the crossbars. These nanoelectromechanical devices can be used as fast-response and high-density memory devices as well. PMID:22110862

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

Selective positioning and integration of individual single-walled carbon nanotubes.

PubMed

Jiao, Liying; Xian, Xiaojun; Wu, Zhongyun; Zhang, Jin; Liu, Zhongfan

2009-01-01

We present a general selective positioning and integration technique for fabricating single-walled carbon nanotube (SWNT) circuits with preselected individual SWNTs as building blocks by utilizing poly(methyl methacrylate) (PMMA) thin film as a macroscopically handlable mediator. The transparency and marker-replicating capability of PMMA mediator allow the selective placement of chirality-specific nanotubes onto predesigned patterned surfaces with a resolution of ca. 1 mum. This technique is compatible with multiple operations and p-n conversion by chemical doping, which enables the construction of complex and logic circuits. As demonstrations of building SWNTs circuits, we fabricated a field effect inverter, a 2 x 2 all-SWNT crossbar field effect transistor (FET), and flexible FETs on plastic with this technique. This selective positioning approach can also be extended to construct purpose-directed architecture with various nanoscale building blocks.

Analysis of observational records of Dae-gyupyo in Joseon Dynasty

NASA Astrophysics Data System (ADS)

Mihn, Byeong-Hee; Lee, Ki-Won; Kim, Sang-Hyuk; Ahn, Young Sook; Lee, Yong Sam

2012-09-01

It is known that Dae-gyupyo (the Large Noon Gnomon) and So-gyupyo (the Small Noon Gnomon) were constructed in the reign of King Sejong (1418--1450) of the Joseon Dynasty. Gyupyo is an astronomical instrument for measuring the length of the shadow cast by a celestial body at the meridian passage time; it consists of two basic parts: a measuring scale and a vertical column. According to the Veritable Records of King Sejong and of King Myeongjong (1545--1567), the column of Dae-gyupyo was 40 Cheok (˜ 8 m) in height from the measuring scale and had a cross-bar, like the Guibiao of Shoujing Guo of the Yuan Dynasty in China. In the latter Veritable Records, three observations of the Sun on the date of the winter solstice and two of the full Moon on the first month in a luni-solar calendar are also recorded. In particular, the observational record of Dae-gyupyo for the Sun on Dec. 12, 1563 is ˜ 1 m shorter than the previous two records. To explain this, we investigated two possibilities: the vertical column was inclined, and the cross-bar was lowered. The cross-bar was attached to the column by a supporting arm; that should be installed at an angle of ˜ 36.9° to the north on the basis of a geometric structure inferred from the records of Yuanshi (History of the Yuan Dynasty). We found that it was possible that the vertical column was inclined ˜ 7.7° to the south or the supporting arm was tilted ˜ 58.3° downward. We suggest that the arm was tilted by ˜ 95° (= 36.9° + 58.3°).

Power harvesting for railroad track safety enhancement using vertical track displacement

NASA Astrophysics Data System (ADS)

Nelson, Carl A.; Platt, Stephen R.; Hansen, Sean E.; Fateh, Mahmood

2009-03-01

A significant portion of railroad infrastructure exists in areas that are relatively remote. Railroad crossings in these areas are typically only marked with reflective signage and do not have warning light systems or crossbars due to the cost of electrical infrastructure. Distributed sensor networks used for railroad track health monitoring applications would be useful in these areas, but the same limitation regarding electrical infrastructure exists. This motivates the search for a long-term, low-maintenance power supply solution for remote railroad deployment. This paper describes the development of a mechanical device for harvesting mechanical power from passing railcar traffic that can be used to supply electrical power to warning light systems at crossings and to remote networks of sensors via rechargeable batteries. The device is mounted to and spans two rail ties such that it directly harnesses the vertical displacement of the rail and attached ties and translates the linear motion into rotational motion. The rotational motion is amplified and mechanically rectified to rotate a PMDC generator that charges a system of batteries. A prototype was built and tested in a laboratory setting for verifying functionality of the design. Results indicate power production capabilities on the order of 10 W per device in its current form. This is sufficient for illuminating high-efficiency LED lights at a railroad crossing or for powering track-health sensor networks.

47 CFR 32.2211 - Non-digital switching.

Code of Federal Regulations, 2010 CFR

2010-10-01

... switching. (a) This account shall include: (1) Original cost of stored program control analog circuit-switching and associated equipment. (2) Cost of remote analog electronic circuit switches. (3) Original cost of non-electronic circuit-switching equipment such as Step-by-Step, Crossbar, and Other Electro...

47 CFR 32.2211 - Non-digital switching.

Code of Federal Regulations, 2013 CFR

2013-10-01

... switching. (a) This account shall include: (1) Original cost of stored program control analog circuit-switching and associated equipment. (2) Cost of remote analog electronic circuit switches. (3) Original cost of non-electronic circuit-switching equipment such as Step-by-Step, Crossbar, and Other Electro...

47 CFR 32.2211 - Non-digital switching.

Code of Federal Regulations, 2012 CFR

2012-10-01

... switching. (a) This account shall include: (1) Original cost of stored program control analog circuit-switching and associated equipment. (2) Cost of remote analog electronic circuit switches. (3) Original cost of non-electronic circuit-switching equipment such as Step-by-Step, Crossbar, and Other Electro...

47 CFR 32.2211 - Non-digital switching.

Code of Federal Regulations, 2011 CFR

2011-10-01

... switching. (a) This account shall include: (1) Original cost of stored program control analog circuit-switching and associated equipment. (2) Cost of remote analog electronic circuit switches. (3) Original cost of non-electronic circuit-switching equipment such as Step-by-Step, Crossbar, and Other Electro...

47 CFR 32.2211 - Non-digital switching.

Code of Federal Regulations, 2014 CFR

2014-10-01

... switching. (a) This account shall include: (1) Original cost of stored program control analog circuit-switching and associated equipment. (2) Cost of remote analog electronic circuit switches. (3) Original cost of non-electronic circuit-switching equipment such as Step-by-Step, Crossbar, and Other Electro...

Matching the laser generated p bunch into a crossbar-H drift tube linac

NASA Astrophysics Data System (ADS)

Almomani, A.; Droba, M.; Ratzinger, U.; Hofmann, I.

2012-05-01

Proton bunches with energies up to 30 MeV have been measured at the PHELIX laser. Because of the laser-plasma interactions at a power density of about 4×1019W/cm2, a total yield of 1.5×1013protons was produced. For the reference energy of 10 MeV, the yield within ±0.5MeV was exceeding 1010protons. The important topic for a further acceleration of the laser generated bunch is the matching into the acceptance of an rf accelerator stage. With respect to the high space charge forces and the transit energy range, only drift tube linacs seem adequate for this purpose. A crossbar H-type (CH) cavity was chosen as the linac structure. Optimum emittance values for the linac injection are compared with the available laser generated beam parameters. Options for beam matching into a CH structure by a pulsed magnetic solenoid and by using the simulation codes LASIN and LORASR are presented.

Implementation of Basic and Universal Gates In a single Circuit Based On Quantum-dot Cellular Automata Using Multi-Layer Crossbar Wire

NASA Astrophysics Data System (ADS)

Bhowmik, Dhrubajyoti; Saha, Apu Kr; Dutta, Paramartha; Nandi, Supratim

2017-08-01

Quantum-dot Cellular Automata (QCA) is one of the most substitutes developing nanotechnologies for electronic circuits, as a result of lower force utilization, higher speed and smaller size in correlation with CMOS innovation. The essential devices, a Quantum-dot cell can be utilized to logic gates and wires. As it is the key building block on nanotechnology circuits. By applying simple gates, the hardware requirements for a QCA circuit can be decreased and circuits can be less complex as far as level, delay and cell check. This article exhibits an unobtrusive methodology for actualizing novel upgraded simple and universal gates, which can be connected to outline numerous variations of complex QCA circuits. Proposed gates are straightforward in structure and capable as far as implementing any digital circuits. The main aim is to build all basic and universal gates in a simple circuit with and without crossbar-wire. Simulation results and physical relations affirm its handiness in actualizing each advanced circuit.

Proposal of a new electromechanical total artificial heart: the TAH Serpentina.

PubMed

Sauer, I M; Frank, J; Bücherl, E S

1999-03-01

A new type of energy converter for an electro-mechanical total artificial heart (TAH) based on the principle of a unidirectional moving motor is described. Named the TAH Serpentina, the concept consists of 2 major parts, a pendulum shaped movable element fixed on one side using a joint bearing and a special shaped drum cam. Pusher plates are mounted flexibly to the crossbar of the pendulum. A motor drives the special shaped drum cam linked to the pendulum through a ball bearing. The circular motion of the unidirectional moving brushless DC motor is transferred into the linear motion of the pendulum to drive the pusher plates. Using a crossbar with a variable length, the stroke of the pendulum and therefore the displaced blood volume is alterable. To achieve a variable length, an electric driven screw thread or a hydraulic system is possible. Comparable to the natural heart, cardiac output would be determined by frequency and stroke volume.

Ta2O5-memristor synaptic array with winner-take-all method for neuromorphic pattern matching

NASA Astrophysics Data System (ADS)

Truong, Son Ngoc; Van Pham, Khoa; Yang, Wonsun; Min, Kyeong-Sik; Abbas, Yawar; Kang, Chi Jung; Shin, Sangho; Pedrotti, Ken

2016-08-01

Pattern matching or pattern recognition is one of the elemental components that constitute the very complicated recalling and remembering process in human's brain. To realize this neuromorphic pattern matching, we fabricated and tested a 3 × 3 memristor synaptic array with the winner-take-all method in this research. In the measurement, first, the 3 × 3 Ta2O5 memristor array is programmed to store [LLL], [LHH], and [HLH], where L is a low-resistance state and H is a high-resistance state, at the 1st, 2nd, and 3rd columns, respectively. After the programming, three input patterns, [111], [100], and [010], are applied to the memristor synaptic array. From the measurement results, we confirm that all three input patterns can be recognized well by using a twin memristor crossbar with synaptic arrays. This measurement can be thought of as the first real verification of the twin memristor crossbar with memristive synaptic arrays for neuromorphic pattern recognition.

Silicon Modulators, Switches and Sub-systems for Optical Interconnect

NASA Astrophysics Data System (ADS)

Li, Qi

Silicon photonics is emerging as a promising platform for manufacturing and integrating photonic devices for light generation, modulation, switching and detection. The compatibility with existing CMOS microelectronic foundries and high index contrast in silicon could enable low cost and high performance photonic systems, which find many applications in optical communication, data center networking and photonic network-on-chip. This thesis first develops and demonstrates several experimental work on high speed silicon modulators and switches with record performance and novel functionality. A 8x40 Gb/s transmitter based on silicon microrings is first presented. Then an end-to-end link using microrings for Binary Phase Shift Keying (BPSK) modulation and demodulation is shown, and its performance with conventional BPSK modulation/ demodulation techniques is compared. Next, a silicon traveling-wave Mach- Zehnder modulator is demonstrated at data rate up to 56 Gb/s for OOK modulation and 48 Gb/s for BPSK modulation, showing its capability at high speed communication systems. Then a single silicon microring is shown with 2x2 full crossbar switching functionality, enabling optical interconnects with ultra small footprint. Then several other experiments in the silicon platform are presented, including a fully integrated in-band Optical Signal to Noise Ratio (OSNR) monitor, characterization of optical power upper bound in a silicon microring modulator, and wavelength conversion in a dispersion-engineered waveguide. The last part of this thesis is on network-level application of photonics, specically a broadcast-and-select network based on star coupler is introduced, and its scalability performance is studied. Finally a novel switch architecture for data center networks is discussed, and its benefits as a disaggregated network are presented.

RF design of 324 MHz superconducting (SC) CH cavity for 0.21 beta

NASA Astrophysics Data System (ADS)

Taletskiy, K.; Surkov, D.; Gusarova, M.

2017-12-01

The results of RF optimizations for 324 MHz SC cross-bar H-mode (CH) cavity for 0.21 beta are presented. Maximum surface electric field of 36 MV/m and a corresponding effective accelerating gradient of 7 MV/m have been achieved.

30 CFR 75.205 - Installation of roof support using mining machines with integral roof bolters.

Code of Federal Regulations, 2010 CFR

2010-07-01

... feet or more apart shall be installed with a wooden crossbar at least 3 inches thick and 8 inches wide... less than 9 feet apart shall be installed with a wooden plank at least 2 inches thick and 8 inches wide...

Resistive switching mechanism in the one diode-one resistor memory based on p+-Si/n-ZnO heterostructure revealed by in-situ TEM

NASA Astrophysics Data System (ADS)

Zhang, Lei; Zhu, Liang; Li, Xiaomei; Xu, Zhi; Wang, Wenlong; Bai, Xuedong

2017-03-01

One diode-one resistor (1D1R) memory is an effective architecture to suppress the crosstalk interference, realizing the crossbar network integration of resistive random access memory (RRAM). Herein, we designed a p+-Si/n-ZnO heterostructure with 1D1R function. Compared with the conventional multilayer 1D1R devices, the structure and fabrication technique can be largely simplified. The real-time imaging of formation/rupture process of conductive filament (CF) process demonstrated the RS mechanism by in-situ transmission electron microscopy (TEM). Meanwhile, we observed that the formed CF is only confined to the outside of depletion region of Si/ZnO pn junction, and the formation of CF does not degrade the diode performance, which allows the coexistence of RS and rectifying behaviors, revealing the 1D1R switching model. Furthermore, it has been confirmed that the CF is consisting of the oxygen vacancy by in-situ TEM characterization.

Coexistence of diode-like volatile and multilevel nonvolatile resistive switching in a ZrO2/TiO2 stack structure.

PubMed

Li, Yingtao; Yuan, Peng; Fu, Liping; Li, Rongrong; Gao, Xiaoping; Tao, Chunlan

2015-10-02

Diode-like volatile resistive switching as well as nonvolatile resistive switching behaviors in a Cu/ZrO₂/TiO₂/Ti stack are investigated. Depending on the current compliance during the electroforming process, either volatile resistive switching or nonvolatile resistive switching is observed. With a lower current compliance (<10 μA), the Cu/ZrO₂/TiO₂/Ti device exhibits diode-like volatile resistive switching with a rectifying ratio over 10(6). The permanent transition from volatile to nonvolatile resistive switching can be obtained by applying a higher current compliance of 100 μA. Furthermore, by using different reset voltages, the Cu/ZrO₂/TiO₂/Ti device exhibits multilevel memory characteristics with high uniformity. The coexistence of nonvolatile multilevel memory and diode-like volatile resistive switching behaviors in the same Cu/ZrO₂/TiO₂/Ti device opens areas of applications in high-density storage, logic circuits, neural networks, and passive crossbar memory selectors.

Performance and policy dimensions in internet routing

NASA Technical Reports Server (NTRS)

Mills, David L.; Boncelet, Charles G.; Elias, John G.; Schragger, Paul A.; Jackson, Alden W.; Thyagarajan, Ajit

1995-01-01

The Internet Routing Project, referred to in this report as the 'Highball Project', has been investigating architectures suitable for networks spanning large geographic areas and capable of very high data rates. The Highball network architecture is based on a high speed crossbar switch and an adaptive, distributed, TDMA scheduling algorithm. The scheduling algorithm controls the instantaneous configuration and swell time of the switch, one of which is attached to each node. In order to send a single burst or a multi-burst packet, a reservation request is sent to all nodes. The scheduling algorithm then configures the switches immediately prior to the arrival of each burst, so it can be relayed immediately without requiring local storage. Reservations and housekeeping information are sent using a special broadcast-spanning-tree schedule. Progress to date in the Highball Project includes the design and testing of a suite of scheduling algorithms, construction of software reservation/scheduling simulators, and construction of a strawman hardware and software implementation. A prototype switch controller and timestamp generator have been completed and are in test. Detailed documentation on the algorithms, protocols and experiments conducted are given in various reports and papers published. Abstracts of this literature are included in the bibliography at the end of this report, which serves as an extended executive summary.

Demonstration of optically controlled data routing with the use of multiple-quantum-well bistable and electro-optical devices.

PubMed

Koppa, P; Chavel, P; Oudar, J L; Kuszelewicz, R; Schnell, J P; Pocholle, J P

1997-08-10

We present experimental results on a 1-to-64-channel free-space photonic switching demonstration system based on GaAs/GaAlAs multiple-quantum-well active device arrays. Two control schemes are demonstrated: data transparent optical self-routing usable in a packet-switching environment and direct optical control with potential signal amplification for circuit switching. The self-routing operation relies on the optical recognition of the binary destination address coded in each packet header. Address decoding is implemented with elementary optical bistable devices and modulator pixels as all-optical latches and electro-optical and gates, respectively. All 60 defect-free channels of the system could be operated one by one, but the simultaneous operation of only three channels could be achieved mainly because of the spatial nonhomogeneities of the devices. Direct-control operation is based on directly setting the bistable device reflectivity with a variable-control beam power. This working mode turned out to be much more tolerant of spatial noises: 37 channels of the system could be operated simultaneously. Further development of the system to a crossbar of N inputs and M outputs and system miniaturization are also considered.

A Pt/TiO(2)/Ti Schottky-type selection diode for alleviating the sneak current in resistance switching memory arrays.

PubMed

Park, Woo Young; Kim, Gun Hwan; Seok, Jun Yeong; Kim, Kyung Min; Song, Seul Ji; Lee, Min Hwan; Hwang, Cheol Seong

2010-05-14

This study examined the properties of Schottky-type diodes composed of Pt/TiO(2)/Ti, where the Pt/TiO(2) and TiO(2)/Ti junctions correspond to the blocking and ohmic contacts, respectively, as the selection device for a resistive switching cross-bar array. An extremely high forward-to-reverse current ratio of approximately 10(9) was achieved at 1 V when the TiO(2) film thickness was 19 nm. TiO(2) film was grown by atomic layer deposition at a substrate temperature of 250 degrees C. Conductive atomic force microscopy revealed that the forward current flew locally, which limits the maximum forward current density to < 10 A cm(-2) for a large electrode (an area of approximately 60 000 microm(2)). However, the local current measurement showed a local forward current density as high as approximately 10(5) A cm(-2). Therefore, it is expected that this type of Schottky diode effectively suppresses the sneak current without adverse interference effects in a nano-scale resistive switching cross-bar array with high block density.

Optimization of chemical structure of Schottky-type selection diode for crossbar resistive memory.

PubMed

Kim, Gun Hwan; Lee, Jong Ho; Jeon, Woojin; Song, Seul Ji; Seok, Jun Yeong; Yoon, Jung Ho; Yoon, Kyung Jean; Park, Tae Joo; Hwang, Cheol Seong

2012-10-24

The electrical performances of Pt/TiO(2)/Ti/Pt stacked Schottky-type diode (SD) was systematically examined, and this performance is dependent on the chemical structures of the each layer and their interfaces. The Ti layers containing a tolerable amount of oxygen showed metallic electrical conduction characteristics, which was confirmed by sheet resistance measurement with elevating the temperature, transmission line measurement (TLM), and Auger electron spectroscopy (AES) analysis. However, the chemical structure of SD stack and resulting electrical properties were crucially affected by the dissolved oxygen concentration in the Ti layers. The lower oxidation potential of the Ti layer with initially higher oxygen concentration suppressed the oxygen deficiency of the overlying TiO(2) layer induced by consumption of the oxygen from TiO(2) layer. This structure results in the lower reverse current of SDs without significant degradation of forward-state current. Conductive atomic force microscopy (CAFM) analysis showed the current conduction through the local conduction paths in the presented SDs, which guarantees a sufficient forward-current density as a selection device for highly integrated crossbar array resistive memory.

A light for anaesthetists.

PubMed

Flowerdew, R M

1976-11-01

A new type of lighting device is incorporated into the ether screen cross-bar, enabling better illumination of the patient's face. A 12-V, DC power supply is used. The temperature, with vacuum-assisted cooling, should not cause burns to an unconscious patient. Assessment of patient colour was evaluated and found to be reliable. The lamp must not be used with flammable anaesthetic agents.

High-performance silicon photonic tri-state switch based on balanced nested Mach-Zehnder interferometer.

PubMed

Lu, Zeqin; Celo, Dritan; Mehrvar, Hamid; Bernier, Eric; Chrostowski, Lukas

2017-09-25

This work proposes a novel silicon photonic tri-state (cross/bar/blocking) switch, featuring high-speed switching, broadband operation, and crosstalk-free performance. The switch is designed based on a 2 × 2 balanced nested Mach-Zehnder interferometer structure with carrier injection phase tuning. As compared to silicon photonic dual-state (cross/bar) switches based on Mach-Zehnder interferometers with carrier injection phase tuning, the proposed switch not only has better performance in cross/bar switching but also provides an extra blocking state. The unique blocking state has a great advantage in applications of N × N switch fabrics, where idle switching elements in the fabrics can be configured to the blocking state for crosstalk suppression. According to our numerical experiments on a fully loaded 8 × 8 dilated Banyan switch fabric, the worst output crosstalk of the 8 × 8 switch can be dramatically suppressed by more than 50 dB, by assigning the blocking state to idle switching elements in the fabric. The results of this work can extend the functionality of silicon photonic switches and significantly improve the performance of on-chip N × N photonic switching technologies.

Utilizing Interlayer Excitons in Bilayer WS2 for Increased Photovoltaic Response in Ultrathin Graphene Vertical Cross-Bar Photodetecting Tunneling Transistors.

PubMed

Zhou, Yingqiu; Tan, Haijie; Sheng, Yuewen; Fan, Ye; Xu, Wenshuo; Warner, Jamie H

2018-04-19

Here we study the layer-dependent photoconductivity in Gr/WS 2 /Gr vertical stacked tunneling (VST) cross-bar devices made using two-dimensional (2D) materials all grown by chemical vapor deposition. The larger number of devices (>100) enables a statistically robust analysis on the comparative differences in the photovoltaic response of monolayer and bilayer WS 2 , which cannot be achieved in small batch devices made using mechanically exfoliated materials. We show a dramatic increase in photovoltaic response for Gr/WS 2 (2L)/Gr compared to monolayers because of the long inter- and intralayer exciton lifetimes and the small exciton binding energy (both interlayer and intralayer excitons) of bilayer WS 2 compared with that of monolayer WS 2 . Different doping levels and dielectric environments of top and bottom graphene electrodes result in a potential difference across a ∼1 nm vertical device, which gives rise to large electric fields perpendicular to the WS 2 layers that cause band structure modification. Our results show how precise control over layer number in all 2D VST devices dictates the photophysics and performance for photosensing applications.

Three-dimensional crossbar arrays of self-rectifying Si/SiO 2/Si memristors

DOE PAGES

Li, Can; Han, Lili; Jiang, Hao; ...

2017-06-05

Memristors are promising building blocks for the next generation memory, unconventional computing systems and beyond. Currently common materials used to build memristors are not necessarily compatible with the silicon dominant complementary metal-oxide-semiconductor (CMOS) technology. Furthermore, external selector devices or circuits are usually required in order for large memristor arrays to function properly, resulting in increased circuit complexity. Here we demonstrate fully CMOS-compatible, all-silicon based and self-rectifying memristors that negate the need for external selectors in large arrays. It consists of p- and n-type doped single crystalline silicon electrodes and a thin chemically produced silicon oxide switching layer. The device exhibitsmore » repeatable resistance switching behavior with high rectifying ratio (10 5), high ON/OFF conductance ratio (10 4) and attractive retention at 300 °C. We further build a 5-layer 3-dimensional (3D) crossbar array of 100 nm memristors by stacking fluid supported silicon membranes. The CMOS compatibility and self-rectifying behavior open up opportunities for mass production of memristor arrays and 3D hybrid circuits on full-wafer scale silicon and flexible substrates without increasing circuit complexity.« less

Nanoscale diffusive memristor crossbars as physical unclonable functions.

PubMed

Zhang, R; Jiang, H; Wang, Z R; Lin, P; Zhuo, Y; Holcomb, D; Zhang, D H; Yang, J J; Xia, Q

2018-02-08

Physical unclonable functions have emerged as promising hardware security primitives for device authentication and key generation in the era of the Internet of Things. Herein, we report novel physical unclonable functions built upon the crossbars of nanoscale diffusive memristors that translate the stochastic distribution of Ag clusters in a SiO 2 matrix into a random binary bitmap that serves as a device fingerprint. The random dispersion of Ag led to an uneven number of clusters at each cross-point, which in turn resulted in a stochastic ability to switch in the Ag:SiO 2 diffusive memristors in an array. The randomness of the dispersion was a barrier to fingerprint cloning and the unique fingerprints of each device were persistent after fabrication. Using an optimized fabrication procedure, we maximized the randomness and achieved an inter-class Hamming distance of 50.68%. We also discovered that the bits were not flipping after over 10 4 s at 400 K, suggesting superior reliability of our physical unclonable functions. In addition, our diffusive memristor-based physical unclonable functions were easy to fabricate and did not require complicated post-processing for digitization and thus, provide new opportunities in hardware security applications.

Self-Rectifying Effect in Resistive Switching Memory Using Amorphous InGaZnO

NASA Astrophysics Data System (ADS)

Lee, Jin-Woo; Kwon, Hyeon-Min; Kim, Myeong-Ho; Lee, Seung-Ryul; Kim, Young-Bae; Choi, Duck-Kyun

2014-05-01

Resistance random access memory (ReRAM) has received attention as next-generation memory because of its excellent operating properties and high density integration capability as a crossbar array. However, the application of the existing ReRAM as a crossbar array may lead to crosstalk between adjacent cells due to its symmetric I- V characteristics. In this study, the self-rectifying effect of contact between amorphous In-Ga-Zn-O (a-IGZO) and TaO x was examined in a Pt/a-IGZO/TaO x /Al2O3/W structure. The experimental results show not only self-rectifying behavior but also forming-free characteristics. During the deposition of a-IGZO on the TaO x , an oxygen-rich TaO x interfacial layer was formed. The rectifying effect was observed regardless of the interface formation and is believed to be associated with Schottky contact formation between a-IGZO and TaO x . The current level remained unchanged despite repeated DC sweep cycles. The low resistance state/high resistance state ratio was about 101 at a read voltage of -0.5 V, and the rectifying ratio was about 103 at ±2 V.

Spin orbit torque based electronic neuron

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

Sengupta, Abhronil, E-mail: asengup@purdue.edu; Choday, Sri Harsha; Kim, Yusung

2015-04-06

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step switching scheme, a charge current places the magnetization of a nano-magnet along the hard-axis, i.e., an unstable point for the magnet. In the second step, the SOT device (neuron) receives a current (from the synapses) which moves the magnetization from the unstable point to one of the two stable states. The polarity of the synaptic current encodes the excitatory and inhibitory nature of themore » neuron input and determines the final orientation of the magnetization. A resistive crossbar array, functioning as synapses, generates a bipolar current that is a weighted sum of the inputs. The simulation of a two layer feed-forward artificial neural network based on the SOT electronic neuron shows that it consumes ∼3× lower power than a 45 nm digital CMOS implementation, while reaching ∼80% accuracy in the classification of 100 images of handwritten digits from the MNIST dataset.« less

Cross/bar polymer electro-optic routing switch with broadband flatting spectral response over 130 nm: Principle, design and analysis

NASA Astrophysics Data System (ADS)

Zheng, Chuan-Tao; Zheng, Li-Hua; Luo, Qian-Qian; Liang, Lei; Ma, Chun-Sheng; Zhang, Da-Ming

2013-05-01

A novel non-resonance 2×2 polymer electro-optic (EO) switch with flatting spectral response is proposed by employing two-section reversed active Mach-Zehnder interferometers (MZIs), a passive middle directional coupler (M-DC) and two passive phase generating couplers (PGCs). Two crosstalk compensations are performed by optimizing the PGCs to broaden the spectrum under bar-state and optimizing the two active MZIs to broaden the spectrum under cross-state. The bar-state and cross-state voltages are 0 and ±4 V, respectively, with the two optimized MZI EO region lengths of 4068 and 5941 μm. Sufficiently considering wavelength dispersion of material and waveguide, a wide spectrum over 130 nm (1473-1603 nm) is achieved for dropping the crosstalk below -30 dB, and within this range, an insertion loss of 1.8-12.3 dB is observed. Under the same crosstalk level, this spectrum is over 2 times of that of the traditional 2×2 MZI switch (60 nm) based on the same materials. This broadband 2×2 switch is more attractive than our previously reported broadband 1×1 switch due to cross/bar routing operations other than simple ON/OFF functions.

A new torsion pendulum for gravitational reference sensor technology development.

PubMed

Ciani, Giacomo; Chilton, Andrew; Apple, Stephen; Olatunde, Taiwo; Aitken, Michael; Mueller, Guido; Conklin, John W

2017-06-01

We report on the design and sensitivity of a new torsion pendulum for measuring the performance of ultra-precise inertial sensors and for the development of associated technologies for space-based gravitational wave observatories and geodesy missions. The apparatus comprises a 1 m-long, 50 μm-diameter tungsten fiber that supports an inertial member inside a vacuum system. The inertial member is an aluminum crossbar with four hollow cubic test masses at each end. This structure converts the rotation of the torsion pendulum into translation of the test masses. Two test masses are enclosed in capacitive sensors which provide readout and actuation. These test masses are electrically insulated from the rest of the crossbar and their electrical charge is controlled by photoemission using fiber-coupled ultraviolet light emitting diodes. The capacitive readout measures the test mass displacement with a broadband sensitivity of 30 nm∕Hz and is complemented by a laser interferometer with a sensitivity of about 0.5 nm∕Hz. The performance of the pendulum, as determined by the measured residual torque noise and expressed in terms of equivalent force acting on a single test mass, is roughly 200 fN∕Hz around 2 mHz, which is about a factor of 20 above the thermal noise limit of the fiber.

Fabrication of Nano-Crossbar Resistive Switching Memory Based on the Copper-Tantalum Pentoxide-Platinum Device Structure

NASA Astrophysics Data System (ADS)

Olga Gneri, Paula; Jardim, Marcos

Resistive switching memory has been of interest lately not only for its simple metal-insulator-metal (MIM) structure but also for its promising ease of scalability an integration into current CMOS technologies like the Field Programmable Gate Arrays and other non-volatile memory applications. There are several resistive switching MIM combinations but under this scope of research, attention will be paid to the bipolar resistive switching characteristics and fabrication of Tantalum Pentaoxide sandwiched between platinum and copper. By changing the polarity of the voltage bias, this metal-insulator-metal (MIM) device can be switched between a high resistive state (OFF) and low resistive state (ON). The change in states is induced by an electrochemical metallization process, which causes a formation or dissolution of Cu metal filamentary paths in the Tantalum Pentaoxide insulator. There is very little thorough experimental information about the Cu-Ta 2O5-Pt switching characteristics when scaled to nanometer dimensions. In this light, the MIM structure was fabricated in a two-dimensional crossbar format. Also, with the limited available resources, a multi-spacer technique was formulated to localize the active device area in this MIM configuration to less than 20nm. This step is important in understanding the switching characteristics and reliability of this structure when scaled to nanometer dimensions.

On the origin of resistive switching volatility in Ni/TiO{sub 2}/Ni stacks

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

Cortese, Simone, E-mail: simone.cortese@soton.ac.uk; Trapatseli, Maria; Khiat, Ali

2016-08-14

Resistive switching and resistive random access memories have attracted huge interest for next generation nonvolatile memory applications, also thought to be able to overcome flash memories limitations when arranged in crossbar arrays. A cornerstone of their potential success is that the toggling between two distinct resistance states, usually a High Resistive State (HRS) and a Low Resistive State (LRS), is an intrinsic non-volatile phenomenon with the two states being thermodynamically stable. TiO{sub 2} is one of the most common materials known to support non-volatile RS. In this paper, we report a volatile resistive switching in a titanium dioxide thin filmmore » sandwiched by two nickel electrodes. The aim of this work is to understand the underlying physical mechanism that triggers the volatile effect, which is ascribed to the presence of a NiO layer at the bottom interface. The NiO layer alters the equilibrium between electric field driven filament formation and thermal enhanced ion diffusion, resulting in the volatile behaviour. Although the volatility is not ideal for non-volatile memory applications, it shows merit for access devices in crossbar arrays due to its high LRS/HRS ratio, which are also briefly discussed.« less

"What Do These Stones Mean?" Inscriptions on Stone from an Ancient Monastery in Ireland that Address Jewish-Christian Relations

ERIC Educational Resources Information Center

Shillington, V. George

2013-01-01

Etched on a stone from a monastery from the Middle Ages at a small village in County Roscommon in Ireland is a combination of Jewish and Christian symbols. The Menorah sits atop a cross. At the base of the cross and at both ends of the crossbar are three small extensions. The image is one of religious integration. Augustine, whose argument for the…

Silicon Micromachining in RF and Photonic Applications

NASA Technical Reports Server (NTRS)

Lin, Tsen-Hwang; Congdon, Phil; Magel, Gregory; Pang, Lily; Goldsmith, Chuck; Randall, John; Ho, Nguyen

1995-01-01

Texas Instruments (TI) has developed membrane and micromirror devices since the late 1970s. An eggcrate space membrane was used as the spatial light modulator in the early years. Discrete micromirrors supported by cantilever beams created a new era for micromirror devices. Torsional micromirror and flexure-beam micromirror devices were promising for mass production because of their stable supports. TI's digital torsional micromirror device is an amplitude modulator (known as the digital micromirror device (DMD) and is in production development, discussed elsewhere. We also use a torsional device for a 4 x 4 fiber-optic crossbar switch in a 2 cm x 2 cm package. The flexure-beam micromirror device is an analog phase modulator and is considered more efficient than amplitude modulators for use in optical processing systems. TI also developed millimeter-sized membranes for integrated optical switches for telecommunication and network applications. Using a member in radio frequency (RF) switch applications is a rapidly growing area because of the micromechanical device performance in microsecond-switching characteristics. Our preliminary membrane RF switch test structure results indicate promising speed and RF switching performance. TI collaborated with MIT for modeling of metal-based micromachining.

Reduction of Flow Diagrams to Unfolded Form Modulo Snarls.

DTIC Science & Technology

1987-04-14

the English name of the Greek letter zeta.) 1.) An unintelligent canonical method called the Ŗ-level crossbar/pole" representation (3cp). This... Second , it will make these pictorial representations (all of which go by the name fC. Even though this is an abuse of language , it is in the spirit...received an M.S. degree In computer and communications sciences from the University of Michigan. Bs Is currently teaching a course on assembly language

Non-blocking crossbar permutation engine with constant routing latency

NASA Technical Reports Server (NTRS)

Monacos, Steve P. (Inventor)

1994-01-01

The invention is embodied in an N x N crossbar for routing packets from a set of N input ports to a set of N output ports, each packet having a header identifying one of the output ports as its destination, including a plurality of individual links which carry individual packets. Each link has a link input end and a link output end, a plurality of switches. Each of the switches has at least top and bottom switch inputs connected to a corresponding pair of the link output ends and top and bottom switch outputs connected to a corresponding pair of link input ends, whereby each switch is connected to four different links. Each of the switches has an exchange state which routes packets from the top and bottom switch inputs to the bottom and top switch outputs, respectively, and a bypass state which routes packets from the top and bottom switch inputs to the top and bottom switch outputs, respectively. A plurality of individual controller devices governing respective switches for sensing from a header of a packet at each switch input for the identity of the destination output port of the packet and selecting one of the exchange and bypass states in accordance with the identity of the destination output port and with the location of the corresponding switch relative to the destination output port.

Nanowire nanocomputer as a finite-state machine.

PubMed

Yao, Jun; Yan, Hao; Das, Shamik; Klemic, James F; Ellenbogen, James C; Lieber, Charles M

2014-02-18

Implementation of complex computer circuits assembled from the bottom up and integrated on the nanometer scale has long been a goal of electronics research. It requires a design and fabrication strategy that can address individual nanometer-scale electronic devices, while enabling large-scale assembly of those devices into highly organized, integrated computational circuits. We describe how such a strategy has led to the design, construction, and demonstration of a nanoelectronic finite-state machine. The system was fabricated using a design-oriented approach enabled by a deterministic, bottom-up assembly process that does not require individual nanowire registration. This methodology allowed construction of the nanoelectronic finite-state machine through modular design using a multitile architecture. Each tile/module consists of two interconnected crossbar nanowire arrays, with each cross-point consisting of a programmable nanowire transistor node. The nanoelectronic finite-state machine integrates 180 programmable nanowire transistor nodes in three tiles or six total crossbar arrays, and incorporates both sequential and arithmetic logic, with extensive intertile and intratile communication that exhibits rigorous input/output matching. Our system realizes the complete 2-bit logic flow and clocked control over state registration that are required for a finite-state machine or computer. The programmable multitile circuit was also reprogrammed to a functionally distinct 2-bit full adder with 32-set matched and complete logic output. These steps forward and the ability of our unique design-oriented deterministic methodology to yield more extensive multitile systems suggest that proposed general-purpose nanocomputers can be realized in the near future.

Nanowire nanocomputer as a finite-state machine

PubMed Central

Yao, Jun; Yan, Hao; Das, Shamik; Klemic, James F.; Ellenbogen, James C.; Lieber, Charles M.

2014-01-01

Implementation of complex computer circuits assembled from the bottom up and integrated on the nanometer scale has long been a goal of electronics research. It requires a design and fabrication strategy that can address individual nanometer-scale electronic devices, while enabling large-scale assembly of those devices into highly organized, integrated computational circuits. We describe how such a strategy has led to the design, construction, and demonstration of a nanoelectronic finite-state machine. The system was fabricated using a design-oriented approach enabled by a deterministic, bottom–up assembly process that does not require individual nanowire registration. This methodology allowed construction of the nanoelectronic finite-state machine through modular design using a multitile architecture. Each tile/module consists of two interconnected crossbar nanowire arrays, with each cross-point consisting of a programmable nanowire transistor node. The nanoelectronic finite-state machine integrates 180 programmable nanowire transistor nodes in three tiles or six total crossbar arrays, and incorporates both sequential and arithmetic logic, with extensive intertile and intratile communication that exhibits rigorous input/output matching. Our system realizes the complete 2-bit logic flow and clocked control over state registration that are required for a finite-state machine or computer. The programmable multitile circuit was also reprogrammed to a functionally distinct 2-bit full adder with 32-set matched and complete logic output. These steps forward and the ability of our unique design-oriented deterministic methodology to yield more extensive multitile systems suggest that proposed general-purpose nanocomputers can be realized in the near future. PMID:24469812

Functional Circuitry on Commercial Fabric via Textile-Compatible Nanoscale Film Coating Process for Fibertronics.

PubMed

Bae, Hagyoul; Jang, Byung Chul; Park, Hongkeun; Jung, Soo-Ho; Lee, Hye Moon; Park, Jun-Young; Jeon, Seung-Bae; Son, Gyeongho; Tcho, Il-Woong; Yu, Kyoungsik; Im, Sung Gap; Choi, Sung-Yool; Choi, Yang-Kyu

2017-10-11

Fabric-based electronic textiles (e-textiles) are the fundamental components of wearable electronic systems, which can provide convenient hand-free access to computer and electronics applications. However, e-textile technologies presently face significant technical challenges. These challenges include difficulties of fabrication due to the delicate nature of the materials, and limited operating time, a consequence of the conventional normally on computing architecture, with volatile power-hungry electronic components, and modest battery storage. Here, we report a novel poly(ethylene glycol dimethacrylate) (pEGDMA)-textile memristive nonvolatile logic-in-memory circuit, enabling normally off computing, that can overcome those challenges. To form the metal electrode and resistive switching layer, strands of cotton yarn were coated with aluminum (Al) using a solution dip coating method, and the pEGDMA was conformally applied using an initiated chemical vapor deposition process. The intersection of two Al/pEGDMA coated yarns becomes a unit memristor in the lattice structure. The pEGDMA-Textile Memristor (ETM), a form of crossbar array, was interwoven using a grid of Al/pEGDMA coated yarns and untreated yarns. The former were employed in the active memristor and the latter suppressed cell-to-cell disturbance. We experimentally demonstrated for the first time that the basic Boolean functions, including a half adder as well as NOT, NOR, OR, AND, and NAND logic gates, are successfully implemented with the ETM crossbar array on a fabric substrate. This research may represent a breakthrough development for practical wearable and smart fibertronics.

Comparison of two anaerobic water polo-specific tests with the Wingate test.

PubMed

Bampouras, Theodoros M; Marrin, Kelly

2009-01-01

The purpose of the current study was to compare 2 water polo-specific tests-the 14 x 25-m swims (SWIM) and the 30-second crossbar jumps (30CJ)-with a laboratory-based test of anaerobic power, the Wingate Anaerobic Test (WAnT). Thirteen elite women's water polo players (mean +/- SD: age 22.0 +/- 4.4 years, height 168.7 +/- 7.9 cm, body mass 65.9 +/- 6.1 kg, body fat 23.6 +/- 3.5 %, maximum oxygen uptake 51.4 +/- 4.5 mlxkgxmin) participated in the study. The SWIM involved 14 repeated "all-out" sprints every 30 seconds. Swimming time was recorded, and sprint velocity, mean velocity (Vmean), and the gradient of the linear regression equation (GRADIENT) were calculated. The 30CJ involved repeated in-water water polo jumps and touching the goal crossbar with both hands. The number of touches in 30 seconds was recorded. Additionally, the subjects completed a 30-second WAnT, and mean power (Mp) and fatigue index (FI) were calculated. Kendall tau (tau) rank correlation was used to examine for correlation between ranks. Significance level was set at p

Architecture design of resistor/FET-logic demultiplexer for hybrid CMOS/nanodevice circuit interconnect.

PubMed

Li, Shu; Zhang, Tong

2008-05-07

Hybrid nanoelectronics consisting of nanodevice crossbars on top of CMOS backplane circuits is emerging as one viable option to sustain Moore's law after the CMOS scaling limit is reached. One main design challenge in such hybrid nanoelectronics is the interface between the highly dense nanowires in nanodevice crossbars and relatively coarse microwires in the CMOS domain. Such an interface can be realized through a logic circuit called a demultiplexer (demux). In this context, all the prior work on demux design uses a single type of device, such as resistor, diode or field effect transistor (FET), to realize the demultiplexing function. However, different types of devices have their own advantages and disadvantages in terms of functionality, manufacturability, speed and power consumption. This makes none of them provide a satisfactory solution. To tackle this challenge, this work proposes to combine resistor with FET to implement the demux, leading to the hybrid resistor/FET-logic demux. Such hybrid demux architecture can make these two types of devices complement each other well to improve the overall demux design effectiveness. Furthermore, due to the inevitable fabrication process variations at the nanoscale, the effects of resistor conductance and FET threshold voltage variability are analyzed and evaluated based on computer simulations. The simulation results provide the requirement on the fabrication process to ensure a high demux reliability, and promise the hybrid resistor/FET-logic demux an improved addressability and process variance tolerance.

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications

PubMed Central

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O.

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n2 memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach. PMID:26578867

Generalized reconfigurable memristive dynamical system (MDS) for neuromorphic applications.

PubMed

Bavandpour, Mohammad; Soleimani, Hamid; Linares-Barranco, Bernabé; Abbott, Derek; Chua, Leon O

2015-01-01

This study firstly presents (i) a novel general cellular mapping scheme for two dimensional neuromorphic dynamical systems such as bio-inspired neuron models, and (ii) an efficient mixed analog-digital circuit, which can be conveniently implemented on a hybrid memristor-crossbar/CMOS platform, for hardware implementation of the scheme. This approach employs 4n memristors and no switch for implementing an n-cell system in comparison with 2n (2) memristors and 2n switches of a Cellular Memristive Dynamical System (CMDS). Moreover, this approach allows for dynamical variables with both analog and one-hot digital values opening a wide range of choices for interconnections and networking schemes. Dynamical response analyses show that this circuit exhibits various responses based on the underlying bifurcation scenarios which determine the main characteristics of the neuromorphic dynamical systems. Due to high programmability of the circuit, it can be applied to a variety of learning systems, real-time applications, and analytically indescribable dynamical systems. We simulate the FitzHugh-Nagumo (FHN), Adaptive Exponential (AdEx) integrate and fire, and Izhikevich neuron models on our platform, and investigate the dynamical behaviors of these circuits as case studies. Moreover, error analysis shows that our approach is suitably accurate. We also develop a simple hardware prototype for experimental demonstration of our approach.

The Pasm Parallel Processing System: Design, Simulation, and Image Processing Applications. Volume 1

DTIC Science & Technology

1989-12-31

was not funded and the author and other members of the PASM group turned their attention to related studies such as the further definition of the... Four such quadrants comprise the set of MCs and PEs. The logical PE i within each MC group is serviced by MSU i. Figure 1.9.3 shows that the MSUs are...instead of four Data Input Queues and with a 4-by-4 instead of a 2-by-2 crossbar switch could be designed. Studies indicate that the perfor- mance of a

Lattice QCD calculation using VPP500

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

Kim, Seyong; Ohta, Shigemi

1995-02-01

A new vector parallel supercomputer, Fujitsu VPP500, was installed at RIKEN earlier this year. It consists of 30 vector computers, each with 1.6 GFLOPS peak speed and 256 MB memory, connected by a crossbar switch with 400 MB/s peak data transfer rate each way between any pair of nodes. The authors developed a Fortran lattice QCD simulation code for it. It runs at about 1.1 GFLOPS sustained per node for Metropolis pure-gauge update, and about 0.8 GFLOPS sustained per node for conjugate gradient inversion of staggered fermion matrix.

Development and preliminary evaluation of an ultrasonic motor actuated needle guide for 3T MRI-guided transperineal prostate interventions

NASA Astrophysics Data System (ADS)

Song, Sang-Eun; Tokuda, Junichi; Tuncali, Kemal; Tempany, Clare; Hata, Nobuhiko

2012-02-01

Image guided prostate interventions have been accelerated by Magnetic Resonance Imaging (MRI) and robotic technologies in the past few years. However, transrectal ultrasound (TRUS) guided procedure still remains as vast majority in clinical practice due to engineering and clinical complexity of the MRI-guided robotic interventions. Subsequently, great advantages and increasing availability of MRI have not been utilized at its maximum capacity in clinic. To benefit patients from the advantages of MRI, we developed an MRI-compatible motorized needle guide device "Smart Template" that resembles a conventional prostate template to perform MRI-guided prostate interventions with minimal changes in the clinical procedure. The requirements and specifications of the Smart Template were identified from our latest MRI-guided intervention system that has been clinically used in manual mode for prostate biopsy. Smart Template consists of vertical and horizontal crossbars that are driven by two ultrasonic motors via timing-belt and mitergear transmissions. Navigation software that controls the crossbar position to provide needle insertion positions was also developed. The software can be operated independently or interactively with an open-source navigation software, 3D Slicer, that has been developed for prostate intervention. As preliminary evaluation, MRI distortion and SNR test were conducted. Significant MRI distortion was found close to the threaded brass alloy components of the template. However, the affected volume was limited outside the clinical region of interest. SNR values over routine MRI scan sequences for prostate biopsy indicated insignificant image degradation during the presence of the robotic system and actuation of the ultrasonic motors.

Multiple-Ring Digital Communication Network

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

Photonics in Switching. Organization of the 1993 Photonics Science Topical Meetings Held in Palm Springs, California on March 15 - 17, 1993. Technical Digest

DTIC Science & Technology

1993-03-17

placed on the number of inputs and outputs. For the TeO2 material used in this design, the TB is approximately 1000. Due to the over-resolved...Design of the acoustooptic crossbar switch Figure 2 shows a numerical simulation of the momentum space of an 8 by 8 switch in TeO2 . This switch...results Figure 4 shows switching results from a preliminary demonstration of a three by three switch in a beam-steered flint glass cell. The scope trace

A new species of the genus Opisthotropis Gunther, 1872 (Squamata: Colubridae: Natricinae) from Guangdong Province, China.

PubMed

Yang, Jian-huan; Sung, Yik-hei; Chan, Bosco Pui-Lok

2013-01-01

A new natricid snake of the genus Opisthotropis Gunther, 1872, Opisthotropis laui sp. nov., is described from Mt. Gudou, Jiangmen City, Guangdong Province, China. The new species can be distinguished from other congeners by the combination of the following characters: dorsal scales weakly keeled throughout, in 25:23:23 rows; 10 supralabials; 11 infralabials; two internasals, longer than wide, not touching the loreal; one loreal, not touching the eye; one preocular; two postoculars; one anterior temporal scale; 152 ventrals; 53 subcaudals; body and tail dark olive above, with light yellow crossbars.

Precessional switching of a perpendicular anisotropy magneto-tunneling junction without a magnetic field

NASA Astrophysics Data System (ADS)

Drobitch, Justine L.; Ahsanul Abeed, Md; Bandyopadhyay, Supriyo

2017-10-01

We describe an approach to implement precessional switching of a perpendicular-magnetic-anisotropy magneto-tunneling-junction (p-MTJ) without using any magnetic field. The switching is accomplished with voltage-controlled-magnetic-anisotropy (VCMA), spin transfer torque (STT) and mechanical strain. The soft layer of the p-MTJ is magnetostrictive and the strain acts as an effective in-plane magnetic field around which the magnetization of the soft layer precesses to complete a flip. A two-terminal energy-efficient p-MTJ based memory cell, that is compatible with crossbar architecture and high cell density, is designed.

Power- and Low-Resistance-State-Dependent, Bipolar Reset-Switching Transitions in SiN-Based Resistive Random-Access Memory

NASA Astrophysics Data System (ADS)

Kim, Sungjun; Park, Byung-Gook

2016-08-01

A study on the bipolar-resistive switching of an Ni/SiN/Si-based resistive random-access memory (RRAM) device shows that the influences of the reset power and the resistance value of the low-resistance state (LRS) on the reset-switching transitions are strong. For a low LRS with a large conducting path, the sharp reset switching, which requires a high reset power (>7 mW), was observed, whereas for a high LRS with small multiple-conducting paths, the step-by-step reset switching with a low reset power (<7 mW) was observed. The attainment of higher nonlinear current-voltage ( I-V) characteristics in terms of the step-by-step reset switching is due to the steep current-increased region of the trap-controlled space charge-limited current (SCLC) model. A multilevel cell (MLC) operation, for which the reset stop voltage ( V STOP) is used in the DC sweep mode and an incremental amplitude is used in the pulse mode for the step-by-step reset switching, is demonstrated here. The results of the present study suggest that well-controlled conducting paths in a SiN-based RRAM device, which are not too strong and not too weak, offer considerable potential for the realization of low-power and high-density crossbar-array applications.

High hopes: can molecular electronics realise its potential?

PubMed

Coskun, Ali; Spruell, Jason M; Barin, Gokhan; Dichtel, William R; Flood, Amar H; Botros, Youssry Y; Stoddart, J Fraser

2012-07-21

Manipulating and controlling the self-organisation of small collections of molecules, as an alternative to investigating individual molecules, has motivated researchers bent on processing and storing information in molecular electronic devices (MEDs). Although numerous ingenious examples of single-molecule devices have provided fundamental insights into their molecular electronic properties, MEDs incorporating hundreds to thousands of molecules trapped between wires in two-dimensional arrays within crossbar architectures offer a glimmer of hope for molecular memory applications. In this critical review, we focus attention on the collective behaviour of switchable mechanically interlocked molecules (MIMs)--specifically, bistable rotaxanes and catenanes--which exhibit reset lifetimes between their ON and OFF states ranging from seconds in solution to hours in crossbar devices. When these switchable MIMs are introduced into high viscosity polymer matrices, or self-assembled as monolayers onto metal surfaces, both in the form of nanoparticles and flat electrodes, or organised as tightly packed islands of hundreds and thousands of molecules sandwiched between two electrodes, the thermodynamics which characterise their switching remain approximately constant while the kinetics associated with their reset follow an intuitively predictable trend--that is, fast when they are free in solution and sluggish when they are constrained within closely packed monolayers. The importance of seamless interactions and constant feedback between the makers, the measurers and the modellers in establishing the structure-property relationships in these integrated functioning systems cannot be stressed enough as rationalising the many different factors that impact device performance becomes more and more demanding. The choice of electrodes, as well as the self-organised superstructures of the monolayers of switchable MIMs employed in the molecular switch tunnel junctions (MSTJs) associated with the crossbars of these MEDs, have a profound influence on device operation and performance. It is now clear, after much investigation, that a distinction should be drawn between two types of switching that can be elicited from MSTJs. One affords small ON/OFF ratios and is a direct consequence of the switching in bistable MIMs that leads to a relatively small remnant molecular signature--an activated chemical process. The other leads to a very much larger signature and ON/OFF ratios resulting from physical or chemical changes in the electrodes themselves. Control experiments with various compounds, including degenerate catenanes and free dumbbells, which cannot and do not switch, are crucial in establishing the authenticity of the small ON/OFF ratios and remnant molecular signatures produced by bistable MIMs. Moreover, experiments conducted on monolayers in MSTJs of molecules designed to switch and molecules designed not to switch have been probed directly by spectroscopic and other means in support of MEDs that store information through switching collections of bistable MIMs contained in arrays of MSTJs. In the quest for the next generation of MEDs, it is likely that monolayers of bistable MIMs will be replaced by robust crystalline extended structures wherein the switchable components, derived from bistable MIMs, are organised precisely in a periodic manner.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Synchronization in Complex Networks with Multiple Connections

NASA Astrophysics Data System (ADS)

Wu, Qing-Chu; Fu, Xin-Chu; Sun, Wei-Gang

2010-01-01

In this paper a class of networks with multiple connections are discussed. The multiple connections include two different types of links between nodes in complex networks. For this new model, we give a simple generating procedure. Furthermore, we investigate dynamical synchronization behavior in a delayed two-layer network, giving corresponding theoretical analysis and numerical examples.

Bayesian module identification from multiple noisy networks.

PubMed

Zamani Dadaneh, Siamak; Qian, Xiaoning

2016-12-01

Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of vertices in these networks that are topologically cohesive with similar interaction patterns with the rest of the vertices. Most of the existing module identification algorithms assume that the given networks are faithfully measured without errors. However, in many real-world applications, for example, when analyzing protein-protein interaction networks from high-throughput profiling techniques, there is significant noise with both false positive and missing links between vertices. In this paper, we propose a new model for more robust module identification by taking advantage of multiple observed networks with significant noise so that signals in multiple networks can be strengthened and help improve the solution quality by combining information from various sources. We adopt a hierarchical Bayesian model to integrate multiple noisy snapshots that capture the underlying modular structure of the networks under study. By introducing a latent root assignment matrix and its relations to instantaneous module assignments in all the observed networks to capture the underlying modular structure and combine information across multiple networks, an efficient variational Bayes algorithm can be derived to accurately and robustly identify the underlying modules from multiple noisy networks. Experiments on synthetic and protein-protein interaction data sets show that our proposed model enhances both the accuracy and resolution in detecting cohesive modules, and it is less vulnerable to noise in the observed data. In addition, it shows higher power in predicting missing edges compared to individual-network methods.

The US Network of Pediatric Multiple Sclerosis Centers: Development, Progress, and Next Steps.

PubMed

Casper, T Charles; Rose, John W; Roalstad, Shelly; Waubant, Emmanuelle; Aaen, Gregory; Belman, Anita; Chitnis, Tanuja; Gorman, Mark; Krupp, Lauren; Lotze, Timothy E; Ness, Jayne; Patterson, Marc; Rodriguez, Moses; Weinstock-Guttman, Bianca; Browning, Brittan; Graves, Jennifer; Tillema, Jan-Mendelt; Benson, Leslie; Harris, Yolanda

2015-09-01

Multiple sclerosis and other demyelinating diseases in the pediatric population have received an increasing level of attention by clinicians and researchers. The low incidence of these diseases in children creates a need for the involvement of multiple clinical centers in research efforts. The Network of Pediatric Multiple Sclerosis Centers was created initially in 2006 to improve the diagnosis and care of children with demyelinating diseases. In 2010, the Network shifted its focus to multicenter research while continuing to advance the care of patients. The Network has obtained support from the National Multiple Sclerosis Society, the Guthy-Jackson Charitable Foundation, and the National Institutes of Health. The Network will continue to serve as a platform for conducting impactful research in pediatric demyelinating diseases of the central nervous system. This article provides a description of the history and development, organization, mission, research priorities, current studies, and future plans of the Network. © The Author(s) 2014.

The US Network of Pediatric Multiple Sclerosis Centers: Development, Progress, and Next Steps

PubMed Central

Casper, T. Charles; Rose, John W.; Roalstad, Shelly; Waubant, Emmanuelle; Aaen, Gregory; Belman, Anita; Chitnis, Tanuja; Gorman, Mark; Krupp, Lauren; Lotze, Timothy E.; Ness, Jayne; Patterson, Marc; Rodriguez, Moses; Weinstock-Guttman, Bianca; Browning, Brittan; Graves, Jennifer; Tillema, Jan-Mendelt; Benson, Leslie; Harris, Yolanda

2014-01-01

Multiple sclerosis and other demyelinating diseases in the pediatric population have received an increasing level of attention by clinicians and researchers. The low incidence of these diseases in children creates a need for the involvement of multiple clinical centers in research efforts. The Network of Pediatric Multiple Sclerosis Centers was created initially in 2006 to improve the diagnosis and care of children with demyelinating diseases. In 2010, the Network shifted its focus to multicenter research while continuing to advance the care of patients. The Network has obtained support from the National Multiple Sclerosis Society, the Guthy-Jackson Charitable Foundation, and the National Institutes of Health. The Network will continue to serve as a platform for conducting impactful research in pediatric demyelinating diseases of the central nervous system. This article provides a description of the history and development, organization, mission, research priorities, current studies, and future plans of the Network. PMID:25270659

CRISTISPIRA IN NORTH AMERICAN SHELLFISH. A NOTE ON A SPIRILLUM FOUND IN OYSTERS.

PubMed

Noguchi, H

1921-08-31

Ten varieties of North American shellfish were examined for the occurrence of Cristispira in their styles. A cristispira was found in various numbers in Ostrea virginiana, Venus mercenaria, and Modiola modiolus, but none in Ensis americana, Mya arenaria, Mactra solidissima, Pecten irradians, Mytilus edulis, Fulgur canaliculatus, or Nassa obsoleta. Of 298 oysters, only 128 showed the crystalline styles, in which cristispiras were present in 99. Active cristispiras were found in 59 styles only and degenerated forms in the remaining 40. In 110 clams (Venus mercenaria) 70 styles were found, and only 8 of these contained cristispiras; 5 yielded active and the other 3 degenerated cristispiras. In 97 modiolas there were 73 styles, only 4 of which contained cristispiras. The physical properties of the crystalline styles of these shellfish varied considerably. The styles of the oysters were moderately soft, and when exposed to the air or mixed with sea water they underwent liquefaction, forming a clear, viscid material. The styles from clams and modiolas were opaque and were more firm, not easily crushed even in a mortar. The styles of the scallops were the most solid of all the styles examined. It happened that the softer the styles, the more frequent was the occurrence of the cristispira; in fact, no cristispira was detected in styles other than those of oysters, clams, and modiolas, of which oysters had the softest styles and the largest percentage of cristispira invasion. The following observations were made regarding the structure of the cristispira found in oysters. The body is a long, flexible cylinder, with blunt extremities, towards which the diameter gradually diminishes. In motion the body rapidly stretches and contracts, forming in the contracted state several serpentine undulations. A membranous appendage (Gross' crista) winds about the body throughout its entire length. The inner margin is in connection with the body, the outer margin is free and is distinctly heavier. The latter is undulatory; that is, the width of the membrane, or crista, is narrower at some points than at others. The membrane is composed of numerous fine fibrils running in a roughly parallel or slightly oblique course, showing interwoven narrow meshes; at the outer margin there is a dense smooth ridge. The contour of the body is highly refractive, as if possessing a cell membrane. The interior structure, as revealed by dark-field illumination, is an almost homogeneous, less refractive substance, but there are present minute highly refractive granules more or less symmetrically arranged. There is no definite cross-bar or chambered structure. On the other hand, when vital staining with brilliant cresyl blue is applied, there appear numerous paired masses of lavender hue at fairly regular intervals, suggesting the cross-bar aspect of a stained specimen. In a few specimens there was seen a dim outline of cross-bar effect. Neutral red, Bismarck brown, and crystal violet all bring out deeply stained granules and reticular structure but no definite cross-bars. The crista is a fibrillar structure, connected with the body at its inner edge. The outer margin is a thickened bundle of fibrils running an undulating course along the entire length of the crista. The crista is elastic and when detached from degenerated organisms assumes a rather regularly wound spiral, consisting of longitudinal bundles of fibrils (Figs. 36 to 38). A fragment of two or three waves may be encountered in a preparation containing many degenerated organisms (Fig. 39). The composition of the crista can best be studied in degenerated remains of the organism. During the life of Cristispira it is stretched or relaxed according to the contraction or extension of the body. The elasticity of the crista appears to furnish the organism with a propelling and rotating power upon its extension after being drawn tightly to the body by some contractile apparatus (myoneme) present somewhere within the cell body. The crista serves as a rudder and propeller for the swimming organism. It is interesting to compare here the elastic and regularly waved flagella of certain bacteria and spirochetes; it is possible that the crista of Cristispira is a highly modified form of flagella. The nature of the substance which stains dark blue with Giemsa's stain is not known, but it does not give a chromatin reaction. By Heidenhain's iron-hematoxylin method it takes a dark grayish tint, similar to the cell wall or crista, which are also dark gray. This substance was regarded by Gross and Zuelzer as volutin, which is of nutritive origin. It is probable that there are also embedded within it minute chromidial elements. Multiplication is by transverse fission. Cristispira balbianii is parasitic and does not survive more than a few days in ordinary sea water emulsion, even at its optimum temperature. In its natural habitat, or the crystalline style, it is usually pure, but is sometimes found in association with a tiny spiral organism (Spirillum ostreae). The cristispiras in the styles seem to diminish rapidly when oysters are collected from their beds and transferred elsewhere; oysters kept in tanks or cars for several days do not contain the cristispiras, and in opened oysters the styles disappear promptly at room temperature. All efforts to cultivate this organism have failed.

Predicate calculus for an architecture of multiple neural networks

NASA Astrophysics Data System (ADS)

Consoli, Robert H.

1990-08-01

Future projects with neural networks will require multiple individual network components. Current efforts along these lines are ad hoc. This paper relates the neural network to a classical device and derives a multi-part architecture from that model. Further it provides a Predicate Calculus variant for describing the location and nature of the trainings and suggests Resolution Refutation as a method for determining the performance of the system as well as the location of needed trainings for specific proofs. 2. THE NEURAL NETWORK AND A CLASSICAL DEVICE Recently investigators have been making reports about architectures of multiple neural networksL234. These efforts are appearing at an early stage in neural network investigations they are characterized by architectures suggested directly by the problem space. Touretzky and Hinton suggest an architecture for processing logical statements1 the design of this architecture arises from the syntax of a restricted class of logical expressions and exhibits syntactic limitations. In similar fashion a multiple neural netword arises out of a control problem2 from the sequence learning problem3 and from the domain of machine learning. 4 But a general theory of multiple neural devices is missing. More general attempts to relate single or multiple neural networks to classical computing devices are not common although an attempt is made to relate single neural devices to a Turing machines and Sun et a!. develop a multiple neural architecture that performs pattern classification.

Fiber optic crossbar switch for automatically patching optical signals

NASA Technical Reports Server (NTRS)

Bell, C. H. (Inventor)

1983-01-01

A system for automatically optically switching fiber optic data signals between a plurality of input optical fibers and selective ones of a plurality of output fibers is described. The system includes optical detectors which are connected to each of the input fibers for converting the optic data signals appearing at the respective input fibers to an RF signal. A plurality of RF to optical signal converters are arranged in rows and columns. The output of each of the optical detectors are each applied to a respective row of optical signal converted for being converters back to an optical signal when the particular optical signal converter is selectively activated by a dc voltage.

Fully Printed Memristors from Cu-SiO2 Core-Shell Nanowire Composites

NASA Astrophysics Data System (ADS)

Catenacci, Matthew J.; Flowers, Patrick F.; Cao, Changyong; Andrews, Joseph B.; Franklin, Aaron D.; Wiley, Benjamin J.

2017-07-01

This article describes a fully printed memory in which a composite of Cu-SiO2 nanowires dispersed in ethylcellulose acts as a resistive switch between printed Cu and Au electrodes. A 16-cell crossbar array of these memristors was printed with an aerosol jet. The memristors exhibited moderate operating voltages (˜3 V), no degradation over 104 switching cycles, write speeds of 3 μs, and extrapolated retention times of 10 years. The low operating voltage enabled the programming of a fully printed 4-bit memristor array with an Arduino. The excellent performance of these fully printed memristors could help enable the creation of fully printed RFID tags and sensors with integrated data storage.

Results of an investigation of the 0.003-scale space shuttle external tank MSFC model 460 in the NASA/MSFC 14 x 14 inch Trisonic Wind Tunnel to determine static pressure distributions during reentry (TA2F), volume 3

NASA Technical Reports Server (NTRS)

Ramsey, P. E.; Winkler, G. W.

1975-01-01

Static pressure distributions for the external tank (ET) at reentry conditions are presented. Basic configuration of the model was the MCR 0200 ET modified to include a rectangular crossbar at the aft ET/orbiter attach point. Mach numbers were 1.96, 3.48, and 4.96. Reynolds number per foot at these Mach numbers were 6.95 million, 6.42 million, and 4.95 million, respectively. Angle of attack range was -8 to 100 degrees and roll angle was 0 to 315 degrees.

Nano-cone resistive memory for ultralow power operation.

PubMed

Kim, Sungjun; Jung, Sunghun; Kim, Min-Hwi; Kim, Tae-Hyeon; Bang, Suhyun; Cho, Seongjae; Park, Byung-Gook

2017-03-24

SiN x -based nano-structure resistive memory is fabricated by fully silicon CMOS compatible process integration including particularly designed anisotropic etching for the construction of a nano-cone silicon bottom electrode (BE). Bipolar resistive switching characteristics have significantly reduced switching current and voltage and are demonstrated in a nano-cone BE structure, as compared with those in a flat BE one. We have verified by systematic device simulations that the main cause of reduction in the performance parameters is the high electric field being more effectively concentrated at the tip of the cone-shaped BE. The greatly improved nonlinearity of the nano-cone resistive memory cell will be beneficial in the ultra-high-density crossbar array.

Transient dynamics of NbOx threshold switches explained by Poole-Frenkel based thermal feedback mechanism

NASA Astrophysics Data System (ADS)

Wang, Ziwen; Kumar, Suhas; Nishi, Yoshio; Wong, H.-S. Philip

2018-05-01

Niobium oxide (NbOx) two-terminal threshold switches are potential candidates as selector devices in crossbar memory arrays and as building blocks for neuromorphic systems. However, the physical mechanism of NbOx threshold switches is still under debate. In this paper, we show that a thermal feedback mechanism based on Poole-Frenkel conduction can explain both the quasi-static and the transient electrical characteristics that are experimentally observed for NbOx threshold switches, providing strong support for the validity of this mechanism. Furthermore, a clear picture of the transient dynamics during the thermal-feedback-induced threshold switching is presented, providing useful insights required to model nonlinear devices where thermal feedback is important.

CrossSim

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

Plimpton, Steven J.; Agarwal, Sapan; Schiek, Richard

2016-09-02

CrossSim is a simulator for modeling neural-inspired machine learning algorithms on analog hardware, such as resistive memory crossbars. It includes noise models for reading and updating the resistances, which can be based on idealized equations or experimental data. It can also introduce noise and finite precision effects when converting values from digital to analog and vice versa. All of these effects can be turned on or off as an algorithm processes a data set and attempts to learn its salient attributes so that it can be categorized in the machine learning training/classification context. CrossSim thus allows the robustness, accuracy, andmore » energy usage of a machine learning algorithm to be tested on simulated hardware.« less

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

PubMed

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

2015-10-01

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

Multi-scale modularity and motif distributional effect in metabolic networks.

PubMed

Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

2016-01-01

Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

Anti-synchronization control of BAM memristive neural networks with multiple proportional delays and stochastic perturbations

NASA Astrophysics Data System (ADS)

Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao

2018-01-01

Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.

Advanced wireless mobile collaborative sensing network for tactical and strategic missions

NASA Astrophysics Data System (ADS)

Xu, Hao

2017-05-01

In this paper, an advanced wireless mobile collaborative sensing network will be developed. Through properly combining wireless sensor network, emerging mobile robots and multi-antenna sensing/communication techniques, we could demonstrate superiority of developed sensing network. To be concrete, heterogeneous mobile robots including unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) are equipped with multi-model sensors and wireless transceiver antennas. Through real-time collaborative formation control, multiple mobile robots can team the best formation that can provide most accurate sensing results. Also, formatting multiple mobile robots can also construct a multiple-input multiple-output (MIMO) communication system that can provide a reliable and high performance communication network.

Enhanced disease characterization through multi network functional normalization in fMRI.

PubMed

Çetin, Mustafa S; Khullar, Siddharth; Damaraju, Eswar; Michael, Andrew M; Baum, Stefi A; Calhoun, Vince D

2015-01-01

Conventionally, structural topology is used for spatial normalization during the pre-processing of fMRI. The co-existence of multiple intrinsic networks which can be detected in the resting brain are well-studied. Also, these networks exhibit temporal and spatial modulation during cognitive task vs. rest which shows the existence of common spatial excitation patterns between these identified networks. Previous work (Khullar et al., 2011) has shown that structural and functional data may not have direct one-to-one correspondence and functional activation patterns in a well-defined structural region can vary across subjects even for a well-defined functional task. The results of this study and the existence of the neural activity patterns in multiple networks motivates us to investigate multiple resting-state networks as a single fusion template for functional normalization for multi groups of subjects. We extend the previous approach (Khullar et al., 2011) by co-registering multi group of subjects (healthy control and schizophrenia patients) and by utilizing multiple resting-state networks (instead of just one) as a single fusion template for functional normalization. In this paper we describe the initial steps toward using multiple resting-state networks as a single fusion template for functional normalization. A simple wavelet-based image fusion approach is presented in order to evaluate the feasibility of combining multiple functional networks. Our results showed improvements in both the significance of group statistics (healthy control and schizophrenia patients) and the spatial extent of activation when a multiple resting-state network applied as a single fusion template for functional normalization after the conventional structural normalization. Also, our results provided evidence that the improvement in significance of group statistics lead to better accuracy results for classification of healthy controls and schizophrenia patients.

Hubless satellite communications networks

NASA Technical Reports Server (NTRS)

Robinson, Peter Alan

1994-01-01

Frequency Comb Multiple Access (FCMA) is a new combined modulation and multiple access method which will allow cheap hubless Very Small Aperture Terminal (VSAT) networks to be constructed. Theoretical results show bandwidth efficiency and power efficiency improvements over other modulation and multiple access methods. Costs of the VSAT network are reduced dramatically since a hub station is not required.

Multiple Factors-Aware Diffusion in Social Networks

DTIC Science & Technology

2015-05-22

Multiple Factors-Aware Diffusion in Social Networks Chung-Kuang Chou(B) and Ming-Syan Chen Department of Electrical Engineering, National Taiwan...propagates from nodes to nodes over a social network . The behavior that a node adopts an information piece in a social network can be affected by...Twitter dataset. Keywords: Social networks · Diffusion models 1 Introduction Information diffusion in social networks has been an active research field

Qualitative analysis of Cohen-Grossberg neural networks with multiple delays

NASA Astrophysics Data System (ADS)

Ye, Hui; Michel, Anthony N.; Wang, Kaining

1995-03-01

It is well known that a class of artificial neural networks with symmetric interconnections and without transmission delays, known as Cohen-Grossberg neural networks, possesses global stability (i.e., all trajectories tend to some equilibrium). We demonstrate in the present paper that many of the qualitative properties of Cohen-Grossberg networks will not be affected by the introduction of sufficiently small delays. Specifically, we establish some bound conditions for the time delays under which a given Cohen-Grossberg network with multiple delays is globally stable and possesses the same asymptotically stable equilibria as the corresponding network without delays. An effective method of determining the asymptotic stability of an equilibrium of a Cohen-Grossberg network with multiple delays is also presented. The present results are motivated by some of the authors earlier work [Phys. Rev. E 50, 4206 (1994)] and by some of the work of Marcus and Westervelt [Phys. Rev. A 39, 347 (1989)]. These works address qualitative analyses of Hopfield neural networks with one time delay. The present work generalizes these results to Cohen-Grossberg neural networks with multiple time delays. Hopfield neural networks constitute special cases of Cohen-Grossberg neural networks.

Structural disconnection is responsible for increased functional connectivity in multiple sclerosis.

PubMed

Patel, Kevin R; Tobyne, Sean; Porter, Daria; Bireley, John Daniel; Smith, Victoria; Klawiter, Eric

2018-06-01

Increased synchrony within neuroanatomical networks is often observed in neurophysiologic studies of human brain disease. Most often, this phenomenon is ascribed to a compensatory process in the face of injury, though evidence supporting such accounts is limited. Given the known dependence of resting-state functional connectivity (rsFC) on underlying structural connectivity (SC), we examine an alternative hypothesis: that topographical changes in SC, specifically particular patterns of disconnection, contribute to increased network rsFC. We obtain measures of rsFC using fMRI and SC using probabilistic tractography in 50 healthy and 28 multiple sclerosis subjects. Using a computational model of neuronal dynamics, we simulate BOLD using healthy subject SC to couple regions. We find that altering the model by introducing structural disconnection patterns observed in those multiple sclerosis subjects with high network rsFC generates simulations with high rsFC as well, suggesting that disconnection itself plays a role in producing high network functional connectivity. We then examine SC data in individuals. In multiple sclerosis subjects with high network rsFC, we find a preferential disconnection between the relevant network and wider system. We examine the significance of such network isolation by introducing random disconnection into the model. As observed empirically, simulated network rsFC increases with removal of connections bridging a community with the remainder of the brain. We thus show that structural disconnection known to occur in multiple sclerosis contributes to network rsFC changes in multiple sclerosis and further that community isolation is responsible for elevated network functional connectivity.

Design of a MIMD neural network processor

NASA Astrophysics Data System (ADS)

Saeks, Richard E.; Priddy, Kevin L.; Pap, Robert M.; Stowell, S.

1994-03-01

The Accurate Automation Corporation (AAC) neural network processor (NNP) module is a fully programmable multiple instruction multiple data (MIMD) parallel processor optimized for the implementation of neural networks. The AAC NNP design fully exploits the intrinsic sparseness of neural network topologies. Moreover, by using a MIMD parallel processing architecture one can update multiple neurons in parallel with efficiency approaching 100 percent as the size of the network increases. Each AAC NNP module has 8 K neurons and 32 K interconnections and is capable of 140,000,000 connections per second with an eight processor array capable of over one billion connections per second.

Hyperswitch Communication Network Computer

NASA Technical Reports Server (NTRS)

Peterson, John C.; Chow, Edward T.; Priel, Moshe; Upchurch, Edwin T.

1993-01-01

Hyperswitch Communications Network (HCN) computer is prototype multiple-processor computer being developed. Incorporates improved version of hyperswitch communication network described in "Hyperswitch Network For Hypercube Computer" (NPO-16905). Designed to support high-level software and expansion of itself. HCN computer is message-passing, multiple-instruction/multiple-data computer offering significant advantages over older single-processor and bus-based multiple-processor computers, with respect to price/performance ratio, reliability, availability, and manufacturing. Design of HCN operating-system software provides flexible computing environment accommodating both parallel and distributed processing. Also achieves balance among following competing factors; performance in processing and communications, ease of use, and tolerance of (and recovery from) faults.

An Energy Efficient Cooperative Hierarchical MIMO Clustering Scheme for Wireless Sensor Networks

PubMed Central

Nasim, Mehwish; Qaisar, Saad; Lee, Sungyoung

2012-01-01

In this work, we present an energy efficient hierarchical cooperative clustering scheme for wireless sensor networks. Communication cost is a crucial factor in depleting the energy of sensor nodes. In the proposed scheme, nodes cooperate to form clusters at each level of network hierarchy ensuring maximal coverage and minimal energy expenditure with relatively uniform distribution of load within the network. Performance is enhanced by cooperative multiple-input multiple-output (MIMO) communication ensuring energy efficiency for WSN deployments over large geographical areas. We test our scheme using TOSSIM and compare the proposed scheme with cooperative multiple-input multiple-output (CMIMO) clustering scheme and traditional multihop Single-Input-Single-Output (SISO) routing approach. Performance is evaluated on the basis of number of clusters, number of hops, energy consumption and network lifetime. Experimental results show significant energy conservation and increase in network lifetime as compared to existing schemes. PMID:22368459

Unsupervised learning of contextual constraints in neural networks for simultaneous visual processing of multiple objects

NASA Astrophysics Data System (ADS)

Marshall, Jonathan A.

1992-12-01

A simple self-organizing neural network model, called an EXIN network, that learns to process sensory information in a context-sensitive manner, is described. EXIN networks develop efficient representation structures for higher-level visual tasks such as segmentation, grouping, transparency, depth perception, and size perception. Exposure to a perceptual environment during a developmental period serves to configure the network to perform appropriate organization of sensory data. A new anti-Hebbian inhibitory learning rule permits superposition of multiple simultaneous neural activations (multiple winners), while maintaining contextual consistency constraints, instead of forcing winner-take-all pattern classifications. The activations can represent multiple patterns simultaneously and can represent uncertainty. The network performs parallel parsing, credit attribution, and simultaneous constraint satisfaction. EXIN networks can learn to represent multiple oriented edges even where they intersect and can learn to represent multiple transparently overlaid surfaces defined by stereo or motion cues. In the case of stereo transparency, the inhibitory learning implements both a uniqueness constraint and permits coactivation of cells representing multiple disparities at the same image location. Thus two or more disparities can be active simultaneously without interference. This behavior is analogous to that of Prazdny's stereo vision algorithm, with the bonus that each binocular point is assigned a unique disparity. In a large implementation, such a NN would also be able to represent effectively the disparities of a cloud of points at random depths, like human observers, and unlike Prazdny's method

Diversity Performance Analysis on Multiple HAP Networks.

PubMed

Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

2015-06-30

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

Wireless Computing Architecture III

DTIC Science & Technology

2013-09-01

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

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

Liu, Yizhou, E-mail: yliu062@ucr.edu; Yin, Gen; Lake, Roger K., E-mail: rlake@ece.ucr.edu

Single skyrmion creation and annihilation by spin waves in a crossbar geometry are theoretically analyzed. A critical spin-wave frequency is required both for the creation and the annihilation of a skyrmion. The minimum frequencies for creation and annihilation are similar, but the optimum frequency for creation is below the critical frequency for skyrmion annihilation. If a skyrmion already exists in the cross bar region, a spin wave below the critical frequency causes the skyrmion to circulate within the central region. A heat assisted creation process reduces the spin-wave frequency and amplitude required for creating a skyrmion. The effective field resultingmore » from the Dzyaloshinskii-Moriya interaction and the emergent field of the skyrmion acting on the spin wave drive the creation and annihilation processes.« less

High-Speed Optical Wide-Area Data-Communication Network

NASA Technical Reports Server (NTRS)

Monacos, Steve P.

1994-01-01

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

NASA Tech Briefs, November 2003

NASA Technical Reports Server (NTRS)

2003-01-01

Topics covered include: Computer Program Recognizes Patterns in Time-Series Data; Program for User-Friendly Management of Input and Output Data Sets; Noncoherent Tracking of a Source of a Data-Modulated Signal; Software for Acquiring Image Data for PIV; Detecting Edges in Images by Use of Fuzzy Reasoning; A Timer for Synchronous Digital Systems; Prototype Parts of a Digital Beam-Forming Wide-Band Receiver; High-Voltage Droplet Dispenser; Network Extender for MIL-STD-1553 Bus; MMIC HEMT Power Amplifier for 140 to 170 GHz; Piezoelectric Diffraction-Based Optical Switches; Numerical Modeling of Nanoelectronic Devices; Organizing Diverse, Distributed Project Information; Eigensolver for a Sparse, Large Hermitian Matrix; Modified Polar-Format Software for Processing SAR Data; e-Stars Template Builder; Software for Acoustic Rendering; Functionally Graded Nanophase Beryllium/Carbon Composites; Thin Thermal-Insulation Blankets for Very High Temperatures; Prolonging Microgravity on Parabolic Airplane Flights; Device for Locking a Control Knob; Cable-Dispensing Cart; Foam Sensor Structures Would be Self-Deployable and Survive Hard Landings; Real-Gas Effects on Binary Mixing Layers; Earth-Space Link Attenuation Estimation via Ground Radar Kdp; Wedge Heat-Flux Indicators for Flash Thermography; Measuring Diffusion of Liquids by Common-Path Interferometry; Zero-Shear, Low-Disturbance Optical Delay Line; Whispering-Gallery Mode-Locked Lasers; Spatial Light Modulators as Optical Crossbar Switches; Update on EMD and Hilbert-Spectra Analysis of Time Series; Quad-Tree Visual-Calculus Analysis of Satellite Coverage; Dyakonov-Perel Effect on Spin Dephasing in n-Type GaAs; Update on Area Production in Mixing of Supercritical Fluids; and Quasi-Sun-Pointing of Spacecraft Using Radiation Pressure.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations

PubMed Central

2012-01-01

Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html. PMID:22531049

Real-Time Data Filtering and Compression in Wide Area Simulation Networks

DTIC Science & Technology

1992-10-02

Area Simulation Networks Achieving the real-time linkage among multiple , geographically-distant, local area networks that support distributed...November 1989, pp. 52-61. [IEEE85] IEEE/ANSI Standard 8802/3 "Carrier sense multiple access with collision detection (CSMA/CD) access method and...decoding/encoding of multiple bits. The hardware is programmable, easily adaptable and yields a high compression rate. A prototype 2-micron VLSI chip

Distributed multiple path routing in complex networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Wang, San-Xiu; Wu, Ling-Wei; Mei, Pan; Yang, Xu-Hua; Wen, Guang-Hui

2016-12-01

Routing in complex transmission networks is an important problem that has garnered extensive research interest in the recent years. In this paper, we propose a novel routing strategy called the distributed multiple path (DMP) routing strategy. For each of the O-D node pairs in a given network, the DMP routing strategy computes and stores multiple short-length paths that overlap less with each other in advance. And during the transmission stage, it rapidly selects an actual routing path which provides low transmission cost from the pre-computed paths for each transmission task, according to the real-time network transmission status information. Computer simulation results obtained for the lattice, ER random, and scale-free networks indicate that the strategy can significantly improve the anti-congestion ability of transmission networks, as well as provide favorable routing robustness against partial network failures.

Diversity Performance Analysis on Multiple HAP Networks

PubMed Central

Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

2015-01-01

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

Prediction of β-turns in proteins from multiple alignment using neural network

PubMed Central

Kaur, Harpreet; Raghava, Gajendra Pal Singh

2003-01-01

A neural network-based method has been developed for the prediction of β-turns in proteins by using multiple sequence alignment. Two feed-forward back-propagation networks with a single hidden layer are used where the first-sequence structure network is trained with the multiple sequence alignment in the form of PSI-BLAST–generated position-specific scoring matrices. The initial predictions from the first network and PSIPRED-predicted secondary structure are used as input to the second structure-structure network to refine the predictions obtained from the first net. A significant improvement in prediction accuracy has been achieved by using evolutionary information contained in the multiple sequence alignment. The final network yields an overall prediction accuracy of 75.5% when tested by sevenfold cross-validation on a set of 426 nonhomologous protein chains. The corresponding Qpred, Qobs, and Matthews correlation coefficient values are 49.8%, 72.3%, and 0.43, respectively, and are the best among all the previously published β-turn prediction methods. The Web server BetaTPred2 (http://www.imtech.res.in/raghava/betatpred2/) has been developed based on this approach. PMID:12592033

Dynamic Network Selection for Multicast Services in Wireless Cooperative Networks

NASA Astrophysics Data System (ADS)

Chen, Liang; Jin, Le; He, Feng; Cheng, Hanwen; Wu, Lenan

In next generation mobile multimedia communications, different wireless access networks are expected to cooperate. However, it is a challenging task to choose an optimal transmission path in this scenario. This paper focuses on the problem of selecting the optimal access network for multicast services in the cooperative mobile and broadcasting networks. An algorithm is proposed, which considers multiple decision factors and multiple optimization objectives. An analytic hierarchy process (AHP) method is applied to schedule the service queue and an artificial neural network (ANN) is used to improve the flexibility of the algorithm. Simulation results show that by applying the AHP method, a group of weight ratios can be obtained to improve the performance of multiple objectives. And ANN method is effective to adaptively adjust weight ratios when users' new waiting threshold is generated.

Ultrascalable petaflop parallel supercomputer

DOEpatents

Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Chiu, George [Cross River, NY; Cipolla, Thomas M [Katonah, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Hall, Shawn [Pleasantville, NY; Haring, Rudolf A [Cortlandt Manor, NY; Heidelberger, Philip [Cortlandt Manor, NY; Kopcsay, Gerard V [Yorktown Heights, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Takken, Todd [Brewster, NY

2010-07-20

A massively parallel supercomputer of petaOPS-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC) having up to four processing elements. The ASIC nodes are interconnected by multiple independent networks that optimally maximize the throughput of packet communications between nodes with minimal latency. The multiple networks may include three high-speed networks for parallel algorithm message passing including a Torus, collective network, and a Global Asynchronous network that provides global barrier and notification functions. These multiple independent networks may be collaboratively or independently utilized according to the needs or phases of an algorithm for optimizing algorithm processing performance. The use of a DMA engine is provided to facilitate message passing among the nodes without the expenditure of processing resources at the node.

Distributed parallel messaging for multiprocessor systems

DOEpatents

Chen, Dong; Heidelberger, Philip; Salapura, Valentina; Senger, Robert M; Steinmacher-Burrow, Burhard; Sugawara, Yutaka

2013-06-04

A method and apparatus for distributed parallel messaging in a parallel computing system. The apparatus includes, at each node of a multiprocessor network, multiple injection messaging engine units and reception messaging engine units, each implementing a DMA engine and each supporting both multiple packet injection into and multiple reception from a network, in parallel. The reception side of the messaging unit (MU) includes a switch interface enabling writing of data of a packet received from the network to the memory system. The transmission side of the messaging unit, includes switch interface for reading from the memory system when injecting packets into the network.

Weighted Scaling in Non-growth Random Networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li

2012-09-01

We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in non-growth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its total number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scale-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

SOUND SURVEY DESIGNS CAN FACILITATE INTEGRATING STREAM MONITORING DATA ACROSS MULTIPLE PROGRAMS

EPA Science Inventory

Multiple agencies in the Pacific Northwest monitor the condition of stream networks or their watersheds. Some agencies use a stream "network" perspective to report on the fraction or length of the network that either meets or violates particular criteria. Other agencies use a "wa...

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.

Intrinsic brain connectivity in fibromyalgia is associated with chronic pain intensity.

PubMed

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Sawsan; Clauw, Daniel J; Harris, Richard E

2010-08-01

Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. The objective of this study was to investigate the degree of connectivity between multiple brain networks in patients with FM, as well as how activity in these networks correlates with the level of spontaneous pain. Resting-state functional magnetic resonance imaging (FMRI) data from 18 patients with FM and 18 age-matched healthy control subjects were analyzed using dual-regression independent components analysis, which is a data-driven approach for the identification of independent brain networks. Intrinsic, or resting-state, connectivity was evaluated in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also analyzed for covariance with intrinsic connectivity. Patients with FM had greater connectivity within the DMN and right EAN (corrected P [P(corr)] < 0.05 versus controls), and greater connectivity between the DMN and the insular cortex, which is a brain region known to process evoked pain. Furthermore, greater intensity of spontaneous pain at the time of the FMRI scan correlated with greater intrinsic connectivity between the insula and both the DMN and right EAN (P(corr) < 0.05). These findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in patients with FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay among multiple brain networks.

Intrinsic Brain Connectivity in Fibromyalgia is Associated with Chronic Pain Intensity

PubMed Central

Napadow, Vitaly; LaCount, Lauren; Park, Kyungmo; As-Sanie, Suzie; Clauw, Daniel J; Harris, Richard E

2010-01-01

OBJECTIVE Fibromyalgia (FM) is considered to be the prototypical central chronic pain syndrome and is associated with widespread pain that fluctuates spontaneously. Multiple studies have demonstrated altered brain activity in these patients. Our objective was to investigate the degree of connectivity between multiple brain networks in FM, as well as how activity in these networks correlates with spontaneous pain. METHODS Resting functional magnetic resonance imaging (fMRI) data in FM patients (n=18) and age-matched healthy controls (HC, n=18) were analyzed using dual regression independent component analysis (ICA) - a data driven approach used to identify independent brain networks. We evaluated intrinsic, or resting, connectivity in multiple brain networks: the default mode network (DMN), the executive attention network (EAN), and the medial visual network (MVN), with the MVN serving as a negative control. Spontaneous pain levels were also covaried with intrinsic connectivity. RESULTS We found that FM patients had greater connectivity within the DMN and right EAN (rEAN; p<0.05, corrected), and greater connectivity between the DMN and the insular cortex – a brain region known to process evoked pain. Furthermore, greater spontaneous pain at the time of the scan correlated with greater intrinsic connectivity between the insula and both the DMN and rEAN (p<0.05, corrected). CONCLUSION Our findings indicate that resting brain activity within multiple networks is associated with spontaneous clinical pain in FM. These findings may also have broader implications for how subjective experiences such as pain arise from a complex interplay amongst multiple brain networks. PMID:20506181

Ionically Cross-Linked Polymer Networks for the Multiple-Month Release of Small Molecules

PubMed Central

2016-01-01

Long-term (multiple-week or -month) release of small, water-soluble molecules from hydrogels remains a significant pharmaceutical challenge, which is typically overcome at the expense of more-complicated drug carrier designs. Such approaches are payload-specific and include covalent conjugation of drugs to base materials or incorporation of micro- and nanoparticles. As a simpler alternative, here we report a mild and simple method for achieving multiple-month release of small molecules from gel-like polymer networks. Densely cross-linked matrices were prepared through ionotropic gelation of poly(allylamine hydrochloride) (PAH) with either pyrophosphate (PPi) or tripolyphosphate (TPP), all of which are commonly available commercial molecules. The loading of model small molecules (Fast Green FCF and Rhodamine B dyes) within these polymer networks increases with the payload/network binding strength and with the PAH and payload concentrations used during encapsulation. Once loaded into the PAH/PPi and PAH/TPP ionic networks, only a few percent of the payload is released over multiple months. This extended release is achieved regardless of the payload/network binding strength and likely reflects the small hydrodynamic mesh size within the gel-like matrices. Furthermore, the PAH/TPP networks show promising in vitro cytocompatibility with model cells (human dermal fibroblasts), though slight cytotoxic effects were exhibited by the PAH/PPi networks. Taken together, the above findings suggest that PAH/PPi and (especially) PAH/TPP networks might be attractive materials for the multiple-month delivery of drugs and other active molecules (e.g., fragrances or disinfectants). PMID:26811936

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.

Enhanced wall-plug efficiency in AlGaN-based deep-ultraviolet light-emitting diodes with uniform current spreading p-electrode structures

NASA Astrophysics Data System (ADS)

Hao, Guo-Dong; Taniguchi, Manabu; Tamari, Naoki; Inoue, Shin-ichiro

2016-06-01

The current crowding is an especially severe issue in AlGaN-based deep-ultraviolet (DUV) light-emitting diodes (LEDs) because of the low conductivity of the n-AlGaN cladding layer that has a high Al fraction. We theoretically investigated the improvement in internal quantum efficiency and total resistances in DUV-LEDs with an emission wavelength of 265 nm by a well-designed p-electrode geometry to produce uniform current spreading. As a result, the wall-plug efficiency was enhanced by a factor of 60% at an injection current of 350 mA in the designed uniform-current-spreading p-electrode LED when compared with an LED with a conventional cross-bar p-electrode pattern.

Improvement of SET variability in TaO x based resistive RAM devices

NASA Astrophysics Data System (ADS)

Schönhals, Alexander; Waser, Rainer; Wouters, Dirk J.

2017-11-01

Improvement or at least control of variability is one of the key challenges for Redox based resistive switching memory technology. In this paper, we investigate the impact of a serial resistor as a voltage divider on the SET variability in Pt/Ta2O5/Ta/Pt nano crossbar devices. A partial RESET in a competing complementary switching (CS) mode is identified as a possible failure mechanism of bipolar switching SET in our devices. Due to a voltage divider effect, serial resistance value shows unequal impact on switching voltages of both modes which allows for a selective suppression of the CS mode. The impact of voltage divider on SET variability is demonstrated. A combination of appropriate write voltage and serial resistance allows for a significant improvement of the SET variability.

Patterning and templating for nanoelectronics.

PubMed

Galatsis, Kosmas; Wang, Kang L; Ozkan, Mihri; Ozkan, Cengiz S; Huang, Yu; Chang, Jane P; Monbouquette, Harold G; Chen, Yong; Nealey, Paul; Botros, Youssry

2010-02-09

The semiconductor industry will soon be launching 32 nm complementary metal oxide semiconductor (CMOS) technology node using 193 nm lithography patterning technology to fabricate microprocessors with more than 2 billion transistors. To ensure the survival of Moore's law, alternative patterning techniques that offer advantages beyond conventional top-down patterning are aggressively being explored. It is evident that most alternative patterning techniques may not offer compelling advantages to succeed conventional top-down lithography for silicon integrated circuits, but alternative approaches may well indeed offer functional advantages in realising next-generation information processing nanoarchitectures such as those based on cellular, bioinsipired, magnetic dot logic, and crossbar schemes. This paper highlights and evaluates some patterning methods from the Center on Functional Engineered Nano Architectonics in Los Angeles and discusses key benchmarking criteria with respect to CMOS scaling.

Multiple-predators-based capture process on complex networks

NASA Astrophysics Data System (ADS)

Ramiz Sharafat, Rajput; Pu, Cunlai; Li, Jie; Chen, Rongbin; Xu, Zhongqi

2017-03-01

The predator/prey (capture) problem is a prototype of many network-related applications. We study the capture process on complex networks by considering multiple predators from multiple sources. In our model, some lions start from multiple sources simultaneously to capture the lamb by biased random walks, which are controlled with a free parameter $\\alpha$. We derive the distribution of the lamb's lifetime and the expected lifetime $\\left\\langle T\\right\\rangle $. Through simulation, we find that the expected lifetime drops substantially with the increasing number of lions. We also study how the underlying topological structure affects the capture process, and obtain that locating on small-degree nodes is better than large-degree nodes to prolong the lifetime of the lamb. Moreover, dense or homogeneous network structures are against the survival of the lamb.

Evolutionary Scheduler for the Deep Space Network

NASA Technical Reports Server (NTRS)

Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert

2010-01-01

A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

Presurgical localization and spatial shift of resting state networks in patients with brain metastases.

PubMed

Ding, Ju-Rong; Zhu, Fangmei; Hua, Bo; Xiong, Xingzhong; Wen, Yuqiao; Ding, Zhongxiang; Thompson, Paul M

2018-04-02

Brain metastases are the most prevalent cerebral tumors. Resting state networks (RSNs) are involved in multiple perceptual and cognitive functions. Therefore, precisely localizing multiple RSNs may be extremely valuable before surgical resection of metastases, to minimize neurocognitive impairments. Here we aimed to investigate the reliability of independent component analysis (ICA) for localizing multiple RSNs from resting-state functional MRI (rs-fMRI) data in individual patients, and further evaluate lesion-related spatial shifts of the RSNs. Twelve patients with brain metastases and 14 healthy controls were recruited. Using an improved automatic component identification method, we successfully identified seven common RSNs, including: the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN), language network (LN), sensorimotor network (SMN), auditory network (AN) and visual network (VN), in both individual patients and controls. Moreover, the RSNs in the patients showed a visible spatial shift compared to those in the controls, and the spatial shift of some regions was related to the tumor location, which may reflect a complicated functional mechanism - functional disruptions and reorganizations - caused by metastases. Besides, higher cognitive networks (DMN, ECN, DAN and LN) showed significantly larger spatial shifts than perceptual networks (SMN, AN and VN), supporting a functional dichotomy between the two network groups even in pathologic alterations associated with metastases. Overall, our findings provide evidence that ICA is a promising approach for presurgical localization of multiple RSNs from rs-fMRI data in individual patients. More attention should be paid to the spatial shifts of the RSNs before surgical resection.

Path scheduling for multiple mobile actors in wireless sensor network

NASA Astrophysics Data System (ADS)

Trapasiya, Samir D.; Soni, Himanshu B.

2017-05-01

In wireless sensor network (WSN), energy is the main constraint. In this work we have addressed this issue for single as well as multiple mobile sensor actor network. In this work, we have proposed Rendezvous Point Selection Scheme (RPSS) in which Rendezvous Nodes are selected by set covering problem approach and from that, Rendezvous Points are selected in a way to reduce the tour length. The mobile actors tour is scheduled to pass through those Rendezvous Points as per Travelling Salesman Problem (TSP). We have also proposed novel rendezvous node rotation scheme for fair utilisation of all the nodes. We have compared RPSS with Stationery Actor scheme as well as RD-VT, RD-VT-SMT and WRP-SMT for performance metrics like energy consumption, network lifetime, route length and found the better outcome in all the cases for single actor. We have also applied RPSS for multiple mobile actor case like Multi-Actor Single Depot (MASD) termination and Multi-Actor Multiple Depot (MAMD) termination and observed by extensive simulation that MAMD saves the network energy in optimised way and enhance network lifetime compared to all other schemes.

Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke

PubMed Central

Ramsey, Lenny E.; Metcalf, Nicholas V.; Chacko, Ravi V.; Weinberger, Kilian; Baldassarre, Antonello; Hacker, Carl D.; Shulman, Gordon L.; Corbetta, Maurizio

2016-01-01

Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain–behavior relationships in stroke. PMID:27402738

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

Robust Routing Protocol For Digital Messages

NASA Technical Reports Server (NTRS)

Marvit, Maclen

1994-01-01

Refinement of ditigal-message-routing protocol increases fault tolerance of polled networks. AbNET-3 is latest of generic AbNET protocols for transmission of messages among computing nodes. AbNET concept described in "Multiple-Ring Digital Communication Network" (NPO-18133). Specifically aimed at increasing fault tolerance of network in broadcast mode, in which one node broadcasts message to and receives responses from all other nodes. Communication in network of computers maintained even when links fail.

Network inference from multimodal data: A review of approaches from infectious disease transmission.

PubMed

Ray, Bisakha; Ghedin, Elodie; Chunara, Rumi

2016-12-01

Networks inference problems are commonly found in multiple biomedical subfields such as genomics, metagenomics, neuroscience, and epidemiology. Networks are useful for representing a wide range of complex interactions ranging from those between molecular biomarkers, neurons, and microbial communities, to those found in human or animal populations. Recent technological advances have resulted in an increasing amount of healthcare data in multiple modalities, increasing the preponderance of network inference problems. Multi-domain data can now be used to improve the robustness and reliability of recovered networks from unimodal data. For infectious diseases in particular, there is a body of knowledge that has been focused on combining multiple pieces of linked information. Combining or analyzing disparate modalities in concert has demonstrated greater insight into disease transmission than could be obtained from any single modality in isolation. This has been particularly helpful in understanding incidence and transmission at early stages of infections that have pandemic potential. Novel pieces of linked information in the form of spatial, temporal, and other covariates including high-throughput sequence data, clinical visits, social network information, pharmaceutical prescriptions, and clinical symptoms (reported as free-text data) also encourage further investigation of these methods. The purpose of this review is to provide an in-depth analysis of multimodal infectious disease transmission network inference methods with a specific focus on Bayesian inference. We focus on analytical Bayesian inference-based methods as this enables recovering multiple parameters simultaneously, for example, not just the disease transmission network, but also parameters of epidemic dynamics. Our review studies their assumptions, key inference parameters and limitations, and ultimately provides insights about improving future network inference methods in multiple applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Preferential attachment in multiple trade networks

NASA Astrophysics Data System (ADS)

Foschi, Rachele; Riccaboni, Massimo; Schiavo, Stefano

2014-08-01

In this paper we develop a model for the evolution of multiple networks which is able to replicate the concentrated and sparse nature of world trade data. Our model is an extension of the preferential attachment growth model to the case of multiple networks. Countries trade a variety of goods of different complexity. Every country progressively evolves from trading less sophisticated to high-tech goods. The probabilities of capturing more trade opportunities at a given level of complexity and of starting to trade more complex goods are both proportional to the number of existing trade links. We provide a set of theoretical predictions and simulative results. A calibration exercise shows that our model replicates the same concentration level of world trade as well as the sparsity pattern of the trade matrix. We also discuss a set of numerical solutions to deal with large multiple networks.

Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Using a two-phase evolutionary framework to select multiple network spreaders based on community structure

NASA Astrophysics Data System (ADS)

Fu, Yu-Hsiang; Huang, Chung-Yuan; Sun, Chuen-Tsai

2016-11-01

Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders.

IEEE 342 Node Low Voltage Networked Test System

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

Schneider, Kevin P.; Phanivong, Phillippe K.; Lacroix, Jean-Sebastian

The IEEE Distribution Test Feeders provide a benchmark for new algorithms to the distribution analyses community. The low voltage network test feeder represents a moderate size urban system that is unbalanced and highly networked. This is the first distribution test feeder developed by the IEEE that contains unbalanced networked components. The 342 node Low Voltage Networked Test System includes many elements that may be found in a networked system: multiple 13.2kV primary feeders, network protectors, a 120/208V grid network, and multiple 277/480V spot networks. This paper presents a brief review of the history of low voltage networks and how theymore » evolved into the modern systems. This paper will then present a description of the 342 Node IEEE Low Voltage Network Test System and power flow results.« less

Cooperative UAV-Based Communications Backbone for Sensor Networks

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

Roberts, R S

2001-10-07

The objective of this project is to investigate the use of unmanned air vehicles (UAVs) as mobile, adaptive communications backbones for ground-based sensor networks. In this type of network, the UAVs provide communication connectivity to sensors that cannot communicate with each other because of terrain, distance, or other geographical constraints. In these situations, UAVs provide a vertical communication path for the sensors, thereby mitigating geographic obstacles often imposed on networks. With the proper use of UAVs, connectivity to a widely disbursed sensor network in rugged terrain is readily achieved. Our investigation has focused on networks where multiple cooperating UAVs aremore » used to form a network backbone. The advantage of using multiple UAVs to form the network backbone is parallelization of sensor connectivity. Many widely spaced or isolated sensors can be connected to the network at once using this approach. In these networks, the UAVs logically partition the sensor network into sub-networks (subnets), with one UAV assigned per subnet. Partitioning the network into subnets allows the UAVs to service sensors in parallel thereby decreasing the sensor-to-network connectivity. A UAV services sensors in its subnet by flying a route (path) through the subnet, uplinking data collected by the sensors, and forwarding the data to a ground station. An additional advantage of using multiple UAVs in the network is that they provide redundancy in the communications backbone, so that the failure of a single UAV does not necessarily imply the loss of the network.« less

Network-based drug discovery by integrating systems biology and computational technologies

PubMed Central

Leung, Elaine L.; Cao, Zhi-Wei; Jiang, Zhi-Hong; Zhou, Hua

2013-01-01

Network-based intervention has been a trend of curing systemic diseases, but it relies on regimen optimization and valid multi-target actions of the drugs. The complex multi-component nature of medicinal herbs may serve as valuable resources for network-based multi-target drug discovery due to its potential treatment effects by synergy. Recently, robustness of multiple systems biology platforms shows powerful to uncover molecular mechanisms and connections between the drugs and their targeting dynamic network. However, optimization methods of drug combination are insufficient, owning to lacking of tighter integration across multiple ‘-omics’ databases. The newly developed algorithm- or network-based computational models can tightly integrate ‘-omics’ databases and optimize combinational regimens of drug development, which encourage using medicinal herbs to develop into new wave of network-based multi-target drugs. However, challenges on further integration across the databases of medicinal herbs with multiple system biology platforms for multi-target drug optimization remain to the uncertain reliability of individual data sets, width and depth and degree of standardization of herbal medicine. Standardization of the methodology and terminology of multiple system biology and herbal database would facilitate the integration. Enhance public accessible databases and the number of research using system biology platform on herbal medicine would be helpful. Further integration across various ‘-omics’ platforms and computational tools would accelerate development of network-based drug discovery and network medicine. PMID:22877768

The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. SIGNIFICANCE STATEMENT The thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions display network properties that are capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks. PMID:28450543

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.

Multiple network interface core apparatus and method

DOEpatents

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

Network-based Approaches in Pharmacology.

PubMed

Boezio, Baptiste; Audouze, Karine; Ducrot, Pierre; Taboureau, Olivier

2017-10-01

In drug discovery, network-based approaches are expected to spotlight our understanding of drug action across multiple layers of information. On one hand, network pharmacology considers the drug response in the context of a cellular or phenotypic network. On the other hand, a chemical-based network is a promising alternative for characterizing the chemical space. Both can provide complementary support for the development of rational drug design and better knowledge of the mechanisms underlying the multiple actions of drugs. Recent progress in both concepts is discussed here. In addition, a network-based approach using drug-target-therapy data is introduced as an example. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optical Multiple Access Network (OMAN) for advanced processing satellite applications

NASA Technical Reports Server (NTRS)

Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

1991-01-01

An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

Additional considerations are required when preparing a protocol for a systematic review with multiple interventions.

PubMed

Chaimani, Anna; Caldwell, Deborah M; Li, Tianjing; Higgins, Julian P T; Salanti, Georgia

2017-03-01

The number of systematic reviews that aim to compare multiple interventions using network meta-analysis is increasing. In this study, we highlight aspects of a standard systematic review protocol that may need modification when multiple interventions are to be compared. We take the protocol format suggested by Cochrane for a standard systematic review as our reference and compare the considerations for a pairwise review with those required for a valid comparison of multiple interventions. We suggest new sections for protocols of systematic reviews including network meta-analyses with a focus on how to evaluate their assumptions. We provide example text from published protocols to exemplify the considerations. Standard systematic review protocols for pairwise meta-analyses need extensions to accommodate the increased complexity of network meta-analysis. Our suggested modifications are widely applicable to both Cochrane and non-Cochrane systematic reviews involving network meta-analyses. Copyright © 2017 Elsevier Inc. All rights reserved.

Efficient quantum transmission in multiple-source networks.

PubMed

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

2014-04-02

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

Upscaling permeability for three-dimensional fractured porous rocks with the multiple boundary method

NASA Astrophysics Data System (ADS)

Chen, Tao; Clauser, Christoph; Marquart, Gabriele; Willbrand, Karen; Hiller, Thomas

2018-02-01

Upscaling permeability of grid blocks is crucial for groundwater models. A novel upscaling method for three-dimensional fractured porous rocks is presented. The objective of the study was to compare this method with the commonly used Oda upscaling method and the volume averaging method. First, the multiple boundary method and its computational framework were defined for three-dimensional stochastic fracture networks. Then, the different upscaling methods were compared for a set of rotated fractures, for tortuous fractures, and for two discrete fracture networks. The results computed by the multiple boundary method are comparable with those of the other two methods and fit best the analytical solution for a set of rotated fractures. The errors in flow rate of the equivalent fracture model decrease when using the multiple boundary method. Furthermore, the errors of the equivalent fracture models increase from well-connected fracture networks to poorly connected ones. Finally, the diagonal components of the equivalent permeability tensors tend to follow a normal or log-normal distribution for the well-connected fracture network model with infinite fracture size. By contrast, they exhibit a power-law distribution for the poorly connected fracture network with multiple scale fractures. The study demonstrates the accuracy and the flexibility of the multiple boundary upscaling concept. This makes it attractive for being incorporated into any existing flow-based upscaling procedures, which helps in reducing the uncertainty of groundwater models.

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

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

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

2010-06-15

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

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

76 FR 7213 - ACRAnet, Inc.; SettlementOne Credit Corporation, and Sackett National Holdings, Inc.; Fajilan and...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-09

... allege that hackers were able to exploit vulnerabilities in the computer networks of multiple end user clients, putting all consumer reports in those networks at risk. In multiple breaches, hackers accessed...

Analysis and Testing of Mobile Wireless Networks

NASA Technical Reports Server (NTRS)

Alena, Richard; Evenson, Darin; Rundquist, Victor; Clancy, Daniel (Technical Monitor)

2002-01-01

Wireless networks are being used to connect mobile computing elements in more applications as the technology matures. There are now many products (such as 802.11 and 802.11b) which ran in the ISM frequency band and comply with wireless network standards. They are being used increasingly to link mobile Intranet into Wired networks. Standard methods of analyzing and testing their performance and compatibility are needed to determine the limits of the technology. This paper presents analytical and experimental methods of determining network throughput, range and coverage, and interference sources. Both radio frequency (BE) domain and network domain analysis have been applied to determine wireless network throughput and range in the outdoor environment- Comparison of field test data taken under optimal conditions, with performance predicted from RF analysis, yielded quantitative results applicable to future designs. Layering multiple wireless network- sooners can increase performance. Wireless network components can be set to different radio frequency-hopping sequences or spreading functions, allowing more than one sooner to coexist. Therefore, we ran multiple 802.11-compliant systems concurrently in the same geographical area to determine interference effects and scalability, The results can be used to design of more robust networks which have multiple layers of wireless data communication paths and provide increased throughput overall.

Compact modeling of CRS devices based on ECM cells for memory, logic and neuromorphic applications.

PubMed

Linn, E; Menzel, S; Ferch, S; Waser, R

2013-09-27

Dynamic physics-based models of resistive switching devices are of great interest for the realization of complex circuits required for memory, logic and neuromorphic applications. Here, we apply such a model of an electrochemical metallization (ECM) cell to complementary resistive switches (CRSs), which are favorable devices to realize ultra-dense passive crossbar arrays. Since a CRS consists of two resistive switching devices, it is straightforward to apply the dynamic ECM model for CRS simulation with MATLAB and SPICE, enabling study of the device behavior in terms of sweep rate and series resistance variations. Furthermore, typical memory access operations as well as basic implication logic operations can be analyzed, revealing requirements for proper spike and level read operations. This basic understanding facilitates applications of massively parallel computing paradigms required for neuromorphic applications.

Giant Electroresistance in Edge Metal-Insulator-Metal Tunnel Junctions Induced by Ferroelectric Fringe Fields

PubMed Central

Jung, Sungchul; Jeon, Youngeun; Jin, Hanbyul; Lee, Jung-Yong; Ko, Jae-Hyeon; Kim, Nam; Eom, Daejin; Park, Kibog

2016-01-01

An enormous amount of research activities has been devoted to developing new types of non-volatile memory devices as the potential replacements of current flash memory devices. Theoretical device modeling was performed to demonstrate that a huge change of tunnel resistance in an Edge Metal-Insulator-Metal (EMIM) junction of metal crossbar structure can be induced by the modulation of electric fringe field, associated with the polarization reversal of an underlying ferroelectric layer. It is demonstrated that single three-terminal EMIM/Ferroelectric structure could form an active memory cell without any additional selection devices. This new structure can open up a way of fabricating all-thin-film-based, high-density, high-speed, and low-power non-volatile memory devices that are stackable to realize 3D memory architecture. PMID:27476475

Non-volatile memory based on the ferroelectric photovoltaic effect

PubMed Central

Guo, Rui; You, Lu; Zhou, Yang; Shiuh Lim, Zhi; Zou, Xi; Chen, Lang; Ramesh, R.; Wang, Junling

2013-01-01

The quest for a solid state universal memory with high-storage density, high read/write speed, random access and non-volatility has triggered intense research into new materials and novel device architectures. Though the non-volatile memory market is dominated by flash memory now, it has very low operation speed with ~10 μs programming and ~10 ms erasing time. Furthermore, it can only withstand ~105 rewriting cycles, which prevents it from becoming the universal memory. Here we demonstrate that the significant photovoltaic effect of a ferroelectric material, such as BiFeO3 with a band gap in the visible range, can be used to sense the polarization direction non-destructively in a ferroelectric memory. A prototype 16-cell memory based on the cross-bar architecture has been prepared and tested, demonstrating the feasibility of this technique. PMID:23756366

Internal filament modulation in low-dielectric gap design for built-in selector-less resistive switching memory application

NASA Astrophysics Data System (ADS)

Chen, Ying-Chen; Lin, Chih-Yang; Huang, Hui-Chun; Kim, Sungjun; Fowler, Burt; Chang, Yao-Feng; Wu, Xiaohan; Xu, Gaobo; Chang, Ting-Chang; Lee, Jack C.

2018-02-01

Sneak path current is a severe hindrance for the application of high-density resistive random-access memory (RRAM) array designs. In this work, we demonstrate nonlinear (NL) resistive switching characteristics of a HfO x /SiO x -based stacking structure as a realization for selector-less RRAM devices. The NL characteristic was obtained and designed by optimizing the internal filament location with a low effective dielectric constant in the HfO x /SiO x structure. The stacking HfO x /SiO x -based RRAM device as the one-resistor-only memory cell is applicable without needing an additional selector device to solve the sneak path issue with a switching voltage of ~1 V, which is desirable for low-power operating in built-in nonlinearity crossbar array configurations.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

Real-Time Visualization of Network Behaviors for Situational Awareness

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

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

Network Analysis of Rodent Transcriptomes in Spaceflight

NASA Technical Reports Server (NTRS)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

Multiple fMRI system-level baseline connectivity is disrupted in patients with consciousness alterations.

PubMed

Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea

2014-03-01

In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Efficient Quantum Transmission in Multiple-Source Networks

PubMed Central

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

2014-01-01

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

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Multiplex PageRank.

PubMed

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Low Complexity Track Initialization and Fusion for Multi-Modal Sensor Networks

DTIC Science & Technology

2012-11-08

feature was demonstrated via the simulations. Aerospace 2011work further documents our investigation of multiple target tracking filters in...bounds that determine how well a sensor network can resolve and localize multiple targets as a function of the operating parameters such as sensor...probability density (PHD) filter for binary measurements using proximity sensors. 15. SUBJECT TERMS proximity sensors, PHD filter, multiple

Networking CD-ROMs: A Tutorial Introduction.

ERIC Educational Resources Information Center

Perone, Karen

1996-01-01

Provides an introduction to CD-ROM networking. Highlights include LAN (local area network) architectures for CD-ROM networks, peer-to-peer networks, shared file and dedicated file servers, commercial software/vendor solutions, problems, multiple hardware platforms, and multimedia. Six figures illustrate network architectures and a sidebar contains…

Improving link prediction in complex networks by adaptively exploiting multiple structural features of networks

NASA Astrophysics Data System (ADS)

Ma, Chuang; Bao, Zhong-Kui; Zhang, Hai-Feng

2017-10-01

So far, many network-structure-based link prediction methods have been proposed. However, these methods only highlight one or two structural features of networks, and then use the methods to predict missing links in different networks. The performances of these existing methods are not always satisfied in all cases since each network has its unique underlying structural features. In this paper, by analyzing different real networks, we find that the structural features of different networks are remarkably different. In particular, even in the same network, their inner structural features are utterly different. Therefore, more structural features should be considered. However, owing to the remarkably different structural features, the contributions of different features are hard to be given in advance. Inspired by these facts, an adaptive fusion model regarding link prediction is proposed to incorporate multiple structural features. In the model, a logistic function combing multiple structural features is defined, then the weight of each feature in the logistic function is adaptively determined by exploiting the known structure information. Last, we use the "learnt" logistic function to predict the connection probabilities of missing links. According to our experimental results, we find that the performance of our adaptive fusion model is better than many similarity indices.

Protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

Protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1994-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs an antibody recognition message termination process performed by all remote nodes and a remote node polling process performed by other nodes which are master units controlling remote nodes in respective zones of the network assigned to respective master nodes. Each remote node repeats only those messages originated in the local zone, to provide isolation among the master nodes.

A Direct Position-Determination Approach for Multiple Sources Based on Neural Network Computation.

PubMed

Chen, Xin; Wang, Ding; Yin, Jiexin; Wu, Ying

2018-06-13

The most widely used localization technology is the two-step method that localizes transmitters by measuring one or more specified positioning parameters. Direct position determination (DPD) is a promising technique that directly localizes transmitters from sensor outputs and can offer superior localization performance. However, existing DPD algorithms such as maximum likelihood (ML)-based and multiple signal classification (MUSIC)-based estimations are computationally expensive, making it difficult to satisfy real-time demands. To solve this problem, we propose the use of a modular neural network for multiple-source DPD. In this method, the area of interest is divided into multiple sub-areas. Multilayer perceptron (MLP) neural networks are employed to detect the presence of a source in a sub-area and filter sources in other sub-areas, and radial basis function (RBF) neural networks are utilized for position estimation. Simulation results show that a number of appropriately trained neural networks can be successfully used for DPD. The performance of the proposed MLP-MLP-RBF method is comparable to the performance of the conventional MUSIC-based DPD algorithm for various signal-to-noise ratios and signal power ratios. Furthermore, the MLP-MLP-RBF network is less computationally intensive than the classical DPD algorithm and is therefore an attractive choice for real-time applications.

Complex Dynamics of Delay-Coupled Neural Networks

NASA Astrophysics Data System (ADS)

Mao, Xiaochen

2016-09-01

This paper reveals the complicated dynamics of a delay-coupled system that consists of a pair of sub-networks and multiple bidirectional couplings. Time delays are introduced into the internal connections and network-couplings, respectively. The stability and instability of the coupled network are discussed. The sufficient conditions for the existence of oscillations are given. Case studies of numerical simulations are given to validate the analytical results. Interesting and complicated neuronal activities are observed numerically, such as rest states, periodic oscillations, multiple switches of rest states and oscillations, and the coexistence of different types of oscillations.

Estimates of segregation and overlap of functional connectivity networks in the human cerebral cortex.

PubMed

Yeo, B T Thomas; Krienen, Fenna M; Chee, Michael W L; Buckner, Randy L

2014-03-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. © 2013.

Estimates of Segregation and Overlap of Functional Connectivity Networks in the Human Cerebral Cortex

PubMed Central

Yeo, BT Thomas; Krienen, Fenna M; Chee, Michael WL; Buckner, Randy L

2014-01-01

The organization of the human cerebral cortex has recently been explored using techniques for parcellating the cortex into distinct functionally coupled networks. The divergent and convergent nature of cortico-cortical anatomic connections suggests the need to consider the possibility of regions belonging to multiple networks and hierarchies among networks. Here we applied the Latent Dirichlet Allocation (LDA) model and spatial independent component analysis (ICA) to solve for functionally coupled cerebral networks without assuming that cortical regions belong to a single network. Data analyzed included 1,000 subjects from the Brain Genomics Superstruct Project (GSP) and 12 high quality individual subjects from the Human Connectome Project (HCP). The organization of the cerebral cortex was similar regardless of whether a winner-take-all approach or the more relaxed constraints of LDA (or ICA) were imposed. This suggests that large-scale networks may function as partially isolated modules. Several notable interactions among networks were uncovered by the LDA analysis. Many association regions belong to at least two networks, while somatomotor and early visual cortices are especially isolated. As examples of interaction, the precuneus, lateral temporal cortex, medial prefrontal cortex and posterior parietal cortex participate in multiple paralimbic networks that together comprise subsystems of the default network. In addition, regions at or near the frontal eye field and human lateral intraparietal area homologue participate in multiple hierarchically organized networks. These observations were replicated in both datasets and could be detected (and replicated) in individual subjects from the HCP. PMID:24185018

Identifying multiple influential spreaders based on generalized closeness centrality

NASA Astrophysics Data System (ADS)

Liu, Huan-Li; Ma, Chuang; Xiang, Bing-Bing; Tang, Ming; Zhang, Hai-Feng

2018-02-01

To maximize the spreading influence of multiple spreaders in complex networks, one important fact cannot be ignored: the multiple spreaders should be dispersively distributed in networks, which can effectively reduce the redundance of information spreading. For this purpose, we define a generalized closeness centrality (GCC) index by generalizing the closeness centrality index to a set of nodes. The problem converts to how to identify multiple spreaders such that an objective function has the minimal value. By comparing with the K-means clustering algorithm, we find that the optimization problem is very similar to the problem of minimizing the objective function in the K-means method. Therefore, how to find multiple nodes with the highest GCC value can be approximately solved by the K-means method. Two typical transmission dynamics-epidemic spreading process and rumor spreading process are implemented in real networks to verify the good performance of our proposed method.

Tunable optical frequency comb enabled scalable and cost-effective multiuser orthogonal frequency-division multiple access passive optical network with source-free optical network units.

PubMed

Chen, Chen; Zhang, Chongfu; Liu, Deming; Qiu, Kun; Liu, Shuang

2012-10-01

We propose and experimentally demonstrate a multiuser orthogonal frequency-division multiple access passive optical network (OFDMA-PON) with source-free optical network units (ONUs), enabled by tunable optical frequency comb generation technology. By cascading a phase modulator (PM) and an intensity modulator and dynamically controlling the peak-to-peak voltage of a PM driven signal, a tunable optical frequency comb source can be generated. It is utilized to assist the configuration of a multiple source-free ONUs enhanced OFDMA-PON where simultaneous and interference-free multiuser upstream transmission over a single wavelength can be efficiently supported. The proposed multiuser OFDMA-PON is scalable and cost effective, and its feasibility is successfully verified by experiment.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

NASA Astrophysics Data System (ADS)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Efficient and self-adaptive in-situ learning in multilayer memristor neural networks.

PubMed

Li, Can; Belkin, Daniel; Li, Yunning; Yan, Peng; Hu, Miao; Ge, Ning; Jiang, Hao; Montgomery, Eric; Lin, Peng; Wang, Zhongrui; Song, Wenhao; Strachan, John Paul; Barnell, Mark; Wu, Qing; Williams, R Stanley; Yang, J Joshua; Xia, Qiangfei

2018-06-19

Memristors with tunable resistance states are emerging building blocks of artificial neural networks. However, in situ learning on a large-scale multiple-layer memristor network has yet to be demonstrated because of challenges in device property engineering and circuit integration. Here we monolithically integrate hafnium oxide-based memristors with a foundry-made transistor array into a multiple-layer neural network. We experimentally demonstrate in situ learning capability and achieve competitive classification accuracy on a standard machine learning dataset, which further confirms that the training algorithm allows the network to adapt to hardware imperfections. Our simulation using the experimental parameters suggests that a larger network would further increase the classification accuracy. The memristor neural network is a promising hardware platform for artificial intelligence with high speed-energy efficiency.

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.

Traffic handling capability of a broadband indoor wireless network using CDMA multiple access

NASA Astrophysics Data System (ADS)

Zhang, Chang G.; Hafez, H. M.; Falconer, David D.

1994-05-01

CDMA (code division multiple access) may be an attractive technique for wireless access to broadband services because of its multiple access simplicity and other appealing features. In order to investigate traffic handling capabilities of a future network providing a variety of integrated services, this paper presents a study of a broadband indoor wireless network supporting high-speed traffic using CDMA multiple access. The results are obtained through the simulation of an indoor environment and the traffic capabilities of the wireless access to broadband 155.5 MHz ATM-SONET networks using the mm-wave band. A distributed system architecture is employed and the system performance is measured in terms of call blocking probability and dropping probability. The impacts of the base station density, traffic load, average holding time, and variable traffic sources on the system performance are examined. The improvement of system performance by implementing various techniques such as handoff, admission control, power control and sectorization are also investigated.

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Neural computation of arithmetic functions

NASA Technical Reports Server (NTRS)

Siu, Kai-Yeung; Bruck, Jehoshua

1990-01-01

An area of application of neural networks is considered. A neuron is modeled as a linear threshold gate, and the network architecture considered is the layered feedforward network. It is shown how common arithmetic functions such as multiplication and sorting can be efficiently computed in a shallow neural network. Some known results are improved by showing that the product of two n-bit numbers and sorting of n n-bit numbers can be computed by a polynomial-size neural network using only four and five unit delays, respectively. Moreover, the weights of each threshold element in the neural networks require O(log n)-bit (instead of n-bit) accuracy. These results can be extended to more complicated functions such as multiple products, division, rational functions, and approximation of analytic functions.

Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

PubMed

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Proceedings of the Mobile Satellite System Architectures and Multiple Access Techniques Workshop

NASA Technical Reports Server (NTRS)

Dessouky, Khaled

1989-01-01

The Mobile Satellite System Architectures and Multiple Access Techniques Workshop served as a forum for the debate of system and network architecture issues. Particular emphasis was on those issues relating to the choice of multiple access technique(s) for the Mobile Satellite Service (MSS). These proceedings contain articles that expand upon the 12 presentations given in the workshop. Contrasting views on Frequency Division Multiple Access (FDMA), Code Division Multiple Access (CDMA), and Time Division Multiple Access (TDMA)-based architectures are presented, and system issues relating to signaling, spacecraft design, and network management constraints are addressed. An overview article that summarizes the issues raised in the numerous discussion periods of the workshop is also included.

Circle of Care: Extending Beyond Primary Caregivers to Examine Collaborative Caretaking in Adolescent Development

PubMed Central

Margolis, Kathryn L.; Fosco, Gregory M.; Stormshak, Elizabeth A.

2013-01-01

In the contemporary family, which is increasingly shaped by multicultural influences, parents rarely are the sole caretakers of their children. To improve understanding of family dynamics, researchers must redefine caregiving networks to include multiple caregivers, such as extended family members. This study explored the influences of caregiving networks on youth depression by examining who youths perceived as caretakers, how many caretakers were in their networks, the youths’ connectedness with adults in their network, and harmony of relationships among adults within the network. Data from an ethnically diverse, urban sample of 180 middle school youths revealed participation of multiple caregivers for all groups, but ethnic differences existed in network composition. These differences in network composition are discussed within a socio-cultural context, considering how positive relationships with specific caregivers may buffer future depression. Longitudinal analyses confirmed the importance of positive relationships with caregiving networks for youth of color when predicting future depression. PMID:27453615

Computing Systemic Risk Using Multiple Behavioral and Keystone Networks: The Emergence of a Crisis in Primate Societies and Banks*

PubMed Central

Fushing, Hsieh; Jordà, Òscar; Beisner, Brianne; McCowan, Brenda

2015-01-01

What do the behavior of monkeys in captivity and the financial system have in common? The nodes in such social systems relate to each other through multiple and keystone networks, not just one network. Each network in the system has its own topology, and the interactions among the system’s networks change over time. In such systems, the lead into a crisis appears to be characterized by a decoupling of the networks from the keystone network. This decoupling can also be seen in the crumbling of the keystone’s power structure toward a more horizontal hierarchy. This paper develops nonparametric methods for describing the joint model of the latent architecture of interconnected networks in order to describe this process of decoupling, and hence provide an early warning system of an impending crisis. PMID:26056422

Scalable Lunar Surface Networks and Adaptive Orbit Access

NASA Technical Reports Server (NTRS)

Wang, Xudong

2015-01-01

Teranovi Technologies, Inc., has developed innovative network architecture, protocols, and algorithms for both lunar surface and orbit access networks. A key component of the overall architecture is a medium access control (MAC) protocol that includes a novel mechanism of overlaying time division multiple access (TDMA) and carrier sense multiple access with collision avoidance (CSMA/CA), ensuring scalable throughput and quality of service. The new MAC protocol is compatible with legacy Institute of Electrical and Electronics Engineers (IEEE) 802.11 networks. Advanced features include efficiency power management, adaptive channel width adjustment, and error control capability. A hybrid routing protocol combines the advantages of ad hoc on-demand distance vector (AODV) routing and disruption/delay-tolerant network (DTN) routing. Performance is significantly better than AODV or DTN and will be particularly effective for wireless networks with intermittent links, such as lunar and planetary surface networks and orbit access networks.

An energy efficient distance-aware routing algorithm with multiple mobile sinks for wireless sensor networks.

PubMed

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-08-18

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption.

An Energy Efficient Distance-Aware Routing Algorithm with Multiple Mobile Sinks for Wireless Sensor Networks

PubMed Central

Wang, Jin; Li, Bin; Xia, Feng; Kim, Chang-Seob; Kim, Jeong-Uk

2014-01-01

Traffic patterns in wireless sensor networks (WSNs) usually follow a many-to-one model. Sensor nodes close to static sinks will deplete their limited energy more rapidly than other sensors, since they will have more data to forward during multihop transmission. This will cause network partition, isolated nodes and much shortened network lifetime. Thus, how to balance energy consumption for sensor nodes is an important research issue. In recent years, exploiting sink mobility technology in WSNs has attracted much research attention because it can not only improve energy efficiency, but prolong network lifetime. In this paper, we propose an energy efficient distance-aware routing algorithm with multiple mobile sink for WSNs, where sink nodes will move with a certain speed along the network boundary to collect monitored data. We study the influence of multiple mobile sink nodes on energy consumption and network lifetime, and we mainly focus on the selection of mobile sink node number and the selection of parking positions, as well as their impact on performance metrics above. We can see that both mobile sink node number and the selection of parking position have important influence on network performance. Simulation results show that our proposed routing algorithm has better performance than traditional routing ones in terms of energy consumption. PMID:25196015

How multiple social networks affect user awareness: The information diffusion process in multiplex networks

NASA Astrophysics Data System (ADS)

Li, Weihua; Tang, Shaoting; Fang, Wenyi; Guo, Quantong; Zhang, Xiao; Zheng, Zhiming

2015-10-01

The information diffusion process in single complex networks has been extensively studied, especially for modeling the spreading activities in online social networks. However, individuals usually use multiple social networks at the same time, and can share the information they have learned from one social network to another. This phenomenon gives rise to a new diffusion process on multiplex networks with more than one network layer. In this paper we account for this multiplex network spreading by proposing a model of information diffusion in two-layer multiplex networks. We develop a theoretical framework using bond percolation and cascading failure to describe the intralayer and interlayer diffusion. This allows us to obtain analytical solutions for the fraction of informed individuals as a function of transmissibility T and the interlayer transmission rate θ . Simulation results show that interaction between layers can greatly enhance the information diffusion process. And explosive diffusion can occur even if the transmissibility of the focal layer is under the critical threshold, due to interlayer transmission.

Multiple-Flat-Panel System Displays Multidimensional Data

NASA Technical Reports Server (NTRS)

Gundo, Daniel; Levit, Creon; Henze, Christopher; Sandstrom, Timothy; Ellsworth, David; Green, Bryan; Joly, Arthur

2006-01-01

The NASA Ames hyperwall is a display system designed to facilitate the visualization of sets of multivariate and multidimensional data like those generated in complex engineering and scientific computations. The hyperwall includes a 77 matrix of computer-driven flat-panel video display units, each presenting an image of 1,280 1,024 pixels. The term hyperwall reflects the fact that this system is a more capable successor to prior computer-driven multiple-flat-panel display systems known by names that include the generic term powerwall and the trade names PowerWall and Powerwall. Each of the 49 flat-panel displays is driven by a rack-mounted, dual-central-processing- unit, workstation-class personal computer equipped with a hig-hperformance graphical-display circuit card and with a hard-disk drive having a storage capacity of 100 GB. Each such computer is a slave node in a master/ slave computing/data-communication system (see Figure 1). The computer that acts as the master node is similar to the slave-node computers, except that it runs the master portion of the system software and is equipped with a keyboard and mouse for control by a human operator. The system utilizes commercially available master/slave software along with custom software that enables the human controller to interact simultaneously with any number of selected slave nodes. In a powerwall, a single rendering task is spread across multiple processors and then the multiple outputs are tiled into one seamless super-display. It must be noted that the hyperwall concept subsumes the powerwall concept in that a single scene could be rendered as a mosaic image on the hyperwall. However, the hyperwall offers a wider set of capabilities to serve a different purpose: The hyperwall concept is one of (1) simultaneously displaying multiple different but related images, and (2) providing means for composing and controlling such sets of images. In place of elaborate software or hardware crossbar switches, the hyperwall concept substitutes reliance on the human visual system for integration, synthesis, and discrimination of patterns in complex and high-dimensional data spaces represented by the multiple displayed images. The variety of multidimensional data sets that can be displayed on the hyperwall is practically unlimited. For example, Figure 2 shows a hyperwall display of surface pressures and streamlines from a computational simulation of airflow about an aerospacecraft at various Mach numbers and angles of attack. In this display, Mach numbers increase from left to right and angles of attack increase from bottom to top. That is, all images in the same column represent simulations at the same Mach number, while all images in the same row represent simulations at the same angle of attack. The same viewing transformations and the same mapping from surface pressure to colors were used in generating all the images.

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

Du, Gang, E-mail: dugang@hdu.edu.cn; Li, Hongxia; Mao, Qinan

A bidirectional threshold switching (TS) characteristic was demonstrated in Ag/ZrO{sub 2}/Pt electrochemical metallization cells by using the electrochemical active Ag electrode and appropriate programming operation strategies The volatile TS was stable and reproducible and the rectify ratio could be tuned to ∼10{sup 7} by engineering the compliance current. We infer that the volatile behavior is essentially due to the moisture absorption in the electron beam evaporated films, which remarkably improved the anodic oxidation as well as the migration of Ag{sup +} ions. The resultant electromotive force would act as a driving force for the metal filaments dissolution, leading to themore » spontaneous volatile characteristics. Moreover, conductance quantization behaviors were also achieved owing to formation and annihilation of atomic scale metal filaments in the film matrix. Our results illustrate that the Ag/ZrO{sub 2}/Pt device with superior TS performances is a promising candidate for selector applications in passive crossbar arrays.« less

Fully-Coupled Thermo-Electrical Modeling and Simulation of Transition Metal Oxide Memristors

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

Mamaluy, Denis; Gao, Xujiao; Tierney, Brian David

2016-11-01

Transition metal oxide (TMO) memristors have recently attracted special attention from the semiconductor industry and academia. Memristors are one of the strongest candidates to replace flash memory, and possibly DRAM and SRAM in the near future. Moreover, memristors have a high potential to enable beyond-CMOS technology advances in novel architectures for high performance computing (HPC). The utility of memristors has been demonstrated in reprogrammable logic (cross-bar switches), brain-inspired computing and in non-CMOS complementary logic. Indeed, the potential use of memristors as logic devices is especially important considering the inevitable end of CMOS technology scaling that is anticipated by 2025. Inmore » order to aid the on-going Sandia memristor fabrication effort with a memristor design tool and establish a clear physical picture of resistance switching in TMO memristors, we have created and validated with experimental data a simulation tool we name the Memristor Charge Transport (MCT) Simulator.« less

PCI-based WILDFIRE reconfigurable computing engines

NASA Astrophysics Data System (ADS)

Fross, Bradley K.; Donaldson, Robert L.; Palmer, Douglas J.

1996-10-01

WILDFORCE is the first PCI-based custom reconfigurable computer that is based on the Splash 2 technology transferred from the National Security Agency and the Institute for Defense Analyses, Supercomputing Research Center (SRC). The WILDFORCE architecture has many of the features of the WILDFIRE computer, such as field- programmable gate array (FPGA) based processing elements, linear array and crossbar interconnection, and high- performance memory and I/O subsystems. New features introduced in the PCI-based WILDFIRE systems include memory/processor options that can be added to any processing element. These options include static and dynamic memory, digital signal processors (DSPs), FPGAs, and microprocessors. In addition to memory/processor options, many different application specific connectors can be used to extend the I/O capabilities of the system, including systolic I/O, camera input and video display output. This paper also discusses how this new PCI-based reconfigurable computing engine is used for rapid-prototyping, real-time video processing and other DSP applications.

Effect of thermal insulation on the electrical characteristics of NbOx threshold switches

NASA Astrophysics Data System (ADS)

Wang, Ziwen; Kumar, Suhas; Wong, H.-S. Philip; Nishi, Yoshio

2018-02-01

Threshold switches based on niobium oxide (NbOx) are promising candidates as bidirectional selector devices in crossbar memory arrays and building blocks for neuromorphic computing. Here, it is experimentally demonstrated that the electrical characteristics of NbOx threshold switches can be tuned by engineering the thermal insulation. Increasing the thermal insulation by ˜10× is shown to produce ˜7× reduction in threshold current and ˜45% reduction in threshold voltage. The reduced threshold voltage leads to ˜5× reduction in half-selection leakage, which highlights the effectiveness of reducing half-selection leakage of NbOx selectors by engineering the thermal insulation. A thermal feedback model based on Poole-Frenkel conduction in NbOx can explain the experimental results very well, which also serves as a piece of strong evidence supporting the validity of the Poole-Frenkel based mechanism in NbOx threshold switches.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

PubMed

Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

Quantum key distribution network for multiple applications

NASA Astrophysics Data System (ADS)

Tajima, A.; Kondoh, T.; Ochi, T.; Fujiwara, M.; Yoshino, K.; Iizuka, H.; Sakamoto, T.; Tomita, A.; Shimamura, E.; Asami, S.; Sasaki, M.

2017-09-01

The fundamental architecture and functions of secure key management in a quantum key distribution (QKD) network with enhanced universal interfaces for smooth key sharing between arbitrary two nodes and enabling multiple secure communication applications are proposed. The proposed architecture consists of three layers: a quantum layer, key management layer and key supply layer. We explain the functions of each layer, the key formats in each layer and the key lifecycle for enabling a practical QKD network. A quantum key distribution-advanced encryption standard (QKD-AES) hybrid system and an encrypted smartphone system were developed as secure communication applications on our QKD network. The validity and usefulness of these systems were demonstrated on the Tokyo QKD Network testbed.

Monitoring technique for multiple power splitter-passive optical networks using a tunable OTDR and FBGs

NASA Astrophysics Data System (ADS)

Hann, Swook; Kim, Dong-Hwan; Park, Chang-Soo

2006-04-01

A monitoring technique for multiple power splitter-passive optical networks (PS-PON) is presented. The technique is based on the remote sensing of fiber Bragg grating (FBG) using a tunable OTDR. To monitor the multiple PS-PON, the FBG can be used for a wavelength dependent reflective reference on each branch end of the PS. The FBG helps discern an individual event of the multiple PS-PON for the monitoring in collaborate with information of Rayleigh backscattered power. The multiple PS-PON can be analyzed by the monitoring method at the central office under 10-Gbit/s in-service.

Naming Game with Multiple Hearers

NASA Astrophysics Data System (ADS)

Li, Bing; Chen, Guanrong; Chow, Tommy W. S.

2013-05-01

A new model called Naming Game with Multiple Hearers (NGMH) is proposed in this paper. A naming game over a population of individuals aims to reach consensus on the name of an object through pair-wise local interactions among all the individuals. The proposed NGMH model describes the learning process of a new word, in a population with one speaker and multiple hearers, at each interaction towards convergence. The characteristics of NGMH are examined on three types of network topologies, namely ER random-graph network, WS small-world network, and BA scale-free network. Comparative analysis on the convergence time is performed, revealing that the topology with a larger average (node) degree can reach consensus faster than the others over the same population. It is found that, for a homogeneous network, the average degree is the limiting value of the number of hearers, which reduces the individual ability of learning new words, consequently decreasing the convergence time; for a scale-free network, this limiting value is the deviation of the average degree. It is also found that a network with a larger clustering coefficient takes longer time to converge; especially a small-word network with smallest rewiring possibility takes longest time to reach convergence. As more new nodes are being added to scale-free networks with different degree distributions, their convergence time appears to be robust against the network-size variation. Most new findings reported in this paper are different from that of the single-speaker/single-hearer naming games documented in the literature.

Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

PubMed Central

Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

2016-01-01

Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

Link prediction in multiplex online social networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Link prediction in multiplex online social networks.

PubMed

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

An open source web interface for linking models to infrastructure system databases

NASA Astrophysics Data System (ADS)

Knox, S.; Mohamed, K.; Harou, J. J.; Rheinheimer, D. E.; Medellin-Azuara, J.; Meier, P.; Tilmant, A.; Rosenberg, D. E.

2016-12-01

Models of networked engineered resource systems such as water or energy systems are often built collaboratively with developers from different domains working at different locations. These models can be linked to large scale real world databases, and they are constantly being improved and extended. As the development and application of these models becomes more sophisticated, and the computing power required for simulations and/or optimisations increases, so has the need for online services and tools which enable the efficient development and deployment of these models. Hydra Platform is an open source, web-based data management system, which allows modellers of network-based models to remotely store network topology and associated data in a generalised manner, allowing it to serve multiple disciplines. Hydra Platform uses a web API using JSON to allow external programs (referred to as `Apps') to interact with its stored networks and perform actions such as importing data, running models, or exporting the networks to different formats. Hydra Platform supports multiple users accessing the same network and has a suite of functions for managing users and data. We present ongoing development in Hydra Platform, the Hydra Web User Interface, through which users can collaboratively manage network data and models in a web browser. The web interface allows multiple users to graphically access, edit and share their networks, run apps and view results. Through apps, which are located on the server, the web interface can give users access to external data sources and models without the need to install or configure any software. This also ensures model results can be reproduced by removing platform or version dependence. Managing data and deploying models via the web interface provides a way for multiple modellers to collaboratively manage data, deploy and monitor model runs and analyse results.

Overlapping Networks Engaged during Spoken Language Production and Its Cognitive Control

PubMed Central

Wise, Richard J.S.; Mehta, Amrish; Leech, Robert

2014-01-01

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and “rest,” to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. PMID:24966373

A carrier sensed multiple access protocol for high data base rate ring networks

NASA Technical Reports Server (NTRS)

Foudriat, E. C.; Maly, Kurt J.; Overstreet, C. Michael; Khanna, S.; Paterra, Frank

1990-01-01

The results of the study of a simple but effective media access protocol for high data rate networks are presented. The protocol is based on the fact that at high data rates networks can contain multiple messages simultaneously over their span, and that in a ring, nodes used to detect the presence of a message arriving from the immediate upstream neighbor. When an incoming signal is detected, the node must either abort or truncate a message it is presently sending. Thus, the protocol with local carrier sensing and multiple access is designated CSMA/RN. The performance of CSMA/RN with TTattempt and truncate is studied using analytic and simulation models. Three performance factors, wait or access time, service time and response or end-to-end travel time are presented. The service time is basically a function of the network rate, it changes by a factor of 1 between no load and full load. Wait time, which is zero for no load, remains small for load factors up to 70 percent of full load. Response time, which adds travel time while on the network to wait and service time, is mainly a function of network length, especially for longer distance networks. Simulation results are shown for CSMA/RN where messages are removed at the destination. A wide range of local and metropolitan area network parameters including variations in message size, network length, and node count are studied. Finally, a scaling factor based upon the ratio of message to network length demonstrates that the results, and hence, the CSMA/RN protocol, are applicable to wide area networks.

Overlapping networks engaged during spoken language production and its cognitive control.

PubMed

Geranmayeh, Fatemeh; Wise, Richard J S; Mehta, Amrish; Leech, Robert

2014-06-25

Spoken language production is a complex brain function that relies on large-scale networks. These include domain-specific networks that mediate language-specific processes, as well as domain-general networks mediating top-down and bottom-up attentional control. Language control is thought to involve a left-lateralized fronto-temporal-parietal (FTP) system. However, these regions do not always activate for language tasks and similar regions have been implicated in nonlinguistic cognitive processes. These inconsistent findings suggest that either the left FTP is involved in multidomain cognitive control or that there are multiple spatially overlapping FTP systems. We present evidence from an fMRI study using multivariate analysis to identify spatiotemporal networks involved in spoken language production in humans. We compared spoken language production (Speech) with multiple baselines, counting (Count), nonverbal decision (Decision), and "rest," to pull apart the multiple partially overlapping networks that are involved in speech production. A left-lateralized FTP network was activated during Speech and deactivated during Count and nonverbal Decision trials, implicating it in cognitive control specific to sentential spoken language production. A mirror right-lateralized FTP network was activated in the Count and Decision trials, but not Speech. Importantly, a second overlapping left FTP network showed relative deactivation in Speech. These three networks, with distinct time courses, overlapped in the left parietal lobe. Contrary to the standard model of the left FTP as being dominant for speech, we revealed a more complex pattern within the left FTP, including at least two left FTP networks with competing functional roles, only one of which was activated in speech production. Copyright © 2014 Geranmayeh et al.

Dynamic Modeling of Systemic Risk in Financial Networks

NASA Astrophysics Data System (ADS)

Avakian, Adam

Modern financial networks are complicated structures that can contain multiple types of nodes and connections between those nodes. Banks, governments and even individual people weave into an intricate network of debt, risk correlations and many other forms of interconnectedness. We explore multiple types of financial network models with a focus on understanding the dynamics and causes of cascading failures in such systems. In particular, we apply real-world data from multiple sources to these models to better understand real-world financial networks. We use the results of the Federal Reserve "Banking Organization Systemic Risk Report" (FR Y-15), which surveys the largest US banks on their level of interconnectedness, to find relationships between various measures of network connectivity and systemic risk in the US financial sector. This network model is then stress-tested under a number of scenarios to determine systemic risks inherent in the various network structures. We also use detailed historical balance sheet data from the Venezuelan banking system to build a bipartite network model and find relationships between the changing network structure over time and the response of the system to various shocks. We find that the relationship between interconnectedness and systemic risk is highly dependent on the system and model but that it is always a significant one. These models are useful tools that add value to regulators in creating new measurements of systemic risk in financial networks. These models could be used as macroprudential tools for monitoring the health of the entire banking system as a whole rather than only of individual banks.

High speed polling protocol for multiple node network with sequential flooding of a polling message and a poll-answering message

NASA Technical Reports Server (NTRS)

Marvit, Maclen (Inventor); Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs a remote node polling process performed by a master node by transmitting a polling message generically addressed to all remote nodes associated with the master node. Each remote node responds upon receipt of the generically addressed polling message by sequentially flooding the network with a poll-answering informational message and with the polling message.

Muscle networks: Connectivity analysis of EMG activity during postural control

NASA Astrophysics Data System (ADS)

Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

2015-12-01

Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Locating multiple diffusion sources in time varying networks from sparse observations.

PubMed

Hu, Zhao-Long; Shen, Zhesi; Cao, Shinan; Podobnik, Boris; Yang, Huijie; Wang, Wen-Xu; Lai, Ying-Cheng

2018-02-08

Data based source localization in complex networks has a broad range of applications. Despite recent progress, locating multiple diffusion sources in time varying networks remains to be an outstanding problem. Bridging structural observability and sparse signal reconstruction theories, we develop a general framework to locate diffusion sources in time varying networks based solely on sparse data from a small set of messenger nodes. A general finding is that large degree nodes produce more valuable information than small degree nodes, a result that contrasts that for static networks. Choosing large degree nodes as the messengers, we find that sparse observations from a few such nodes are often sufficient for any number of diffusion sources to be located for a variety of model and empirical networks. Counterintuitively, sources in more rapidly varying networks can be identified more readily with fewer required messenger nodes.

Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees.

PubMed

Mirzaei, Sajad; Wu, Yufeng

2016-01-01

Hybridization networks represent plausible evolutionary histories of species that are affected by reticulate evolutionary processes. An established computational problem on hybridization networks is constructing the most parsimonious hybridization network such that each of the given phylogenetic trees (called gene trees) is "displayed" in the network. There have been several previous approaches, including an exact method and several heuristics, for this NP-hard problem. However, the exact method is only applicable to a limited range of data, and heuristic methods can be less accurate and also slow sometimes. In this paper, we develop a new algorithm for constructing near parsimonious networks for multiple binary gene trees. This method is more efficient for large numbers of gene trees than previous heuristics. This new method also produces more parsimonious results on many simulated datasets as well as a real biological dataset than a previous method. We also show that our method produces topologically more accurate networks for many datasets.

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

PubMed

Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

2018-04-16

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

An elementary quantum network using robust nuclear spin qubits in diamond

NASA Astrophysics Data System (ADS)

Kalb, Norbert; Reiserer, Andreas; Humphreys, Peter; Blok, Machiel; van Bemmelen, Koen; Twitchen, Daniel; Markham, Matthew; Taminiau, Tim; Hanson, Ronald

Quantum registers containing multiple robust qubits can form the nodes of future quantum networks for computation and communication. Information storage within such nodes must be resilient to any type of local operation. Here we demonstrate multiple robust memories by employing five nuclear spins adjacent to a nitrogen-vacancy defect centre in diamond. We characterize the storage of quantum superpositions and their resilience to entangling attempts with the electron spin of the defect centre. The storage fidelity is found to be limited by the probabilistic electron spin reset after failed entangling attempts. Control over multiple memories is then utilized to encode states in decoherence protected subspaces with increased robustness. Furthermore we demonstrate memory control in two optically linked network nodes and characterize the storage capabilities of both memories in terms of the process fidelity with the identity. These results pave the way towards multi-qubit quantum algorithms in a remote network setting.

Quantification of Road Network Vulnerability and Traffic Impacts to Regional Landslide Hazards.

NASA Astrophysics Data System (ADS)

Postance, Benjamin; Hillier, John; Dixon, Neil; Dijkstra, Tom

2015-04-01

Slope instability represents a prevalent hazard to transport networks. In the UK regional road networks are frequently disrupted by multiple slope failures triggered during intense precipitation events; primarily due to a degree of regional homogeneity of slope materials, geomorphology and weather conditions. It is of interest to examine how different locations and combinations of slope failure impact road networks, particularly in the context of projected climate change and a 40% increase in UK road demand by 2040. In this study an extensive number (>50 000) of multiple failure event scenarios are simulated within a dynamic micro simulation to assess traffic impacts during peak flow (7 - 10 AM). Possible failure locations are selected within the county of Gloucestershire (3150 km2) using historic failure sites and British Geological Survey GeoSure data. Initial investigations employ a multiple linear regression analyses to consider the severity of traffic impacts, as measured by time, in respect of spatial and topographical network characteristics including connectivity, density and capacity in proximity to failure sites; the network distance between disruptions in multiple failure scenarios is used to consider the effects of spatial clustering. The UK Department of Transport road travel demand and UKCP09 weather projection data to 2080 provide a suitable basis for traffic simulations and probabilistic slope stability assessments. Future work will thus focus on the development of a catastrophe risk model to simulate traffic impacts under various narratives of future travel demand and slope instability under climatic change. The results of this investigation shall contribute to the understanding of road network vulnerabilities and traffic impacts from climate driven slope hazards.

Effect of the heterogeneous neuron and information transmission delay on stochastic resonance of neuronal networks

NASA Astrophysics Data System (ADS)

Wang, Qingyun; Zhang, Honghui; Chen, Guanrong

2012-12-01

We study the effect of heterogeneous neuron and information transmission delay on stochastic resonance of scale-free neuronal networks. For this purpose, we introduce the heterogeneity to the specified neuron with the highest degree. It is shown that in the absence of delay, an intermediate noise level can optimally assist spike firings of collective neurons so as to achieve stochastic resonance on scale-free neuronal networks for small and intermediate αh, which plays a heterogeneous role. Maxima of stochastic resonance measure are enhanced as αh increases, which implies that the heterogeneity can improve stochastic resonance. However, as αh is beyond a certain large value, no obvious stochastic resonance can be observed. If the information transmission delay is introduced to neuronal networks, stochastic resonance is dramatically affected. In particular, the tuned information transmission delay can induce multiple stochastic resonance, which can be manifested as well-expressed maximum in the measure for stochastic resonance, appearing every multiple of one half of the subthreshold stimulus period. Furthermore, we can observe that stochastic resonance at odd multiple of one half of the subthreshold stimulus period is subharmonic, as opposed to the case of even multiple of one half of the subthreshold stimulus period. More interestingly, multiple stochastic resonance can also be improved by the suitable heterogeneous neuron. Presented results can provide good insights into the understanding of the heterogeneous neuron and information transmission delay on realistic neuronal networks.

Adaptive Connectivity Restoration from Node Failure(s) in Wireless Sensor Networks

PubMed Central

Wang, Huaiyuan; Ding, Xu; Huang, Cheng; Wu, Xiaobei

2016-01-01

Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA. PMID:27690030

Substance Use, Distress, and Adolescent School Networks

PubMed Central

McLeod, Jane D.; Uemura, Ryotaro

2012-01-01

This study examined the associations of substance use, psychological distress, and mental health services receipt with the structure and content of adolescent school-based networks. Using data from the National Longitudinal Study of Adolescent Health, we found that substance use was associated with receiving more, but making fewer, peer nominations. It also was associated with less favorable network characteristics, such as low GPA. Services receipt was associated with receiving and making fewer nominations, less favorable network characteristics, and a lower likelihood of reciprocated best friendships. Psychological distress had fewer significant associations. All associations were modest in magnitude. Our results suggest the importance of considering multiple indicators of socioemotional problems and multiple dimensions of social networks in research on adolescent peer relations. PMID:23066337

The International Postal Network and Other Global Flows as Proxies for National Wellbeing.

PubMed

Hristova, Desislava; Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

2016-01-01

The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals.

The International Postal Network and Other Global Flows as Proxies for National Wellbeing

PubMed Central

Rutherford, Alex; Anson, Jose; Luengo-Oroz, Miguel; Mascolo, Cecilia

2016-01-01

The digital exhaust left by flows of physical and digital commodities provides a rich measure of the nature, strength and significance of relationships between countries in the global network. With this work, we examine how these traces and the network structure can reveal the socioeconomic profile of different countries. We take into account multiple international networks of physical and digital flows, including the previously unexplored international postal network. By measuring the position of each country in the Trade, Postal, Migration, International Flights, IP and Digital Communications networks, we are able to build proxies for a number of crucial socioeconomic indicators such as GDP per capita and the Human Development Index ranking along with twelve other indicators used as benchmarks of national well-being by the United Nations and other international organisations. In this context, we have also proposed and evaluated a global connectivity degree measure applying multiplex theory across the six networks that accounts for the strength of relationships between countries. We conclude by showing how countries with shared community membership over multiple networks have similar socioeconomic profiles. Combining multiple flow data sources can help understand the forces which drive economic activity on a global level. Such an ability to infer proxy indicators in a context of incomplete information is extremely timely in light of recent discussions on measurement of indicators relevant to the Sustainable Development Goals. PMID:27248142

The maintenance of cooperation in multiplex networks with limited and partible resources of agents

NASA Astrophysics Data System (ADS)

Li, Zhaofeng; Shen, Bi; Jiang, Yichuan

2017-02-01

In this paper, we try to explain the maintenance of cooperation in multiplex networks with limited and partible resources of agents: defection brings larger short-term benefit and cooperative agents may become defective because of the unaffordable costs of cooperative behaviors that are performed in multiple layers simultaneously. Recent studies have identified the positive effects of multiple layers on evolutionary cooperation but generally overlook the maximum costs of agents in these synchronous games. By utilizing network effects and designing evolutionary mechanisms, cooperative behaviors become prevailing in public goods games, and agents can allocate personal resources across multiple layers. First, we generalize degree diversity into multiplex networks to improve the prospect for cooperation. Second, to prevent agents allocating all the resources into one layer, a greedy-first mechanism is proposed, in which agents prefer to add additional investments in the higher-payoff layer. It is found that greedy-first agents can perform cooperative behaviors in multiplex networks when one layer is scale-free network and degree differences between conjoint nodes increase. Our work may help to explain the emergence of cooperation in the absence of individual reputation and punishment mechanisms.

Bayesian networks improve causal environmental ...

EPA Pesticide Factsheets

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value

Boolean and brain-inspired computing using spin-transfer torque devices

NASA Astrophysics Data System (ADS)

Fan, Deliang

Several completely new approaches (such as spintronic, carbon nanotube, graphene, TFETs, etc.) to information processing and data storage technologies are emerging to address the time frame beyond current Complementary Metal-Oxide-Semiconductor (CMOS) roadmap. The high speed magnetization switching of a nano-magnet due to current induced spin-transfer torque (STT) have been demonstrated in recent experiments. Such STT devices can be explored in compact, low power memory and logic design. In order to truly leverage STT devices based computing, researchers require a re-think of circuit, architecture, and computing model, since the STT devices are unlikely to be drop-in replacements for CMOS. The potential of STT devices based computing will be best realized by considering new computing models that are inherently suited to the characteristics of STT devices, and new applications that are enabled by their unique capabilities, thereby attaining performance that CMOS cannot achieve. The goal of this research is to conduct synergistic exploration in architecture, circuit and device levels for Boolean and brain-inspired computing using nanoscale STT devices. Specifically, we first show that the non-volatile STT devices can be used in designing configurable Boolean logic blocks. We propose a spin-memristor threshold logic (SMTL) gate design, where memristive cross-bar array is used to perform current mode summation of binary inputs and the low power current mode spintronic threshold device carries out the energy efficient threshold operation. Next, for brain-inspired computing, we have exploited different spin-transfer torque device structures that can implement the hard-limiting and soft-limiting artificial neuron transfer functions respectively. We apply such STT based neuron (or 'spin-neuron') in various neural network architectures, such as hierarchical temporal memory and feed-forward neural network, for performing "human-like" cognitive computing, which show more than two orders of lower energy consumption compared to state of the art CMOS implementation. Finally, we show the dynamics of injection locked Spin Hall Effect Spin-Torque Oscillator (SHE-STO) cluster can be exploited as a robust multi-dimensional distance metric for associative computing, image/ video analysis, etc. Our simulation results show that the proposed system architecture with injection locked SHE-STOs and the associated CMOS interface circuits can be suitable for robust and energy efficient associative computing and pattern matching.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

NASA Astrophysics Data System (ADS)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

Multiple μ-stability of neural networks with unbounded time-varying delays.

PubMed

Wang, Lili; Chen, Tianping

2014-05-01

In this paper, we are concerned with a class of recurrent neural networks with unbounded time-varying delays. Based on the geometrical configuration of activation functions, the phase space R(n) can be divided into several Φη-type subsets. Accordingly, a new set of regions Ωη are proposed, and rigorous mathematical analysis is provided to derive the existence of equilibrium point and its local μ-stability in each Ωη. It concludes that the n-dimensional neural networks can exhibit at least 3(n) equilibrium points and 2(n) of them are μ-stable. Furthermore, due to the compatible property, a set of new conditions are presented to address the dynamics in the remaining 3(n)-2(n) subset regions. As direct applications of these results, we can get some criteria on the multiple exponential stability, multiple power stability, multiple log-stability, multiple log-log-stability and so on. In addition, the approach and results can also be extended to the neural networks with K-level nonlinear activation functions and unbounded time-varying delays, in which there can store (2K+1)(n) equilibrium points, (K+1)(n) of them are locally μ-stable. Numerical examples are given to illustrate the effectiveness of our results. Copyright © 2014 Elsevier Ltd. All rights reserved.

Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

PubMed

Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

2013-01-28

We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile.

A Regularizer Approach for RBF Networks Under the Concurrent Weight Failure Situation.

PubMed

Leung, Chi-Sing; Wan, Wai Yan; Feng, Ruibin

2017-06-01

Many existing results on fault-tolerant algorithms focus on the single fault source situation, where a trained network is affected by one kind of weight failure. In fact, a trained network may be affected by multiple kinds of weight failure. This paper first studies how the open weight fault and the multiplicative weight noise degrade the performance of radial basis function (RBF) networks. Afterward, we define the objective function for training fault-tolerant RBF networks. Based on the objective function, we then develop two learning algorithms, one batch mode and one online mode. Besides, the convergent conditions of our online algorithm are investigated. Finally, we develop a formula to estimate the test set error of faulty networks trained from our approach. This formula helps us to optimize some tuning parameters, such as RBF width.

Allocation and management issues in multiple-transaction open access transmission networks

NASA Astrophysics Data System (ADS)

Tao, Shu

This thesis focuses on some key issues related to allocation and management by the independent grid operator (IGO) of unbundled services in multiple-transaction open access transmission networks. The three unbundled services addressed in the thesis are transmission real power losses, reactive power support requirements from generation sources, and transmission congestion management. We develop the general framework that explicitly represents multiple transactions undertaken simultaneously in the transmission grid. This framework serves as the basis for formulating various problems treated in the thesis. We use this comprehensive framework to develop a physical-flow-based mechanism to allocate the total transmission losses to each transaction using the system. An important property of the allocation scheme is its capability to effectively deal with counter flows that result in the presence of specific transactions. Using the loss allocation results as the basis, we construct the equivalent loss compensation concept and apply it to develop flexible and effective procedures for compensating losses in multiple-transaction networks. We present a new physical-flow-based mechanism for allocating the reactive power support requirements provided by generators in multiple-transaction networks. The allocatable reactive support requirements are formulated as the sum of two specific components---the voltage magnitude variation component and the voltage angle variation component. The formulation utilizes the multiple-transaction framework and makes use of certain simplifying approximations. The formulation leads to a natural allocation as a function of the amount of each transaction. The physical interpretation of each allocation as a sensitivity of the reactive output of a generator is discussed. We propose a congestion management allocation scheme for multiple-transaction networks. The proposed scheme determines the allocation of congestion among the transactions on a physical-flow basis. It also proposes a congestion relief scheme that removes the congestion attributed to each transaction on the network in a least-cost manner to the IGO and determines the appropriate transmission charges to each transaction for its transmission usage. The thesis provides a compendium of problems that are natural extensions of the research results reported here and appear to be good candidates for future work.

Multiple attribute decision making model and application to food safety risk evaluation.

PubMed

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Unprotected sex of homeless youth: results from a multilevel dyadic analysis of individual, social network, and relationship factors.

PubMed

Kennedy, David P; Tucker, Joan S; Green, Harold D; Golinelli, Daniela; Ewing, Brett

2012-10-01

Homeless youth have elevated risk of HIV through sexual behavior. This project investigates the multiple levels of influence on unprotected sex among homeless youth, including social network, individual, and partner level influences. Findings are based on analyses of an exploratory, semi-structured interview (n = 40) and a structured personal network interview (n = 240) with randomly selected homeless youth in Los Angeles. Previous social network studies of risky sex by homeless youth have collected limited social network data from non-random samples and have not distinguished sex partner influences from other network influences. The present analyses have identified significant associations with unprotected sex at multiple levels, including individual, partner, and, to a lesser extent, the social network. Analyses also distinguished between youth who did or did not want to use condoms when they had unprotected sex. Implications for social network based HIV risk interventions with homeless youth are discussed.

Unprotected Sex of Homeless Youth: Results from a Multilevel Analysis of Individual, Social Network, and Relationship Factors

PubMed Central

Kennedy, David P.; Tucker, Joan S.; Green, Harold D.; Golinelli, Daniela; Ewing, Brett

2012-01-01

Homeless youth have elevated risk of HIV through sexual behavior. This project investigates the multiple levels of influence on unprotected sex among homeless youth, including social network, individual, and partner level influences. Findings are based on analyses of an exploratory, semi-structured interview (n=40) and a structured personal network interview (n=240) with randomly selected homeless youth in Los Angeles. Previous social network studies of risky sex by homeless youth have collected limited social network data from non-random samples and have not distinguished sex partner influences from other network influences. The present analyses have identified significant associations with unprotected sex at multiple levels, including individual, partner, and, to a lesser extent, the social network. Analyses also distinguished between youth who wished they used condoms after having unprotected sex and youth who did not regret having unprotected sex. Implications for social network based HIV risk interventions with homeless youth are discussed. PMID:22610421

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Searching Information Sources in Networks

DTIC Science & Technology

2017-06-14

SECURITY CLASSIFICATION OF: During the course of this project, we made significant progresses in multiple directions of the information detection...result on information source detection on non-tree networks; (2) The development of information source localization algorithms to detect multiple... information sources. The algorithms have provable performance guarantees and outperform existing algorithms in 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND

Predicting Final GPA of Graduate School Students: Comparing Artificial Neural Networking and Simultaneous Multiple Regression

ERIC Educational Resources Information Center

Anderson, Joan L.

2006-01-01

Data from graduate student applications at a large Western university were used to determine which factors were the best predictors of success in graduate school, as defined by cumulative graduate grade point average. Two statistical models were employed and compared: artificial neural networking and simultaneous multiple regression. Both models…

The Structure of Informal Social Networks of Persons with Profound Intellectual and Multiple Disabilities

ERIC Educational Resources Information Center

Kamstra, A.; van der Putten, A. A. J.; Vlaskamp, C.

2015-01-01

Background: Persons with less severe disabilities are able to express their needs and show initiatives in social contacts, persons with profound intellectual and multiple disabilities (PIMD), however, depend on others for this. This study analysed the structure of informal networks of persons with PIMD. Materials and Methods: Data concerning the…

Portable control device for networked mobile robots

DOEpatents

Feddema, John T.; Byrne, Raymond H.; Bryan, Jon R.; Harrington, John J.; Gladwell, T. Scott

2002-01-01

A handheld control device provides a way for controlling one or multiple mobile robotic vehicles by incorporating a handheld computer with a radio board. The device and software use a personal data organizer as the handheld computer with an additional microprocessor and communication device on a radio board for use in controlling one robot or multiple networked robots.

Phylogeny and evolutionary histories of Pyrus L. revealed by phylogenetic trees and networks based on data from multiple DNA sequences

USDA-ARS?s Scientific Manuscript database

Reconstructing the phylogeny of Pyrus has been difficult due to the wide distribution of the genus and lack of informative data. In this study, we collected 110 accessions representing 25 Pyrus species and constructed both phylogenetic trees and phylogenetic networks based on multiple DNA sequence d...

Definition and characterization of an extended multiple-demand network.

PubMed

Camilleri, J A; Müller, V I; Fox, P; Laird, A R; Hoffstaedter, F; Kalenscher, T; Eickhoff, S B

2018-01-15

Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands. Copyright © 2017 Elsevier Inc. All rights reserved.

The impact of the metabotropic glutamate receptor and other gene family interaction networks on autism

PubMed Central

Hadley, Dexter; Wu, Zhi-liang; Kao, Charlly; Kini, Akshata; Mohamed-Hadley, Alisha; Thomas, Kelly; Vazquez, Lyam; Qiu, Haijun; Mentch, Frank; Pellegrino, Renata; Kim, Cecilia; Connolly, John; Pinto, Dalila; Merikangas, Alison; Klei, Lambertus; Vorstman, Jacob A.S.; Thompson, Ann; Regan, Regina; Pagnamenta, Alistair T.; Oliveira, Bárbara; Magalhaes, Tiago R.; Gilbert, John; Duketis, Eftichia; De Jonge, Maretha V.; Cuccaro, Michael; Correia, Catarina T.; Conroy, Judith; Conceição, Inês C.; Chiocchetti, Andreas G.; Casey, Jillian P.; Bolshakova, Nadia; Bacchelli, Elena; Anney, Richard; Zwaigenbaum, Lonnie; Wittemeyer, Kerstin; Wallace, Simon; Engeland, Herman van; Soorya, Latha; Rogé, Bernadette; Roberts, Wendy; Poustka, Fritz; Mouga, Susana; Minshew, Nancy; McGrew, Susan G.; Lord, Catherine; Leboyer, Marion; Le Couteur, Ann S.; Kolevzon, Alexander; Jacob, Suma; Guter, Stephen; Green, Jonathan; Green, Andrew; Gillberg, Christopher; Fernandez, Bridget A.; Duque, Frederico; Delorme, Richard; Dawson, Geraldine; Café, Cátia; Brennan, Sean; Bourgeron, Thomas; Bolton, Patrick F.; Bölte, Sven; Bernier, Raphael; Baird, Gillian; Bailey, Anthony J.; Anagnostou, Evdokia; Almeida, Joana; Wijsman, Ellen M.; Vieland, Veronica J.; Vicente, Astrid M.; Schellenberg, Gerard D.; Pericak-Vance, Margaret; Paterson, Andrew D.; Parr, Jeremy R.; Oliveira, Guiomar; Almeida, Joana; Café, Cátia; Mouga, Susana; Correia, Catarina; Nurnberger, John I.; Monaco, Anthony P.; Maestrini, Elena; Klauck, Sabine M.; Hakonarson, Hakon; Haines, Jonathan L.; Geschwind, Daniel H.; Freitag, Christine M.; Folstein, Susan E.; Ennis, Sean; Coon, Hilary; Battaglia, Agatino; Szatmari, Peter; Sutcliffe, James S.; Hallmayer, Joachim; Gill, Michael; Cook, Edwin H.; Buxbaum, Joseph D.; Devlin, Bernie; Gallagher, Louise; Betancur, Catalina; Scherer, Stephen W.; Glessner, Joseph; Hakonarson, Hakon

2014-01-01

Although multiple reports show that defective genetic networks underlie the aetiology of autism, few have translated into pharmacotherapeutic opportunities. Since drugs compete with endogenous small molecules for protein binding, many successful drugs target large gene families with multiple drug binding sites. Here we search for defective gene family interaction networks (GFINs) in 6,742 patients with the ASDs relative to 12,544 neurologically normal controls, to find potentially druggable genetic targets. We find significant enrichment of structural defects (P≤2.40E−09, 1.8-fold enrichment) in the metabotropic glutamate receptor (GRM) GFIN, previously observed to impact attention deficit hyperactivity disorder (ADHD) and schizophrenia. Also, the MXD-MYC-MAX network of genes, previously implicated in cancer, is significantly enriched (P≤3.83E−23, 2.5-fold enrichment), as is the calmodulin 1 (CALM1) gene interaction network (P≤4.16E−04, 14.4-fold enrichment), which regulates voltage-independent calcium-activated action potentials at the neuronal synapse. We find that multiple defective gene family interactions underlie autism, presenting new translational opportunities to explore for therapeutic interventions. PMID:24927284

Implementation of Multiple Host Nodes in Wireless Sensing Node Network System for Landslide Monitoring

NASA Astrophysics Data System (ADS)

Abas, Faizulsalihin bin; Takayama, Shigeru

2015-02-01

This paper proposes multiple host nodes in Wireless Sensing Node Network System (WSNNS) for landslide monitoring. As landslide disasters damage monitoring system easily, one major demand in landslide monitoring is the flexibility and robustness of the system to evaluate the current situation in the monitored area. For various reasons WSNNS can provide an important contribution to reach that aim. In this system, acceleration sensors and GPS are deployed in sensing nodes. Location information by GPS, enable the system to estimate network topology and enable the system to perceive the location in emergency by monitoring the node mode. Acceleration sensors deployment, capacitate this system to detect slow mass movement that can lead to landslide occurrence. Once deployed, sensing nodes self-organize into an autonomous wireless ad hoc network. The measurement parameter data from sensing nodes is transmitted to Host System via host node and "Cloud" System. The implementation of multiple host nodes in Local Sensing Node Network System (LSNNS), improve risk- management of the WSNNS for real-time monitoring of landslide disaster.

The Impact of Drug Use in Social Networks of Patients with Substance Use and Bipolar Disorders

PubMed Central

McDonald, Leah J.; Griffin, Margaret L.; Kolodziej, Monika E.; Fitzmaurice, Garrett M.; Weiss, Roger D.

2011-01-01

In this exploratory analysis, we assessed the effect of drug use among social network members on recovery from drug dependence in patients with co-occurring bipolar disorder. Patients (n=57) enrolled in a group therapy study completed assessments over 15 months. Patients with 0–1 drug users in their social networks at intake had few days of drug use during treatment and follow-up, whereas those with ≥ 2 drug users had significantly more days of drug use. Multivariate analysis showed that patients who consistently named multiple drug users in their social networks had a marked increase in drug use over 15 months, while those who never or occasionally named multiple drug users had a small decline in drug use over time. Multiple drug users in social networks of treatment-seeking drug dependent patients with co-occurring bipolar disorder may indicate poor drug use outcomes; efforts to reduce the association with drug users may be useful. This clinical trial has been registered in a public trials registry at clinicaltrials.gov (identifier is NCT00227838). PMID:21314751

Neural Correlates of Alerting and Orienting Impairment in Multiple Sclerosis Patients

PubMed Central

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J.; Hidalgo-Muñoz, Antonio R.; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

Background A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. Results After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Conclusions Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients. PMID:24820333

Neural correlates of alerting and orienting impairment in multiple sclerosis patients.

PubMed

Vázquez-Marrufo, Manuel; Galvao-Carmona, Alejandro; González-Rosa, Javier J; Hidalgo-Muñoz, Antonio R; Borges, Mónica; Ruiz-Peña, Juan Luis; Izquierdo, Guillermo

2014-01-01

A considerable percentage of multiple sclerosis patients have attentional impairment, but understanding its neurophysiological basis remains a challenge. The Attention Network Test allows 3 attentional networks to be studied. Previous behavioural studies using this test have shown that the alerting network is impaired in multiple sclerosis. The aim of this study was to identify neurophysiological indexes of the attention impairment in relapsing-remitting multiple sclerosis patients using this test. After general slowing had been removed in patients group to isolate the effects of each condition, some behavioral differences between them were obtained. About Contingent Negative Variation, a statistically significant decrement were found in the amplitude for Central and Spatial Cue Conditions for patient group (p<0.05). ANOVAs showed for the patient group a significant latency delay for P1 and N1 components (p<0.05) and a decrease of P3 amplitude for congruent and incongruent stimuli (p<0.01). With regard to correlation analysis, PASAT-3s and SDMT showed significant correlations with behavioral measures of the Attention Network Test (p<0.01) and an ERP parameter (CNV amplitude). Behavioral data are highly correlated with the neuropsychological scores and show that the alerting and orienting mechanisms in the patient group were impaired. Reduced amplitude for the Contingent Negative Variation in the patient group suggests that this component could be a physiological marker related to the alerting and orienting impairment in relapsing-remitting multiple sclerosis. P1 and N1 delayed latencies are evidence of the demyelination process that causes impairment in the first steps of the visual sensory processing. Lastly, P3 amplitude shows a general decrease for the pathological group probably indexing a more central impairment. These results suggest that the Attention Network Test give evidence of multiple levels of attention impairment, which could help in the assessment and treatment of relapsing-remitting multiple sclerosis patients.

A performance analysis of DS-CDMA and SCPC VSAT networks

NASA Technical Reports Server (NTRS)

Hayes, David P.; Ha, Tri T.

1990-01-01

Spread-spectrum and single-channel-per-carrier (SCPC) transmission techniques work well in very small aperture terminal (VSAT) networks for multiple-access purposes while allowing the earth station antennas to remain small. Direct-sequence code-division multiple-access (DS-CDMA) is the simplest spread-spectrum technique to use in a VSAT network since a frequency synthesizer is not required for each terminal. An examination is made of the DS-CDMA and SCPC Ku-band VSAT satellite systems for low-density (64-kb/s or less) communications. A method for improving the standardf link analysis of DS-CDMA satellite-switched networks by including certain losses is developed. The performance of 50-channel full mesh and star network architectures is analyzed. The selection of operating conditions producing optimum performance is demonstrated.

Monitoring of physiological parameters from multiple patients using wireless sensor network.

PubMed

Yuce, Mehmet R; Ng, Peng Choong; Khan, Jamil Y

2008-10-01

This paper presents a wireless sensor network system that has the capability to monitor physiological parameters from multiple patient bodies. The system uses the Medical Implant Communication Service band between the sensor nodes and a remote central control unit (CCU) that behaves as a base station. The CCU communicates with another network standard (the internet or a mobile network) for a long distance data transfer. The proposed system offers mobility to patients and flexibility to medical staff to obtain patient's physiological data on demand basis via Internet. A prototype sensor network including hardware, firmware and software designs has been implemented and tested. The developed system has been optimized for power consumption by having the nodes sleep when there is no communication via a bidirectional communication.

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

Fiber-Optic Distribution Of Pulsed Power To Multiple Sensors

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1996-01-01

Optoelectronic systems designed according to time-sharing scheme distribute optical power to multiple integrated-circuit-based sensors in fiber-optic networks. Networks combine flexibility of electronic sensing circuits with advantage of electrical isolation afforded by use of optical fibers instead of electrical conductors to transmit both signals and power. Fiber optics resist corrosion and immune to electromagnetic interference. Sensor networks of this type useful in variety of applications; for example, in monitoring strains in aircraft, buildings, and bridges, and in monitoring and controlling shapes of flexible structures.

Computational multiple steady states for enzymatic esterification of ethanol and oleic acid in an isothermal CSTR.

PubMed

Ho, Pang-Yen; Chuang, Guo-Syong; Chao, An-Chong; Li, Hsing-Ya

2005-05-01

The capacity of complex biochemical reaction networks (consisting of 11 coupled non-linear ordinary differential equations) to show multiple steady states, was investigated. The system involved esterification of ethanol and oleic acid by lipase in an isothermal continuous stirred tank reactor (CSTR). The Deficiency One Algorithm and the Subnetwork Analysis were applied to determine the steady state multiplicity. A set of rate constants and two corresponding steady states are computed. The phenomena of bistability, hysteresis and bifurcation are discussed. Moreover, the capacity of steady state multiplicity is extended to the family of the studied reaction networks.

Family Matters: Gender, Networks, and Entrepreneurial Outcomes.

ERIC Educational Resources Information Center

Renzulli, Linda A.; Aldrich, Howard; Moody, James

2000-01-01

Examines the association between men's and women's social capital and their likelihood of starting a business. Suggests that heterogeneous social networks provide greater access to multiple sources of information. Women had a greater proportion of kin and greater homogeneity in their networks, but it was network characteristics rather than gender…

Group-multicast capable optical virtual private ring with contention avoidance

NASA Astrophysics Data System (ADS)

Peng, Yunfeng; Du, Shu; Long, Keping

2008-11-01

A ring based optical virtual private network (OVPN) employing contention sensing and avoidance is proposed to deliver multiple-to-multiple group-multicast traffic. The network architecture is presented and its operation principles as well as performance are investigated. The main contribution of this article is the presentation of an innovative group-multicast capable OVPN architecture with technologies available today.

Stability and Change in Sustainability of Daily Routines and Social Networks in Families of Children with Profound Intellectual and Multiple Disabilities

ERIC Educational Resources Information Center

Wilder, Jenny; Granlund, Mats

2015-01-01

Background: Children with profound intellectual and multiple disabilities (PIMD) demand intense family accommodations from birth and onwards. This study used an exploratory and qualitative study design to investigate stability and change in sustainability of daily routines and social networks of Swedish families of children with PIMD. Materials…

The Effects of Cognitive Jamming on Wireless Sensor Networks Used for Geolocation

DTIC Science & Technology

2012-03-01

continuously sends out random bits to the channel without following any MAC-layer etiquette [31]. Normally, the underlying MAC protocol allows...23 UDP User Datagram Protocol . . . . . . . . . . . . . . . . . . . 30 MIMO Multiple Input Multiple Output . . . . . . . . . . . . . . . 70...information is packaged and distributed on the network layer, only the physical measurements are considered. This protocol is used to detect faulty nodes

Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters.

PubMed

Wang, Dandan; Zong, Qun; Tian, Bailing; Shao, Shikai; Zhang, Xiuyun; Zhao, Xinyi

2018-02-01

The distributed finite-time formation tracking control problem for multiple unmanned helicopters is investigated in this paper. The control object is to maintain the positions of follower helicopters in formation with external interferences. The helicopter model is divided into a second order outer-loop subsystem and a second order inner-loop subsystem based on multiple-time scale features. Using radial basis function neural network (RBFNN) technique, we first propose a novel finite-time multivariable neural network disturbance observer (FMNNDO) to estimate the external disturbance and model uncertainty, where the neural network (NN) approximation errors can be dynamically compensated by adaptive law. Next, based on FMNNDO, a distributed finite-time formation tracking controller and a finite-time attitude tracking controller are designed using the nonsingular fast terminal sliding mode (NFTSM) method. In order to estimate the second derivative of the virtual desired attitude signal, a novel finite-time sliding mode integral filter is designed. Finally, Lyapunov analysis and multiple-time scale principle ensure the realization of control goal in finite-time. The effectiveness of the proposed FMNNDO and controllers are then verified by numerical simulations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content

PubMed Central

Kling, Teresia; Johansson, Patrik; Sanchez, José; Marinescu, Voichita D.; Jörnsten, Rebecka; Nelander, Sven

2015-01-01

Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets. PMID:25953855

Colloid Surface Chemistry Critically Affects Multiple Particle Tracking Measurements of Biomaterials

PubMed Central

Valentine, M. T.; Perlman, Z. E.; Gardel, M. L.; Shin, J. H.; Matsudaira, P.; Mitchison, T. J.; Weitz, D. A.

2004-01-01

Characterization of the properties of complex biomaterials using microrheological techniques has the promise of providing fundamental insights into their biomechanical functions; however, precise interpretations of such measurements are hindered by inadequate characterization of the interactions between tracers and the networks they probe. We here show that colloid surface chemistry can profoundly affect multiple particle tracking measurements of networks of fibrin, entangled F-actin solutions, and networks of cross-linked F-actin. We present a simple protocol to render the surface of colloidal probe particles protein-resistant by grafting short amine-terminated methoxy-poly(ethylene glycol) to the surface of carboxylated microspheres. We demonstrate that these poly(ethylene glycol)-coated tracers adsorb significantly less protein than particles coated with bovine serum albumin or unmodified probe particles. We establish that varying particle surface chemistry selectively tunes the sensitivity of the particles to different physical properties of their microenvironments. Specifically, particles that are weakly bound to a heterogeneous network are sensitive to changes in network stiffness, whereas protein-resistant tracers measure changes in the viscosity of the fluid and in the network microstructure. We demonstrate experimentally that two-particle microrheology analysis significantly reduces differences arising from tracer surface chemistry, indicating that modifications of network properties near the particle do not introduce large-scale heterogeneities. Our results establish that controlling colloid-protein interactions is crucial to the successful application of multiple particle tracking techniques to reconstituted protein networks, cytoplasm, and cells. PMID:15189896

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

PubMed

Hardy, N F; Buonomano, Dean V

2018-02-01

Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

Using large-scale Granger causality to study changes in brain network properties in the Clinically Isolated Syndrome (CIS) stage of multiple sclerosis

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Chockanathan, Udaysankar; DSouza, Adora M.; Inglese, Matilde; Wismüller, Axel

2017-03-01

Clinically Isolated Syndrome (CIS) is often considered to be the first neurological episode associated with Multiple sclerosis (MS). At an early stage the inflammatory demyelination occurring in the CNS can manifest as a change in neuronal metabolism, with multiple asymptomatic white matter lesions detected in clinical MRI. Such damage may induce topological changes of brain networks, which can be captured by advanced functional MRI (fMRI) analysis techniques. We test this hypothesis by capturing the effective relationships of 90 brain regions, defined in the Automated Anatomic Labeling (AAL) atlas, using a large-scale Granger Causality (lsGC) framework. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We study for differences in these properties in network graphs obtained for 18 subjects (10 male and 8 female, 9 with CIS and 9 healthy controls). Global network properties captured trending differences with modularity and clustering coefficient (p<0.1). Additionally, local network properties, such as local efficiency and the strength of connections, captured statistically significant (p<0.01) differences in some regions of the inferior frontal and parietal lobe. We conclude that multivariate analysis of fMRI time-series can reveal interesting information about changes occurring in the brain in early stages of MS.

Sparse representation of whole-brain fMRI signals for identification of functional networks.

PubMed

Lv, Jinglei; Jiang, Xi; Li, Xiang; Zhu, Dajiang; Chen, Hanbo; Zhang, Tuo; Zhang, Shu; Hu, Xintao; Han, Junwei; Huang, Heng; Zhang, Jing; Guo, Lei; Liu, Tianming

2015-02-01

There have been several recent studies that used sparse representation for fMRI signal analysis and activation detection based on the assumption that each voxel's fMRI signal is linearly composed of sparse components. Previous studies have employed sparse coding to model functional networks in various modalities and scales. These prior contributions inspired the exploration of whether/how sparse representation can be used to identify functional networks in a voxel-wise way and on the whole brain scale. This paper presents a novel, alternative methodology of identifying multiple functional networks via sparse representation of whole-brain task-based fMRI signals. Our basic idea is that all fMRI signals within the whole brain of one subject are aggregated into a big data matrix, which is then factorized into an over-complete dictionary basis matrix and a reference weight matrix via an effective online dictionary learning algorithm. Our extensive experimental results have shown that this novel methodology can uncover multiple functional networks that can be well characterized and interpreted in spatial, temporal and frequency domains based on current brain science knowledge. Importantly, these well-characterized functional network components are quite reproducible in different brains. In general, our methods offer a novel, effective and unified solution to multiple fMRI data analysis tasks including activation detection, de-activation detection, and functional network identification. Copyright © 2014 Elsevier B.V. All rights reserved.

Bayesian Networks Improve Causal Environmental Assessments for Evidence-Based Policy.

PubMed

Carriger, John F; Barron, Mace G; Newman, Michael C

2016-12-20

Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on valued ecological resources. These aspects are demonstrated through hypothetical problem scenarios that explore some major benefits of using Bayesian networks for reasoning and making inferences in evidence-based policy.

Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

PubMed

Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

2014-12-01

Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

(abstract) Experimental Results From Internetworking Data Applications Over Various Wireless Networks Using a Single Flexible Error Control Protocol

NASA Technical Reports Server (NTRS)

Kanai, T.; Kramer, M.; McAuley, A. J.; Nowack, S.; Pinck, D. S.; Ramirez, G.; Stewart, I.; Tohme, H.; Tong, L.

1995-01-01

This paper describes results from several wireless field trials in New Jersey, California, and Colorado, conducted jointly by researchers at Bellcore, JPL, and US West over the course of 1993 and 1994. During these trials, applications communicated over multiple wireless networks including satellite, low power PCS, high power cellular, packet data, and the wireline Public Switched Telecommunications Network (PSTN). Key goals included 1) designing data applications and an API suited to mobile users, 2) investigating internetworking issues, 3) characterizing wireless networks under various field conditions, and 4) comparing the performance of different protocol mechanisms over the diverse networks and applications. We describe experimental results for different protocol mechanisms and parameters, such as acknowledgment schemes and packet sizes. We show the need for powerful error control mechanisms such as selective acknowledgements and combining data from multiple transmissions. We highlight the possibility of a common protocol for all wireless networks, from micro-cellular PCS to satellite networks.

Hyperconnective and hypoconnective cortical and subcortical functional networks in multiple system atrophy.

PubMed

Rosskopf, Johannes; Gorges, Martin; Müller, Hans-Peter; Pinkhardt, Elmar H; Ludolph, Albert C; Kassubek, Jan

2018-04-01

In multiple system atrophy (MSA), the organization of the functional brain connectivity within cortical and subcortical networks and its clinical correlates remains to be investigated. Whole-brain based 'resting-state' fMRI data were obtained from 22 MSA patients (11 MSA-C, 11 MSA-P) and 22 matched healthy controls, together with standardized clinical assessment and video-oculographic recordings (EyeLink ® ). MSA patients vs. controls showed significantly higher ponto-cerebellar functional connectivity and lower default mode network connectivity (p < .05, corrected). No differences were observed in the motor network and in the control network. The higher the ponto-cerebellar network functional connectivity was, the more pronounced was smooth pursuit impairment. This functional connectivity analysis supports a network-dependent combination of hyper- and hypoconnectivity states in MSA, in agreement with adaptive compensatory responses (hyperconnectivity) and a function disconnection syndrome (hypoconnectivity) that may occur in a consecutive sequence. Copyright © 2018 Elsevier Ltd. All rights reserved.

Computationally Efficient Nonlinear Bell Inequalities for Quantum Networks

NASA Astrophysics Data System (ADS)

Luo, Ming-Xing

2018-04-01

The correlations in quantum networks have attracted strong interest with new types of violations of the locality. The standard Bell inequalities cannot characterize the multipartite correlations that are generated by multiple sources. The main problem is that no computationally efficient method is available for constructing useful Bell inequalities for general quantum networks. In this work, we show a significant improvement by presenting new, explicit Bell-type inequalities for general networks including cyclic networks. These nonlinear inequalities are related to the matching problem of an equivalent unweighted bipartite graph that allows constructing a polynomial-time algorithm. For the quantum resources consisting of bipartite entangled pure states and generalized Greenberger-Horne-Zeilinger (GHZ) states, we prove the generic nonmultilocality of quantum networks with multiple independent observers using new Bell inequalities. The violations are maximal with respect to the presented Tsirelson's bound for Einstein-Podolsky-Rosen states and GHZ states. Moreover, these violations hold for Werner states or some general noisy states. Our results suggest that the presented Bell inequalities can be used to characterize experimental quantum networks.

A Compartmentalized Out-of-Equilibrium Enzymatic Reaction Network for Sustained Autonomous Movement

PubMed Central

2016-01-01

Every living cell is a compartmentalized out-of-equilibrium system exquisitely able to convert chemical energy into function. In order to maintain homeostasis, the flux of metabolites is tightly controlled by regulatory enzymatic networks. A crucial prerequisite for the development of lifelike materials is the construction of synthetic systems with compartmentalized reaction networks that maintain out-of-equilibrium function. Here, we aim for autonomous movement as an example of the conversion of feedstock molecules into function. The flux of the conversion is regulated by a rationally designed enzymatic reaction network with multiple feedforward loops. By compartmentalizing the network into bowl-shaped nanocapsules the output of the network is harvested as kinetic energy. The entire system shows sustained and tunable microscopic motion resulting from the conversion of multiple external substrates. The successful compartmentalization of an out-of-equilibrium reaction network is a major first step in harnessing the design principles of life for construction of adaptive and internally regulated lifelike systems. PMID:27924313

Dynamic Neural Networks Supporting Memory Retrieval

PubMed Central

St. Jacques, Peggy L.; Kragel, Philip A.; Rubin, David C.

2011-01-01

How do separate neural networks interact to support complex cognitive processes such as remembrance of the personal past? Autobiographical memory (AM) retrieval recruits a consistent pattern of activation that potentially comprises multiple neural networks. However, it is unclear how such large-scale neural networks interact and are modulated by properties of the memory retrieval process. In the present functional MRI (fMRI) study, we combined independent component analysis (ICA) and dynamic causal modeling (DCM) to understand the neural networks supporting AM retrieval. ICA revealed four task-related components consistent with the previous literature: 1) Medial Prefrontal Cortex (PFC) Network, associated with self-referential processes, 2) Medial Temporal Lobe (MTL) Network, associated with memory, 3) Frontoparietal Network, associated with strategic search, and 4) Cingulooperculum Network, associated with goal maintenance. DCM analysis revealed that the medial PFC network drove activation within the system, consistent with the importance of this network to AM retrieval. Additionally, memory accessibility and recollection uniquely altered connectivity between these neural networks. Recollection modulated the influence of the medial PFC on the MTL network during elaboration, suggesting that greater connectivity among subsystems of the default network supports greater re-experience. In contrast, memory accessibility modulated the influence of frontoparietal and MTL networks on the medial PFC network, suggesting that ease of retrieval involves greater fluency among the multiple networks contributing to AM. These results show the integration between neural networks supporting AM retrieval and the modulation of network connectivity by behavior. PMID:21550407

Trade-off between Multiple Constraints Enables Simultaneous Formation of Modules and Hubs in Neural Systems

PubMed Central

Chen, Yuhan; Wang, Shengjun; Hilgetag, Claus C.; Zhou, Changsong

2013-01-01

The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter , and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of , resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real networks. The discrepancy suggests that there are further relevant factors that are not yet captured here. PMID:23505352

GENE EXPRESSION NETWORKS

EPA Science Inventory

"Gene expression network" is the term used to describe the interplay, simple or complex, between two or more gene products in performing a specific cellular function. Although the delineation of such networks is complicated by the existence of multiple and subtle types of intera...

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Robustness analysis of uncertain dynamical neural networks with multiple time delays.

PubMed

Senan, Sibel

2015-10-01

This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

P³DB 3.0: From plant phosphorylation sites to protein networks.

PubMed

Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.

Effects of the distance among multiple spreaders on the spreading

NASA Astrophysics Data System (ADS)

Hu, Z.-L.; Liu, J.-G.; Yang, G.-Y.; Ren, Z.-M.

2014-04-01

It is very important to investigate the multiple spreaders' effects since the spreading phenomenon is ubiquitous in many complex systems. In this letter, we investigate the effects of the distance among the initial multiple spreaders for regular networks and WS (Watts-Strogatz) small-world networks based on the SIR (Susceptible-Infected-Recovered) model. Assuming the epidemics can spread over the network, the theoretical and experimental results show that for regular networks the larger the distance between spreaders is, the more effective the spreading is. For WS networks, the spreading efficiency will decrease when the distance exceeds a certain value, and a larger connection probability and average degree will result in a smaller distance of the most effective spreading. A better spreading strategy using n spreaders is to choose either the highest k or ks nodes with the condition that there are not any pairs of the n spreaders linked directly (Kitsak M. et al., Nat. Phys., 6 (2010) 888). However, we find that the spreading will be more effective when the distances among the largest-degree spreaders increase. All these results are independent of the network size for the two initial spreaders case. This work may give new insights to explore more effective methods to inhibit the epidemic spreading or increase the information diffusion.

Understanding large multiprotein complexes: applying a multiple allosteric networks model to explain the function of the Mediator transcription complex.

PubMed

Lewis, Brian A

2010-01-15

The regulation of transcription and of many other cellular processes involves large multi-subunit protein complexes. In the context of transcription, it is known that these complexes serve as regulatory platforms that connect activator DNA-binding proteins to a target promoter. However, there is still a lack of understanding regarding the function of these complexes. Why do multi-subunit complexes exist? What is the molecular basis of the function of their constituent subunits, and how are these subunits organized within a complex? What is the reason for physical connections between certain subunits and not others? In this article, I address these issues through a model of network allostery and its application to the eukaryotic RNA polymerase II Mediator transcription complex. The multiple allosteric networks model (MANM) suggests that protein complexes such as Mediator exist not only as physical but also as functional networks of interconnected proteins through which information is transferred from subunit to subunit by the propagation of an allosteric state known as conformational spread. Additionally, there are multiple distinct sub-networks within the Mediator complex that can be defined by their connections to different subunits; these sub-networks have discrete functions that are activated when specific subunits interact with other activator proteins.

A Multi-Objective Partition Method for Marine Sensor Networks Based on Degree of Event Correlation.

PubMed

Huang, Dongmei; Xu, Chenyixuan; Zhao, Danfeng; Song, Wei; He, Qi

2017-09-21

Existing marine sensor networks acquire data from sea areas that are geographically divided, and store the data independently in their affiliated sea area data centers. In the case of marine events across multiple sea areas, the current network structure needs to retrieve data from multiple data centers, and thus severely affects real-time decision making. In this study, in order to provide a fast data retrieval service for a marine sensor network, we use all the marine sensors as the vertices, establish the edge based on marine events, and abstract the marine sensor network as a graph. Then, we construct a multi-objective balanced partition method to partition the abstract graph into multiple regions and store them in the cloud computing platform. This method effectively increases the correlation of the sensors and decreases the retrieval cost. On this basis, an incremental optimization strategy is designed to dynamically optimize existing partitions when new sensors are added into the network. Experimental results show that the proposed method can achieve the optimal layout for distributed storage in the process of disaster data retrieval in the China Sea area, and effectively optimize the result of partitions when new buoys are deployed, which eventually will provide efficient data access service for marine events.

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.

The Face-Processing Network Is Resilient to Focal Resection of Human Visual Cortex

PubMed Central

Jonas, Jacques; Gomez, Jesse; Maillard, Louis; Brissart, Hélène; Hossu, Gabriela; Jacques, Corentin; Loftus, David; Colnat-Coulbois, Sophie; Stigliani, Anthony; Barnett, Michael A.; Grill-Spector, Kalanit; Rossion, Bruno

2016-01-01

Human face perception requires a network of brain regions distributed throughout the occipital and temporal lobes with a right hemisphere advantage. Present theories consider this network as either a processing hierarchy beginning with the inferior occipital gyrus (occipital face area; IOG-faces/OFA) or a multiple-route network with nonhierarchical components. The former predicts that removing IOG-faces/OFA will detrimentally affect downstream stages, whereas the latter does not. We tested this prediction in a human patient (Patient S.P.) requiring removal of the right inferior occipital cortex, including IOG-faces/OFA. We acquired multiple fMRI measurements in Patient S.P. before and after a preplanned surgery and multiple measurements in typical controls, enabling both within-subject/across-session comparisons (Patient S.P. before resection vs Patient S.P. after resection) and between-subject/across-session comparisons (Patient S.P. vs controls). We found that the spatial topology and selectivity of downstream ipsilateral face-selective regions were stable 1 and 8 month(s) after surgery. Additionally, the reliability of distributed patterns of face selectivity in Patient S.P. before versus after resection was not different from across-session reliability in controls. Nevertheless, postoperatively, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1 of the resected hemisphere. Diffusion weighted imaging in Patient S.P. and controls identifies white matter tracts connecting retinotopic areas to downstream face-selective regions, which may contribute to the stable and plastic features of the face network in Patient S.P. after surgery. Together, our results support a multiple-route network of face processing with nonhierarchical components and shed light on stable and plastic features of high-level visual cortex following focal brain damage. SIGNIFICANCE STATEMENT Brain networks consist of interconnected functional regions commonly organized in processing hierarchies. Prevailing theories predict that damage to the input of the hierarchy will detrimentally affect later stages. We tested this prediction with multiple brain measurements in a rare human patient requiring surgical removal of the putative input to a network processing faces. Surprisingly, the spatial topology and selectivity of downstream face-selective regions are stable after surgery. Nevertheless, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1. White matter connections from outside the face network may support these stable and plastic features. As processing hierarchies are ubiquitous in biological and nonbiological systems, our results have pervasive implications for understanding the construction of resilient networks. PMID:27511014

Online Activities, Digital Media Literacy, and Networked Individualism of Korean Youth

ERIC Educational Resources Information Center

Park, Sora; Kim, Eun-mee; Na, Eun-Yeong

2015-01-01

Networked individualism enables Internet users to connect and socialize via their loose and transient multiple networks, whereas digital media literacy is a precondition of effective Internet use. In this study, an attempt has been made to find the link between networked individualism, digital media literacy, and young people's perception of their…

Distributing stand inventory data and maps over a wide area network

Treesearch

Thomas E. Burk

2000-01-01

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

A parallel implementation of the network identification by multiple regression (NIR) algorithm to reverse-engineer regulatory gene networks.

PubMed

Gregoretti, Francesco; Belcastro, Vincenzo; di Bernardo, Diego; Oliva, Gennaro

2010-04-21

The reverse engineering of gene regulatory networks using gene expression profile data has become crucial to gain novel biological knowledge. Large amounts of data that need to be analyzed are currently being produced due to advances in microarray technologies. Using current reverse engineering algorithms to analyze large data sets can be very computational-intensive. These emerging computational requirements can be met using parallel computing techniques. It has been shown that the Network Identification by multiple Regression (NIR) algorithm performs better than the other ready-to-use reverse engineering software. However it cannot be used with large networks with thousands of nodes--as is the case in biological networks--due to the high time and space complexity. In this work we overcome this limitation by designing and developing a parallel version of the NIR algorithm. The new implementation of the algorithm reaches a very good accuracy even for large gene networks, improving our understanding of the gene regulatory networks that is crucial for a wide range of biomedical applications.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Alignment and integration of complex networks by hypergraph-based spectral clustering

NASA Astrophysics Data System (ADS)

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

Alignment and integration of complex networks by hypergraph-based spectral clustering.

PubMed

Michoel, Tom; Nachtergaele, Bruno

2012-11-01

Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

NASA Technical Reports Server (NTRS)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI < 1.0) with varying soil reflectance backgrounds is particularly difficult. Standard multiple regression methods applied to canopies within a single homogeneous soil type yield good results but perform unacceptably when applied across soil boundaries, resulting in absolute percentage errors of >1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Functional Specialization and Flexibility in Human Association Cortex

PubMed Central

Yeo, B. T. Thomas; Krienen, Fenna M.; Eickhoff, Simon B.; Yaakub, Siti N.; Fox, Peter T.; Buckner, Randy L.; Asplund, Christopher L.; Chee, Michael W.L.

2015-01-01

The association cortex supports cognitive functions enabling flexible behavior. Here, we explored the organization of human association cortex by mathematically formalizing the notion that a behavioral task engages multiple cognitive components, which are in turn supported by multiple overlapping brain regions. Application of the model to a large data set of neuroimaging experiments (N = 10 449) identified complex zones of frontal and parietal regions that ranged from being highly specialized to highly flexible. The network organization of the specialized and flexible regions was explored with an independent resting-state fMRI data set (N = 1000). Cortical regions specialized for the same components were strongly coupled, suggesting that components function as partially isolated networks. Functionally flexible regions participated in multiple components to different degrees. This heterogeneous selectivity was predicted by the connectivity between flexible and specialized regions. Functionally flexible regions might support binding or integrating specialized brain networks that, in turn, contribute to the ability to execute multiple and varied tasks. PMID:25249407

The Device Centric Communication System for 5G Networks

NASA Astrophysics Data System (ADS)

Biswash, S. K.; Jayakody, D. N. K.

2017-01-01

The Fifth Generation Communication (5G) networks have several functional features such as: Massive Multiple Input and Multiple Output (MIMO), Device centric data and voice support, Smarter-device communications, etc. The objective for 5G networks is to gain the 1000x more throughput, 10x spectral efficiency, 100 x more energy efficiency than existing technologies. The 5G system will provide the balance between the Quality of Experience (QoE) and the Quality of Service (QoS), without compromising the user benefit. The data rate has been the key metric for wireless QoS; QoE deals with the delay and throughput. In order to realize a balance between the QoS and QoE, we propose a cellular Device centric communication methodology for the overlapping network coverage area in the 5G communication system. The multiple beacon signals mobile tower refers to an overlapping network area, and a user must be forwarded to the next location area. To resolve this issue, we suggest the user centric methodology (without Base Station interface) to handover the device in the next area, until the users finalize the communication. The proposed method will reduce the signalling cost and overheads for the communication.

Principal network analysis: identification of subnetworks representing major dynamics using gene expression data

PubMed Central

Kim, Yongsoo; Kim, Taek-Kyun; Kim, Yungu; Yoo, Jiho; You, Sungyong; Lee, Inyoul; Carlson, George; Hood, Leroy; Choi, Seungjin; Hwang, Daehee

2011-01-01

Motivation: Systems biology attempts to describe complex systems behaviors in terms of dynamic operations of biological networks. However, there is lack of tools that can effectively decode complex network dynamics over multiple conditions. Results: We present principal network analysis (PNA) that can automatically capture major dynamic activation patterns over multiple conditions and then generate protein and metabolic subnetworks for the captured patterns. We first demonstrated the utility of this method by applying it to a synthetic dataset. The results showed that PNA correctly captured the subnetworks representing dynamics in the data. We further applied PNA to two time-course gene expression profiles collected from (i) MCF7 cells after treatments of HRG at multiple doses and (ii) brain samples of four strains of mice infected with two prion strains. The resulting subnetworks and their interactions revealed network dynamics associated with HRG dose-dependent regulation of cell proliferation and differentiation and early PrPSc accumulation during prion infection. Availability: The web-based software is available at: http://sbm.postech.ac.kr/pna. Contact: dhhwang@postech.ac.kr; seungjin@postech.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21193522

An Enriched Unified Medical Language System Semantic Network with a Multiple Subsumption Hierarchy

PubMed Central

Zhang, Li; Perl, Yehoshua; Halper, Michael; Geller, James; Cimino, James J.

2004-01-01

Objective: The Unified Medical Language System's (UMLS's) Semantic Network's (SN's) two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. In this article, the SN is expanded into a multiple subsumption structure with a directed acyclic graph (DAG) IS-A hierarchy, allowing a semantic type to have multiple parents. New viable IS-A links are added as warranted. Design: Two methodologies are presented to identify and add new viable IS-A links. The first methodology is based on imposing the characteristic of connectivity on a previously presented partition of the SN. Four transformations are provided to find viable IS-A links in the process of converting the partition's disconnected groups into connected ones. The second methodology identifies new IS-A links through a string matching process involving names and definitions of various semantic types in the SN. A domain expert is needed to review all the results to determine the validity of the new IS-A links. Results: Nineteen new IS-A links are added to the SN, and four new semantic types are also created to support the multiple subsumption framework. The resulting network, called the Enriched Semantic Network (ESN), exhibits a DAG-structured hierarchy. A partition of the ESN containing 19 connected groups is also derived. Conclusion: The ESN is an expanded abstraction of the UMLS compared with the original SN. Its multiple subsumption hierarchy can accommodate semantic types with multiple parents. Its representation thus provides direct access to a broader range of subsumption knowledge. PMID:14764611

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Altered intra- and inter-network functional coupling of resting-state networks associated with motor dysfunction in stroke.

PubMed

Zhao, Zhiyong; Wu, Jie; Fan, Mingxia; Yin, Dazhi; Tang, Chaozheng; Gong, Jiayu; Xu, Guojun; Gao, Xinjie; Yu, Qiurong; Yang, Hao; Sun, Limin; Jia, Jie

2018-04-24

Motor functions are supported through functional integration across the extended motor system network. Individuals following stroke often show deficits on motor performance requiring coordination of multiple brain networks; however, the assessment of connectivity patterns after stroke was still unclear. This study aimed to investigate the changes in intra- and inter-network functional connectivity (FC) of multiple networks following stroke and further correlate FC with motor performance. Thirty-three left subcortical chronic stroke patients and 34 healthy controls underwent resting-state functional magnetic resonance imaging. Eleven resting-state networks were identified via independent component analysis (ICA). Compared with healthy controls, the stroke group showed abnormal FC within the motor network (MN), visual network (VN), dorsal attention network (DAN), and executive control network (ECN). Additionally, the FC values of the ipsilesional inferior parietal lobule (IPL) within the ECN were negatively correlated with the Fugl-Meyer Assessment (FMA) scores (hand + wrist). With respect to inter-network interactions, the ipsilesional frontoparietal network (FPN) decreased FC with the MN and DAN; the contralesional FPN decreased FC with the ECN, but it increased FC with the default mode network (DMN); and the posterior DMN decreased FC with the VN. In sum, this study demonstrated the coexistence of intra- and inter-network alterations associated with motor-visual attention and high-order cognitive control function in chronic stroke, which might provide insights into brain network plasticity following stroke. © 2018 Wiley Periodicals, Inc.

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

MAGGnet: An international network to foster mitigation of agricultural greenhouse gases

USDA-ARS?s Scientific Manuscript database

Research networks provide a framework for review, synthesis, and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a greenhouse gas (GHG) research network referred to as MAGGnet (Managing Agricultural Greenhouse ...

Global interrupt and barrier networks

DOEpatents

Blumrich, Matthias A.; Chen, Dong; Coteus, Paul W.; Gara, Alan G.; Giampapa, Mark E; Heidelberger, Philip; Kopcsay, Gerard V.; Steinmacher-Burow, Burkhard D.; Takken, Todd E.

2008-10-28

A system and method for generating global asynchronous signals in a computing structure. Particularly, a global interrupt and barrier network is implemented that implements logic for generating global interrupt and barrier signals for controlling global asynchronous operations performed by processing elements at selected processing nodes of a computing structure in accordance with a processing algorithm; and includes the physical interconnecting of the processing nodes for communicating the global interrupt and barrier signals to the elements via low-latency paths. The global asynchronous signals respectively initiate interrupt and barrier operations at the processing nodes at times selected for optimizing performance of the processing algorithms. In one embodiment, the global interrupt and barrier network is implemented in a scalable, massively parallel supercomputing device structure comprising a plurality of processing nodes interconnected by multiple independent networks, with each node including one or more processing elements for performing computation or communication activity as required when performing parallel algorithm operations. One multiple independent network includes a global tree network for enabling high-speed global tree communications among global tree network nodes or sub-trees thereof. The global interrupt and barrier network may operate in parallel with the global tree network for providing global asynchronous sideband signals.

Naming Game on Networks: Let Everyone be Both Speaker and Hearer

PubMed Central

Gao, Yuan; Chen, Guanrong; Chan, Rosa H. M.

2014-01-01

To investigate how consensus is reached on a large self-organized peer-to-peer network, we extended the naming game model commonly used in language and communication to Naming Game in Groups (NGG). Differing from other existing naming game models, in NGG everyone in the population (network) can be both speaker and hearer simultaneously, which resembles in a closer manner to real-life scenarios. Moreover, NGG allows the transmission (communication) of multiple words (opinions) for multiple intra-group consensuses. The communications among indirectly-connected nodes are also enabled in NGG. We simulated and analyzed the consensus process in some typical network topologies, including random-graph networks, small-world networks and scale-free networks, to better understand how global convergence (consensus) could be reached on one common word. The results are interpreted on group negotiation of a peer-to-peer network, which shows that global consensus in the population can be reached more rapidly when more opinions are permitted within each group or when the negotiating groups in the population are larger in size. The novel features and properties introduced by our model have demonstrated its applicability in better investigating general consensus problems on peer-to-peer networks. PMID:25143140

Distributed effects of methylphenidate on the network structure of the resting brain: a connectomic pattern classification analysis.

PubMed

Sripada, Chandra Sekhar; Kessler, Daniel; Welsh, Robert; Angstadt, Michael; Liberzon, Israel; Phan, K Luan; Scott, Clayton

2013-11-01

Methylphenidate is a psychostimulant medication that produces improvements in functions associated with multiple neurocognitive systems. To investigate the potentially distributed effects of methylphenidate on the brain's intrinsic network architecture, we coupled resting state imaging with multivariate pattern classification. In a within-subject, double-blind, placebo-controlled, randomized, counterbalanced, cross-over design, 32 healthy human volunteers received either methylphenidate or placebo prior to two fMRI resting state scans separated by approximately one week. Resting state connectomes were generated by placing regions of interest at regular intervals throughout the brain, and these connectomes were submitted for support vector machine analysis. We found that methylphenidate produces a distributed, reliably detected, multivariate neural signature. Methylphenidate effects were evident across multiple resting state networks, especially visual, somatomotor, and default networks. Methylphenidate reduced coupling within visual and somatomotor networks. In addition, default network exhibited decoupling with several task positive networks, consistent with methylphenidate modulation of the competitive relationship between these networks. These results suggest that connectivity changes within and between large-scale networks are potentially involved in the mechanisms by which methylphenidate improves attention functioning. Copyright © 2013 Elsevier Inc. All rights reserved.

Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

PubMed

Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

2016-11-30

Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

Naming Game on Networks: Let Everyone be Both Speaker and Hearer

NASA Astrophysics Data System (ADS)

Gao, Yuan; Chen, Guanrong; Chan, Rosa H. M.

2014-08-01

To investigate how consensus is reached on a large self-organized peer-to-peer network, we extended the naming game model commonly used in language and communication to Naming Game in Groups (NGG). Differing from other existing naming game models, in NGG everyone in the population (network) can be both speaker and hearer simultaneously, which resembles in a closer manner to real-life scenarios. Moreover, NGG allows the transmission (communication) of multiple words (opinions) for multiple intra-group consensuses. The communications among indirectly-connected nodes are also enabled in NGG. We simulated and analyzed the consensus process in some typical network topologies, including random-graph networks, small-world networks and scale-free networks, to better understand how global convergence (consensus) could be reached on one common word. The results are interpreted on group negotiation of a peer-to-peer network, which shows that global consensus in the population can be reached more rapidly when more opinions are permitted within each group or when the negotiating groups in the population are larger in size. The novel features and properties introduced by our model have demonstrated its applicability in better investigating general consensus problems on peer-to-peer networks.

A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens

PubMed Central

Becich, Michael J.; Bollag, Roni J.; Chavan, Girish; Corrigan, Julia; Dhir, Rajiv; Feldman, Michael D.; Gaudioso, Carmelo; Legowski, Elizabeth; Maihle, Nita J.; Mitchell, Kevin; Murphy, Monica; Sakthivel, Mayur; Tseytlin, Eugene; Weaver, JoEllen

2015-01-01

Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the TIES Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that is de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network. PMID:26670560

An Authentication Protocol for Future Sensor Networks.

PubMed

Bilal, Muhammad; Kang, Shin-Gak

2017-04-28

Authentication is one of the essential security services in Wireless Sensor Networks (WSNs) for ensuring secure data sessions. Sensor node authentication ensures the confidentiality and validity of data collected by the sensor node, whereas user authentication guarantees that only legitimate users can access the sensor data. In a mobile WSN, sensor and user nodes move across the network and exchange data with multiple nodes, thus experiencing the authentication process multiple times. The integration of WSNs with Internet of Things (IoT) brings forth a new kind of WSN architecture along with stricter security requirements; for instance, a sensor node or a user node may need to establish multiple concurrent secure data sessions. With concurrent data sessions, the frequency of the re-authentication process increases in proportion to the number of concurrent connections. Moreover, to establish multiple data sessions, it is essential that a protocol participant have the capability of running multiple instances of the protocol run, which makes the security issue even more challenging. The currently available authentication protocols were designed for the autonomous WSN and do not account for the above requirements. Hence, ensuring a lightweight and efficient authentication protocol has become more crucial. In this paper, we present a novel, lightweight and efficient key exchange and authentication protocol suite called the Secure Mobile Sensor Network (SMSN) Authentication Protocol. In the SMSN a mobile node goes through an initial authentication procedure and receives a re-authentication ticket from the base station. Later a mobile node can use this re-authentication ticket when establishing multiple data exchange sessions and/or when moving across the network. This scheme reduces the communication and computational complexity of the authentication process. We proved the strength of our protocol with rigorous security analysis (including formal analysis using the BAN-logic) and simulated the SMSN and previously proposed schemes in an automated protocol verifier tool. Finally, we compared the computational complexity and communication cost against well-known authentication protocols.

An Authentication Protocol for Future Sensor Networks

PubMed Central

Bilal, Muhammad; Kang, Shin-Gak

2017-01-01

Authentication is one of the essential security services in Wireless Sensor Networks (WSNs) for ensuring secure data sessions. Sensor node authentication ensures the confidentiality and validity of data collected by the sensor node, whereas user authentication guarantees that only legitimate users can access the sensor data. In a mobile WSN, sensor and user nodes move across the network and exchange data with multiple nodes, thus experiencing the authentication process multiple times. The integration of WSNs with Internet of Things (IoT) brings forth a new kind of WSN architecture along with stricter security requirements; for instance, a sensor node or a user node may need to establish multiple concurrent secure data sessions. With concurrent data sessions, the frequency of the re-authentication process increases in proportion to the number of concurrent connections. Moreover, to establish multiple data sessions, it is essential that a protocol participant have the capability of running multiple instances of the protocol run, which makes the security issue even more challenging. The currently available authentication protocols were designed for the autonomous WSN and do not account for the above requirements. Hence, ensuring a lightweight and efficient authentication protocol has become more crucial. In this paper, we present a novel, lightweight and efficient key exchange and authentication protocol suite called the Secure Mobile Sensor Network (SMSN) Authentication Protocol. In the SMSN a mobile node goes through an initial authentication procedure and receives a re-authentication ticket from the base station. Later a mobile node can use this re-authentication ticket when establishing multiple data exchange sessions and/or when moving across the network. This scheme reduces the communication and computational complexity of the authentication process. We proved the strength of our protocol with rigorous security analysis (including formal analysis using the BAN-logic) and simulated the SMSN and previously proposed schemes in an automated protocol verifier tool. Finally, we compared the computational complexity and communication cost against well-known authentication protocols. PMID:28452937

Multiple brain networks for visual self-recognition with different sensitivity for motion and body part.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Miura, Naoki; Akitsuki, Yuko; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2006-10-01

Multiple brain networks may support visual self-recognition. It has been hypothesized that the left ventral occipito-temporal cortex processes one's own face as a symbol, and the right parieto-frontal network processes self-image in association with motion-action contingency. Using functional magnetic resonance imaging, we first tested these hypotheses based on the prediction that these networks preferentially respond to a static self-face and to moving one's whole body, respectively. Brain activation specifically related to self-image during familiarity judgment was compared across four stimulus conditions comprising a two factorial design: factor Motion contrasted picture (Picture) and movie (Movie), and factor Body part a face (Face) and whole body (Body). Second, we attempted to segregate self-specific networks using a principal component analysis (PCA), assuming an independent pattern of inter-subject variability in activation over the four stimulus conditions in each network. The bilateral ventral occipito-temporal and the right parietal and frontal cortices exhibited self-specific activation. The left ventral occipito-temporal cortex exhibited greater self-specific activation for Face than for Body, in Picture, consistent with the prediction for this region. The activation profiles of the right parietal and frontal cortices did not show preference for Movie Body predicted by the assumed roles of these regions. The PCA extracted two cortical networks, one with its peaks in the right posterior, and another in frontal cortices; their possible roles in visuo-spatial and conceptual self-representations, respectively, were suggested by previous findings. The results thus supported and provided evidence of multiple brain networks for visual self-recognition.

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.

Reconfiguration in Robust Distributed Real-Time Systems Based on Global Checkpoints

DTIC Science & Technology

1991-12-01

achieved by utilizing distributed systems in which a single application program executes on multiple processors, connected to a network. The distributed...single application program executes on multiple proces- sors, connected to a network. The distributed nature of such systems make it possible to ...resident at every node. How - ever, the responsibility for execution of a particular function is assigned to only one node in this framework. This function

Performance Analysis on the Coexistence of Multiple Cognitive Radio Networks

DTIC Science & Technology

2015-05-28

the scarce spectrum resources. Cognitive radio is a key in minimizing the spectral congestion through its adaptability, where the radio parameters...static allocation of spectrum results in congestion in some parts of the spectrum and non use in some others, therefore, spectra utilization is...well as the secondary user (SU) activities in multiple CR networks. It is shown that the scheduler provided much needed gain during congestions . However

High speed polling protocol for multiple node network

NASA Technical Reports Server (NTRS)

Kirkham, Harold (Inventor)

1995-01-01

The invention is a multiple interconnected network of intelligent message-repeating remote nodes which employs a remote node polling process performed by a master node by transmitting a polling message generically addressed to all remote nodes associated with the master node. Each remote node responds upon receipt of the generically addressed polling message by transmitting a poll-answering informational message and by relaying the polling message to other adjacent remote nodes.

Space-Time Processing for Tactical Mobile Ad Hoc Networks

DTIC Science & Technology

2007-08-01

rates in mobile ad hoc networks. In addition, he has considered the design of a cross-layer multi-user resource allocation framework using a... framework for many-to-one communication. In this context, multiple nodes cooperate to transmit their packets simultaneously to a single node using multi...spatially multiplexed signals transmitted from multiple nodes. Our goal is to form a framework that activates different sets of communication links

Data collection framework for energy efficient privacy preservation in wireless sensor networks having many-to-many structures.

PubMed

Bahşi, Hayretdin; Levi, Albert

2010-01-01

Wireless sensor networks (WSNs) generally have a many-to-one structure so that event information flows from sensors to a unique sink. In recent WSN applications, many-to-many structures evolved due to the need for conveying collected event information to multiple sinks. Privacy preserved data collection models in the literature do not solve the problems of WSN applications in which network has multiple un-trusted sinks with different level of privacy requirements. This study proposes a data collection framework bases on k-anonymity for preventing record disclosure of collected event information in WSNs. Proposed method takes the anonymity requirements of multiple sinks into consideration by providing different levels of privacy for each destination sink. Attributes, which may identify an event owner, are generalized or encrypted in order to meet the different anonymity requirements of sinks at the same anonymized output. If the same output is formed, it can be multicasted to all sinks. The other trivial solution is to produce different anonymized outputs for each sink and send them to related sinks. Multicasting is an energy efficient data sending alternative for some sensor nodes. Since minimization of energy consumption is an important design criteria for WSNs, multicasting the same event information to multiple sinks reduces the energy consumption of overall network.

Convergence and objective functions of some fault/noise-injection-based online learning algorithms for RBF networks.

PubMed

Ho, Kevin I-J; Leung, Chi-Sing; Sum, John

2010-06-01

In the last two decades, many online fault/noise injection algorithms have been developed to attain a fault tolerant neural network. However, not much theoretical works related to their convergence and objective functions have been reported. This paper studies six common fault/noise-injection-based online learning algorithms for radial basis function (RBF) networks, namely 1) injecting additive input noise, 2) injecting additive/multiplicative weight noise, 3) injecting multiplicative node noise, 4) injecting multiweight fault (random disconnection of weights), 5) injecting multinode fault during training, and 6) weight decay with injecting multinode fault. Based on the Gladyshev theorem, we show that the convergence of these six online algorithms is almost sure. Moreover, their true objective functions being minimized are derived. For injecting additive input noise during training, the objective function is identical to that of the Tikhonov regularizer approach. For injecting additive/multiplicative weight noise during training, the objective function is the simple mean square training error. Thus, injecting additive/multiplicative weight noise during training cannot improve the fault tolerance of an RBF network. Similar to injective additive input noise, the objective functions of other fault/noise-injection-based online algorithms contain a mean square error term and a specialized regularization term.

Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study.

PubMed

Tewarie, Prejaas; Steenwijk, Martijn D; Brookes, Matthew J; Uitdehaag, Bernard M J; Geurts, Jeroen J G; Stam, Cornelis J; Schoonheim, Menno M

2018-06-01

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo-cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Multiple Resting-State Networks Are Associated With Tremors and Cognitive Features in Essential Tremor.

PubMed

Fang, Weidong; Chen, Huiyue; Wang, Hansheng; Zhang, Han; Liu, Mengqi; Puneet, Munankami; Lv, Fajin; Cheng, Oumei; Wang, Xuefeng; Lu, Xiurong; Luo, Tianyou

2015-12-01

The heterogeneous clinical features of essential tremor indicate that the dysfunctions of this syndrome are not confined to motor networks, but extend to nonmotor networks. Currently, these neural network dysfunctions in essential tremor remain unclear. In this study, independent component analysis of resting-state functional MRI was used to study these neural network mechanisms. Thirty-five essential tremor patients and 35 matched healthy controls with clinical and neuropsychological tests were included, and eight resting-state networks were identified. After considering the structure and head-motion factors and testing the reliability of the selected resting-state networks, we assessed the functional connectivity changes within or between resting-state networks. Finally, image-behavior correlation analysis was performed. Compared to healthy controls, essential tremor patients displayed increased functional connectivity in the sensorimotor and salience networks and decreased functional connectivity in the cerebellum network. Additionally, increased functional network connectivity was observed between anterior and posterior default mode networks, and a decreased functional network connectivity was noted between the cerebellum network and the sensorimotor and posterior default mode networks. Importantly, the functional connectivity changes within and between these resting-state networks were correlated with the tremor severity and total cognitive scores of essential tremor patients. The findings of this study provide the first evidence that functional connectivity changes within and between multiple resting-state networks are associated with tremors and cognitive features of essential tremor, and this work demonstrates a potential approach for identifying the underlying neural network mechanisms of this syndrome. © 2015 International Parkinson and Movement Disorder Society.

A feedback control model for network flow with multiple pure time delays

NASA Technical Reports Server (NTRS)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

A sweep algorithm for massively parallel simulation of circuit-switched networks

NASA Technical Reports Server (NTRS)

Gaujal, Bruno; Greenberg, Albert G.; Nicol, David M.

1992-01-01

A new massively parallel algorithm is presented for simulating large asymmetric circuit-switched networks, controlled by a randomized-routing policy that includes trunk-reservation. A single instruction multiple data (SIMD) implementation is described, and corresponding experiments on a 16384 processor MasPar parallel computer are reported. A multiple instruction multiple data (MIMD) implementation is also described, and corresponding experiments on an Intel IPSC/860 parallel computer, using 16 processors, are reported. By exploiting parallelism, our algorithm increases the possible execution rate of such complex simulations by as much as an order of magnitude.

Optical Interconnection Via Computer-Generated Holograms

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang; Zhou, Shaomin

1995-01-01

Method of free-space optical interconnection developed for data-processing applications like parallel optical computing, neural-network computing, and switching in optical communication networks. In method, multiple optical connections between multiple sources of light in one array and multiple photodetectors in another array made via computer-generated holograms in electrically addressed spatial light modulators (ESLMs). Offers potential advantages of massive parallelism, high space-bandwidth product, high time-bandwidth product, low power consumption, low cross talk, and low time skew. Also offers advantage of programmability with flexibility of reconfiguration, including variation of strengths of optical connections in real time.

A systems approach to risk reduction of transportation infrastructure networks subject to multiple hazards : final report, December 31, 2008.

DOT National Transportation Integrated Search

2008-12-31

Integrity, robustness, reliability, and resiliency of infrastructure networks are vital to the economy, : security and well-being of any country. Faced with threats caused by natural and man-made hazards, : transportation infrastructure network manag...

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial. PMID:23563395

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

DOE PAGES

Shen, Yiwen; Hattink, Maarten; Samadi, Payman; ...

2018-04-13

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks

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

Shen, Yiwen; Hattink, Maarten; Samadi, Payman

Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. Here, we present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly networkmore » testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 microsecond control plane latency for data-center and high performance computing platforms.« less

Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

PubMed Central

Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E.; Balázsi, Gábor; Gennaro, Maria Laura

2016-01-01

Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515

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

Rao, Nageswara S; Sen, Satyabrata; Berry, M. L..

Domestic Nuclear Detection Office s (DNDO) Intelligence Radiation Sensors Systems (IRSS) program supported the development of networks of commercial-off-the-shelf (COTS) radiation counters for detecting, localizing, and identifying low-level radiation sources. Under this program, a series of indoor and outdoor tests were conducted with multiple source strengths and types, different background profiles, and various types of source and detector movements. Following the tests, network algorithms were replayed in various re-constructed scenarios using sub-networks. These measurements and algorithm traces together provide a rich collection of highly valuable datasets for testing the current and next generation radiation network algorithms, including the ones (tomore » be) developed by broader R&D communities such as distributed detection, information fusion, and sensor networks. From this multiple TeraByte IRSS database, we distilled out and packaged the first batch of canonical datasets for public release. They include measurements from ten indoor and two outdoor tests which represent increasingly challenging baseline scenarios for robustly testing radiation network algorithms.« less

From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

PubMed

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

Determining geophysical properties from well log data using artificial neural networks and fuzzy inference systems

NASA Astrophysics Data System (ADS)

Chang, Hsien-Cheng

Two novel synergistic systems consisting of artificial neural networks and fuzzy inference systems are developed to determine geophysical properties by using well log data. These systems are employed to improve the determination accuracy in carbonate rocks, which are generally more complex than siliciclastic rocks. One system, consisting of a single adaptive resonance theory (ART) neural network and three fuzzy inference systems (FISs), is used to determine the permeability category. The other system, which is composed of three ART neural networks and a single FIS, is employed to determine the lithofacies. The geophysical properties studied in this research, permeability category and lithofacies, are treated as categorical data. The permeability values are transformed into a "permeability category" to account for the effects of scale differences between core analyses and well logs, and heterogeneity in the carbonate rocks. The ART neural networks dynamically cluster the input data sets into different groups. The FIS is used to incorporate geologic experts' knowledge, which is usually in linguistic forms, into systems. These synergistic systems thus provide viable alternative solutions to overcome the effects of heterogeneity, the uncertainties of carbonate rock depositional environments, and the scarcity of well log data. The results obtained in this research show promising improvements over backpropagation neural networks. For the permeability category, the prediction accuracies are 68.4% and 62.8% for the multiple-single ART neural network-FIS and a single backpropagation neural network, respectively. For lithofacies, the prediction accuracies are 87.6%, 79%, and 62.8% for the single-multiple ART neural network-FIS, a single ART neural network, and a single backpropagation neural network, respectively. The sensitivity analysis results show that the multiple-single ART neural networks-FIS and a single ART neural network possess the same matching trends in determining lithofacies. This research shows that the adaptive resonance theory neural networks enable decision-makers to clearly distinguish the importance of different pieces of data which are useful in three-dimensional subsurface modeling. Geologic experts' knowledge can be easily applied and maintained by using the fuzzy inference systems.

Young Thai women who use methamphetamine: Intersection of sexual partnerships, drug use, and social networks

PubMed Central

German, Danielle; Sherman, Susan A.; Latkin, Carl A.; Sirirojn, Bangorn; Thomson, Nick; Sutcliffe, Catherine G.; Aramrattana, Apinun; Celentano, David D.

2009-01-01

Background Given high rates of methamphetamine (MA) use among young people in Thailand and evidence of an association between MA and increased sexual risk behavior, we examined the association between women’s recent sexual partnerships, social network characteristics and drug and alcohol use. Methods Female participants (n=320) in an HIV behavioral trial among young (18–25 years) MA users in Chiang Mai completed a drug and sexual behavior survey and social network inventory. Multinomial regression analyses accounting for clustered data examined individual and network characteristics associated with recent sexual partnership category. We compared women with only one male partner in the past year (39%) to those with multiple male partners (37%) and those with only female partners (24%). Results Differences in levels of drug and alcohol use and social and sexual network characteristics were dependent on recent sexual partnership profiles. The multiple partner group reported an average of five male partners in the past year; 12% reported consistent condom use in the past 30 days. Compared to both groups, women with multiple male partners used MA more frequently, had larger non-sex networks with more MA users, were more likely to have an MA-using sex partner, and received less emotional support from their partners. Women with multiple male partners and only female partners reported more frequent alcohol use. Conclusions Policy and intervention efforts targeting drug use and sexual behavior among young Thai women are drastically needed and may benefit from consideration of the diversity within the population. These data point to the need for targeted prevention approaches that take into account the varying characteristics and social influences of these different groups of women. PMID:18191393

A feasibility study for long-path multiple detection using a neural network

NASA Technical Reports Server (NTRS)

Feuerbacher, G. A.; Moebes, T. A.

1994-01-01

Least-squares inverse filters have found widespread use in the deconvolution of seismograms and the removal of multiples. The use of least-squares prediction filters with prediction distances greater than unity leads to the method of predictive deconvolution which can be used for the removal of long path multiples. The predictive technique allows one to control the length of the desired output wavelet by control of the predictive distance, and hence to specify the desired degree of resolution. Events which are periodic within given repetition ranges can be attenuated selectively. The method is thus effective in the suppression of rather complex reverberation patterns. A back propagation(BP) neural network is constructed to perform the detection of first arrivals of the multiples and therefore aid in the more accurate determination of the predictive distance of the multiples. The neural detector is applied to synthetic reflection coefficients and synthetic seismic traces. The processing results show that the neural detector is accurate and should lead to an automated fast method for determining predictive distances across vast amounts of data such as seismic field records. The neural network system used in this study was the NASA Software Technology Branch's NETS system.

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.

Detection of multiple perturbations in multi-omics biological networks.

PubMed

Griffin, Paula J; Zhang, Yuqing; Johnson, William Evan; Kolaczyk, Eric D

2018-05-17

Cellular mechanism-of-action is of fundamental concern in many biological studies. It is of particular interest for identifying the cause of disease and learning the way in which treatments act against disease. However, pinpointing such mechanisms is difficult, due to the fact that small perturbations to the cell can have wide-ranging downstream effects. Given a snapshot of cellular activity, it can be challenging to tell where a disturbance originated. The presence of an ever-greater variety of high-throughput biological data offers an opportunity to examine cellular behavior from multiple angles, but also presents the statistical challenge of how to effectively analyze data from multiple sources. In this setting, we propose a method for mechanism-of-action inference by extending network filtering to multi-attribute data. We first estimate a joint Gaussian graphical model across multiple data types using penalized regression and filter for network effects. We then apply a set of likelihood ratio tests to identify the most likely site of the original perturbation. In addition, we propose a conditional testing procedure to allow for detection of multiple perturbations. We demonstrate this methodology on paired gene expression and methylation data from The Cancer Genome Atlas (TCGA). © 2018, The International Biometric Society.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

PubMed

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-10-02

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase.

Adaptive Multi-Node Multiple Input and Multiple Output (MIMO) Transmission for Mobile Wireless Multimedia Sensor Networks

PubMed Central

Cho, Sunghyun; Choi, Ji-Woong; You, Cheolwoo

2013-01-01

Mobile wireless multimedia sensor networks (WMSNs), which consist of mobile sink or sensor nodes and use rich sensing information, require much faster and more reliable wireless links than static wireless sensor networks (WSNs). This paper proposes an adaptive multi-node (MN) multiple input and multiple output (MIMO) transmission to improve the transmission reliability and capacity of mobile sink nodes when they experience spatial correlation. Unlike conventional single-node (SN) MIMO transmission, the proposed scheme considers the use of transmission antennas from more than two sensor nodes. To find an optimal antenna set and a MIMO transmission scheme, a MN MIMO channel model is introduced first, followed by derivation of closed-form ergodic capacity expressions with different MIMO transmission schemes, such as space-time transmit diversity coding and spatial multiplexing. The capacity varies according to the antenna correlation and the path gain from multiple sensor nodes. Based on these statistical results, we propose an adaptive MIMO mode and antenna set switching algorithm that maximizes the ergodic capacity of mobile sink nodes. The ergodic capacity of the proposed scheme is compared with conventional SN MIMO schemes, where the gain increases as the antenna correlation and path gain ratio increase. PMID:24152920

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

PubMed

Zhang, J W; Rangan, A V

2015-04-01

In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Frequency–specific network connectivity increases underlie accurate spatiotemporal memory retrieval

PubMed Central

Watrous, Andrew J.; Tandon, Nitin; Connor, Chris; Pieters, Thomas; Ekstrom, Arne D.

2013-01-01

The medial temporal lobes, prefrontal cortex, and parts of parietal cortex form the neural underpinnings of episodic memory, which includes remembering both where and when an event occurred. Yet how these three key regions interact during retrieval of spatial and temporal context remains largely untested. Here, we employed simultaneous electrocorticographical recordings across multiple lobular regions, employing phase synchronization as a measure of network functional connectivity, while patients retrieved spatial and temporal context associated with an episode. Successful memory retrieval was characterized by greater global connectivity compared to incorrect retrieval, with the MTL acting as a convergence hub for these interactions. Spatial vs. temporal context retrieval resulted in prominent differences in both the spectral and temporal patterns of network interactions. These results emphasize dynamic network interactions as central to episodic memory retrieval, providing novel insight into how multiple contexts underlying a single event can be recreated within the same network. PMID:23354333

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

Chen, Dong; Heidelberger, Philip; Sugawara, Yutaka

An apparatus and method for extending the scalability and improving the partitionability of networks that contain all-to-all links for transporting packet traffic from a source endpoint to a destination endpoint with low per-endpoint (per-server) cost and a small number of hops. An all-to-all wiring in the baseline topology is decomposed into smaller all-to-all components in which each smaller all-to-all connection is replaced with star topology by using global switches. Stacking multiple copies of the star topology baseline network creates a multi-planed switching topology for transporting packet traffic. Point-to-point unified stacking method using global switch wiring methods connects multiple planes ofmore » a baseline topology by using the global switches to create a large network size with a low number of hops, i.e., low network latency. Grouped unified stacking method increases the scalability (network size) of a stacked topology.« less

Providing end-to-end QoS for multimedia applications in 3G wireless networks

NASA Astrophysics Data System (ADS)

Guo, Katherine; Rangarajan, Samapth; Siddiqui, M. A.; Paul, Sanjoy

2003-11-01

As the usage of wireless packet data services increases, wireless carriers today are faced with the challenge of offering multimedia applications with QoS requirements within current 3G data networks. End-to-end QoS requires support at the application, network, link and medium access control (MAC) layers. We discuss existing CDMA2000 network architecture and show its shortcomings that prevent supporting multiple classes of traffic at the Radio Access Network (RAN). We then propose changes in RAN within the standards framework that enable support for multiple traffic classes. In addition, we discuss how Session Initiation Protocol (SIP) can be augmented with QoS signaling for supporting end-to-end QoS. We also review state of the art scheduling algorithms at the base station and provide possible extensions to these algorithms to support different classes of traffic as well as different classes of users.

Third eyelid in the small Indian mongoose (Herpestes javanicus): a morphological and histological study.

PubMed

Kamali, Younes; Khaksar, Zabihollah; Gholami, Soghra

2015-01-01

The Indian mongoose (Herpestes javanicus) is native to parts of Asia, Iran. The purpose of this study was to describe the gross anatomy of the cartilage and histology of the superficial gland of the third eyelid of two adult mongooses. The animals, in terminal stages of disease and near death due to aging or unknown reasons, were referred from Park Zoo (Shiraz, Iran) to our center. By using a modified maceration technique, the morphological characteristics of the cartilage were examined. For histological examinations of the superficial gland of the third eyelid, the samples were stained with haematoxylin and eosin. Also, to detect the elastic fibers in the cartilage sections were stained with orcein and Weigert's resorcin-fuchsin. The cartilage consisted of an ovoid appendix and a mild reverse sigmoid crossbar. Elastic fibers were scattered throughout the cartilage but were more concentrated in the center. The superficial gland of the third eyelid was compound tubuloacinar with serous acini.

KSC-08pd2351

NASA Image and Video Library

2008-08-08

CAPE CANAVERAL, Fla. – Technicians in the Payload Hazardous Servicing Facility at NASA's Kennedy Space Center help guide the Fine Guidance Sensor, or FGS, as it is lifted over the crossbar of the stand at right. The sensor will be installed on the Orbital Replacement Unit Carrier or ORUC, below. An FGS consists of a large structure housing a collection of mirrors, lenses, servos, prisms, beam splitters and photomultiplier tubes. There are three fine guidance sensors on Hubble located at 90-degree intervals around the circumference of the telescope. Along with the gyroscopes, the optical sensors are a key component of Hubble’s highly complex but extraordinarily effective “pointing control system.” The ORUC is one of three carriers that are being prepared for the integration of telescope science instruments, both internal and external replacement components, as well as the flight support equipment to be used by the astronauts during the fifth and final Hubble servicing mission, STS-125, on space shuttle Atlantis. Launch is targeted for Oct. 8. Photo credit: NASA/Jim Grossmann

KSC-08pd2352

NASA Image and Video Library

2008-08-08

CAPE CANAVERAL, Fla. – In the Payload Hazardous Servicing Facility at NASA's Kennedy Space Center, the Fine Guidance Sensor, or FGS, is lifted over the crossbar of the stand. The sensor will be installed on the Orbital Replacement Unit Carrier or ORUC, below. An FGS consists of a large structure housing a collection of mirrors, lenses, servos, prisms, beam splitters and photomultiplier tubes. There are three fine guidance sensors on Hubble located at 90-degree intervals around the circumference of the telescope. Along with the gyroscopes, the optical sensors are a key component of Hubble’s highly complex but extraordinarily effective “pointing control system.” The ORUC is one of three carriers that are being prepared for the integration of telescope science instruments, both internal and external replacement components, as well as the flight support equipment to be used by the astronauts during the fifth and final Hubble servicing mission, STS-125, on space shuttle Atlantis. Launch is targeted for Oct. 8. Photo credit: NASA/Jim Grossmann

Implementation of olfactory bulb glomerular-layer computations in a digital neurosynaptic core.

PubMed

Imam, Nabil; Cleland, Thomas A; Manohar, Rajit; Merolla, Paul A; Arthur, John V; Akopyan, Filipp; Modha, Dharmendra S

2012-01-01

We present a biomimetic system that captures essential functional properties of the glomerular layer of the mammalian olfactory bulb, specifically including its capacity to decorrelate similar odor representations without foreknowledge of the statistical distributions of analyte features. Our system is based on a digital neuromorphic chip consisting of 256 leaky-integrate-and-fire neurons, 1024 × 256 crossbar synapses, and address-event representation communication circuits. The neural circuits configured in the chip reflect established connections among mitral cells, periglomerular cells, external tufted cells, and superficial short-axon cells within the olfactory bulb, and accept input from convergent sets of sensors configured as olfactory sensory neurons. This configuration generates functional transformations comparable to those observed in the glomerular layer of the mammalian olfactory bulb. Our circuits, consuming only 45 pJ of active power per spike with a power supply of 0.85 V, can be used as the first stage of processing in low-power artificial chemical sensing devices inspired by natural olfactory systems.

Guided growth of horizontal GaN nanowires on quartz and their transfer to other substrates.

PubMed

Goren-Ruck, Lior; Tsivion, David; Schvartzman, Mark; Popovitz-Biro, Ronit; Joselevich, Ernesto

2014-03-25

The guided growth of horizontal nanowires has so far been demonstrated on a limited number of substrates. In most cases, the nanowires are covalently bonded to the substrate where they grow and cannot be transferred to other substrates. Here we demonstrate the guided growth of well-aligned horizontal GaN nanowires on quartz and their subsequent transfer to silicon wafers by selective etching of the quartz while maintaining their alignment. The guided growth was observed on different planes of quartz with varying degrees of alignment. We characterized the crystallographic orientations of the nanowires and proposed a new mechanism of "dynamic graphoepitaxy" for their guided growth on quartz. The transfer of the guided nanowires enabled the fabrication of back-gated field-effect transistors from aligned nanowire arrays on oxidized silicon wafers and the production of crossbar arrays. The guided growth of transferrable nanowires opens up the possibility of massively parallel integration of nanowires into functional systems on virtually any desired substrate.

The Fermilab lattice supercomputer project

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

Fischler, M.; Atac, R.; Cook, A.

1989-02-01

The ACPMAPS system is a highly cost effective, local memory MIMD computer targeted at algorithm development and production running for gauge theory on the lattice. The machine consists of a compound hypercube of crates, each of which is a full crossbar switch containing several processors. The processing nodes are single board array processors based on the Weitek XL chip set, each with a peak power of 20 MFLOPS and supported by 8 MBytes of data memory. The system currently being assembled has a peak power of 5 GFLOPS, delivering performance at approximately $250/MFLOP. The system is programmable in C andmore » Fortran. An underpinning of software routines (CANOPY) provides an easy and natural way of coding lattice problems, such that the details of parallelism, and communication and system architecture are transparent to the user. CANOPY can easily be ported to any single CPU or MIMD system which supports C, and allows the coding of typical applications with very little effort. 3 refs., 1 fig.« less

Transient Resistive Switching Devices Made from Egg Albumen Dielectrics and Dissolvable Electrodes.

PubMed

He, Xingli; Zhang, Jian; Wang, Wenbo; Xuan, Weipeng; Wang, Xiaozhi; Zhang, Qilong; Smith, Charles G; Luo, Jikui

2016-05-04

Egg albumen as the dielectric, and dissolvable Mg and W as the top and bottom electrodes are used to fabricate water-soluble memristors. 4 × 4 cross-bar configuration memristor devices show a bipolar resistive switching behavior with a high to low resistance ratio in the range of 1 × 10(2) to 1 × 10(4), higher than most other biomaterial-based memristors, and a retention time over 10(4) s without any sign of deterioration, demonstrating its high stability and reliability. Metal filaments accompanied by hopping conduction are believed to be responsible for the switching behavior of the memory devices. The Mg and W electrodes, and albumen film all can be dissolved in water within 72 h, showing their transient characteristics. This work demonstrates a new way to fabricate biocompatible and dissolvable electronic devices by using cheap, abundant, and 100% natural materials for the forthcoming bioelectronics era as well as for environmental sensors when the Internet of things takes off.

Oxygen Impurities Link Bistability and Magnetoresistance in Organic Spin Valves.

PubMed

Bergenti, Ilaria; Borgatti, Francesco; Calbucci, Marco; Riminucci, Alberto; Cecchini, Raimondo; Graziosi, Patrizio; MacLaren, Donald A; Giglia, Angelo; Rueff, Jean Pascal; Céolin, Denis; Pasquali, Luca; Dediu, Valentin

2018-03-07

Vertical crossbar devices based on manganite and cobalt injecting electrodes and a metal-quinoline molecular transport layer are known to manifest both magnetoresistance (MR) and electrical bistability. The two effects are strongly interwoven, inspiring new device applications such as electrical control of the MR and magnetic modulation of bistability. To explain the device functionality, we identify the mechanism responsible for electrical switching by associating the electrical conductivity and the impedance behavior with the chemical states of buried layers obtained by in operando photoelectron spectroscopy. These measurements revealed that a significant fraction of oxygen ions migrate under voltage application, resulting in a modification of the electronic properties of the organic material and of the oxidation state of the interfacial layer with the ferromagnetic contacts. Variable oxygen doping of the organic molecules represents the key element for correlating bistability and MR, and our measurements provide the first experimental evidence in favor of the impurity-driven model describing the spin transport in organic semiconductors in similar devices.

Signal and noise extraction from analog memory elements for neuromorphic computing.

PubMed

Gong, N; Idé, T; Kim, S; Boybat, I; Sebastian, A; Narayanan, V; Ando, T

2018-05-29

Dense crossbar arrays of non-volatile memory (NVM) can potentially enable massively parallel and highly energy-efficient neuromorphic computing systems. The key requirements for the NVM elements are continuous (analog-like) conductance tuning capability and switching symmetry with acceptable noise levels. However, most NVM devices show non-linear and asymmetric switching behaviors. Such non-linear behaviors render separation of signal and noise extremely difficult with conventional characterization techniques. In this study, we establish a practical methodology based on Gaussian process regression to address this issue. The methodology is agnostic to switching mechanisms and applicable to various NVM devices. We show tradeoff between switching symmetry and signal-to-noise ratio for HfO 2 -based resistive random access memory. Then, we characterize 1000 phase-change memory devices based on Ge 2 Sb 2 Te 5 and separate total variability into device-to-device variability and inherent randomness from individual devices. These results highlight the usefulness of our methodology to realize ideal NVM devices for neuromorphic computing.

A superconducting CW-LINAC for heavy ion acceleration at GSI

NASA Astrophysics Data System (ADS)

Barth, Winfried; Aulenbacher, Kurt; Basten, Markus; Dziuba, Florian; Gettmann, Viktor; Miski-Oglu, Maksym; Podlech, Holger; Yaramyshev, Stepan

2017-03-01

Recently the Universal Linear Accelerator (UNILAC) serves as a powerful high duty factor (25%) heavy ion beam accelerator for the ambitious experiment program at GSI. Beam time availability for SHE (Super Heavy Element)-research will be decreased due to the limitation of the UNILAC providing Uranium beams with an extremely high peak current for FAIR simultaneously. To keep the GSI-SHE program competitive on a high level and even beyond, a standalone superconducting continuous wave (100% duty factor) LINAC in combination with the upgraded GSI High Charge State injector is envisaged. In preparation for this, the first LINAC section (financed by HIM and GSI) will be tested with beam in 2017, demonstrating the future experimental capabilities. Further on the construction of an extended cryo module comprising two shorter Crossbar-H cavities is foreseen to test until end of 2017. As a final R&D step towards an entire LINAC three advanced cryo modules, each comprising two CH cavities, should be built until 2019, serving for first user experiments at the Coulomb barrier.

RRAM-based parallel computing architecture using k-nearest neighbor classification for pattern recognition

NASA Astrophysics Data System (ADS)

Jiang, Yuning; Kang, Jinfeng; Wang, Xinan

2017-03-01

Resistive switching memory (RRAM) is considered as one of the most promising devices for parallel computing solutions that may overcome the von Neumann bottleneck of today’s electronic systems. However, the existing RRAM-based parallel computing architectures suffer from practical problems such as device variations and extra computing circuits. In this work, we propose a novel parallel computing architecture for pattern recognition by implementing k-nearest neighbor classification on metal-oxide RRAM crossbar arrays. Metal-oxide RRAM with gradual RESET behaviors is chosen as both the storage and computing components. The proposed architecture is tested by the MNIST database. High speed (~100 ns per example) and high recognition accuracy (97.05%) are obtained. The influence of several non-ideal device properties is also discussed, and it turns out that the proposed architecture shows great tolerance to device variations. This work paves a new way to achieve RRAM-based parallel computing hardware systems with high performance.

Defect tolerance in resistor-logic demultiplexers for nanoelectronics.

PubMed

Kuekes, Philip J; Robinett, Warren; Williams, R Stanley

2006-05-28

Since defect rates are expected to be high in nanocircuitry, we analyse the performance of resistor-based demultiplexers in the presence of defects. The defects observed to occur in fabricated nanoscale crossbars are stuck-open, stuck-closed, stuck-short, broken-wire, and adjacent-wire-short defects. We analyse the distribution of voltages on the nanowire output lines of a resistor-logic demultiplexer, based on an arbitrary constant-weight code, when defects occur. These analyses show that resistor-logic demultiplexers can tolerate small numbers of stuck-closed, stuck-open, and broken-wire defects on individual nanowires, at the cost of some degradation in the circuit's worst-case voltage margin. For stuck-short and adjacent-wire-short defects, and for nanowires with too many defects of the other types, the demultiplexer can still achieve error-free performance, but with a smaller set of output lines. This design thus has two layers of defect tolerance: the coding layer improves the yield of usable output lines, and an avoidance layer guarantees that error-free performance is achieved.

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

Technologies and Approaches to Elucidate and Model the Virulence Program of Salmonella.

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

McDermott, Jason E.; Yoon, Hyunjin; Nakayasu, Ernesto S.

Salmonella is a primary cause of enteric diseases in a variety of animals. During its evolution into a pathogenic bacterium, Salmonella acquired an elaborate regulatory network that responds to multiple environmental stimuli within host animals and integrates them resulting in fine regulation of the virulence program. The coordinated action by this regulatory network involves numerous virulence regulators, necessitating genome-wide profiling analysis to assess and combine efforts from multiple regulons. In this review we discuss recent high-throughput analytic approaches to understand the regulatory network of Salmonella that controls virulence processes. Application of high-throughput analyses have generated a large amount of datamore » and driven development of computational approaches required for data integration. Therefore, we also cover computer-aided network analyses to infer regulatory networks, and demonstrate how genome-scale data can be used to construct regulatory and metabolic systems models of Salmonella pathogenesis. Genes that are coordinately controlled by multiple virulence regulators under infectious conditions are more likely to be important for pathogenesis. Thus, reconstructing the global regulatory network during infection or, at the very least, under conditions that mimic the host cellular environment not only provides a bird’s eye view of Salmonella survival strategy in response to hostile host environments but also serves as an efficient means to identify novel virulence factors that are essential for Salmonella to accomplish systemic infection in the host.« less

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

Elman, Jeremy A.; Madison, Cindee M.; Baker, Suzanne L.

In Alzheimer's disease (AD), Beta-amyloid (Aβ) deposition is one of the hallmarks. However, it is also present in some cognitively normal elderly adults and may represent a preclinical disease state. While AD patients exhibit disrupted functional connectivity (FC) both within and between resting-state networks, studies of preclinical cases have focused primarily on the default mode network (DMN). The extent to which Aβ-related effects occur outside of the DMN and between networks remains unclear. In the present study, we examine how within- and between-network FC are related to both global and regional Aβ deposition as measured by [ 11 C]PIB-PET inmore » 92 cognitively normal older people. We found that within-network FC changes occurred in multiple networks, including the DMN. Changes of between-network FC were also apparent, suggesting that regions maintaining connections to multiple networks may be particularly susceptible to Aβ-induced alterations. Cortical regions showing altered FC clustered in parietal and temporal cortex, areas known to be susceptible to AD pathology. These results likely represent a mix of local network disruption, compensatory reorganization, and impaired control network function. They indicate the presence of Aβ-related dysfunction of neural systems in cognitively normal people well before these areas become hypometabolic with the onset of cognitive decline.« less

A novel interacting multiple model based network intrusion detection scheme

NASA Astrophysics Data System (ADS)

Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

2006-04-01

In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts.

PubMed

Fleischer, Vinzenz; Radetz, Angela; Ciolac, Dumitru; Muthuraman, Muthuraman; Gonzalez-Escamilla, Gabriel; Zipp, Frauke; Groppa, Sergiu

2017-11-01

Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Research on Some Bus Transport Networks with Random Overlapping Clique Structure

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Wang, Bo; Wang, Wan-Liang; Sun, You-Xian

2008-11-01

On the basis of investigating the statistical data of bus transport networks of three big cities in China, we propose that each bus route is a clique (maximal complete subgraph) and a bus transport network (BTN) consists of a lot of cliques, which intensively connect and overlap with each other. We study the network properties, which include the degree distribution, multiple edges' overlapping time distribution, distribution of the overlap size between any two overlapping cliques, distribution of the number of cliques that a node belongs to. Naturally, the cliques also constitute a network, with the overlapping nodes being their multiple links. We also research its network properties such as degree distribution, clustering, average path length, and so on. We propose that a BTN has the properties of random clique increment and random overlapping clique, at the same time, a BTN is a small-world network with highly clique-clustered and highly clique-overlapped. Finally, we introduce a BTN evolution model, whose simulation results agree well with the statistical laws that emerge in real BTNs.

Oscillations and Multiple Equilibria in Microvascular Blood Flow.

PubMed

Karst, Nathaniel J; Storey, Brian D; Geddes, John B

2015-07-01

We investigate the existence of oscillatory dynamics and multiple steady-state flow rates in a network with a simple topology and in vivo microvascular blood flow constitutive laws. Unlike many previous analytic studies, we employ the most biologically relevant models of the physical properties of whole blood. Through a combination of analytic and numeric techniques, we predict in a series of two-parameter bifurcation diagrams a range of dynamical behaviors, including multiple equilibria flow configurations, simple oscillations in volumetric flow rate, and multiple coexistent limit cycles at physically realizable parameters. We show that complexity in network topology is not necessary for complex behaviors to arise and that nonlinear rheology, in particular the plasma skimming effect, is sufficient to support oscillatory dynamics similar to those observed in vivo.

Use of Network Inference to Elucidate Common and Chemical-specific Effects on Steoidogenesis

EPA Science Inventory

Microarray data is a key source for modeling gene regulatory interactions. Regulatory network models based on multiple datasets are potentially more robust and can provide greater confidence. In this study, we used network modeling on microarray data generated by exposing the fat...

MCAM: multiple clustering analysis methodology for deriving hypotheses and insights from high-throughput proteomic datasets.

PubMed

Naegle, Kristen M; Welsch, Roy E; Yaffe, Michael B; White, Forest M; Lauffenburger, Douglas A

2011-07-01

Advances in proteomic technologies continue to substantially accelerate capability for generating experimental data on protein levels, states, and activities in biological samples. For example, studies on receptor tyrosine kinase signaling networks can now capture the phosphorylation state of hundreds to thousands of proteins across multiple conditions. However, little is known about the function of many of these protein modifications, or the enzymes responsible for modifying them. To address this challenge, we have developed an approach that enhances the power of clustering techniques to infer functional and regulatory meaning of protein states in cell signaling networks. We have created a new computational framework for applying clustering to biological data in order to overcome the typical dependence on specific a priori assumptions and expert knowledge concerning the technical aspects of clustering. Multiple clustering analysis methodology ('MCAM') employs an array of diverse data transformations, distance metrics, set sizes, and clustering algorithms, in a combinatorial fashion, to create a suite of clustering sets. These sets are then evaluated based on their ability to produce biological insights through statistical enrichment of metadata relating to knowledge concerning protein functions, kinase substrates, and sequence motifs. We applied MCAM to a set of dynamic phosphorylation measurements of the ERRB network to explore the relationships between algorithmic parameters and the biological meaning that could be inferred and report on interesting biological predictions. Further, we applied MCAM to multiple phosphoproteomic datasets for the ERBB network, which allowed us to compare independent and incomplete overlapping measurements of phosphorylation sites in the network. We report specific and global differences of the ERBB network stimulated with different ligands and with changes in HER2 expression. Overall, we offer MCAM as a broadly-applicable approach for analysis of proteomic data which may help increase the current understanding of molecular networks in a variety of biological problems. © 2011 Naegle et al.

A fuzzy integral method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification across multiple subjects.

PubMed

Cacha, L A; Parida, S; Dehuri, S; Cho, S-B; Poznanski, R R

2016-12-01

The huge number of voxels in fMRI over time poses a major challenge to for effective analysis. Fast, accurate, and reliable classifiers are required for estimating the decoding accuracy of brain activities. Although machine-learning classifiers seem promising, individual classifiers have their own limitations. To address this limitation, the present paper proposes a method based on the ensemble of neural networks to analyze fMRI data for cognitive state classification for application across multiple subjects. Similarly, the fuzzy integral (FI) approach has been employed as an efficient tool for combining different classifiers. The FI approach led to the development of a classifiers ensemble technique that performs better than any of the single classifier by reducing the misclassification, the bias, and the variance. The proposed method successfully classified the different cognitive states for multiple subjects with high accuracy of classification. Comparison of the performance improvement, while applying ensemble neural networks method, vs. that of the individual neural network strongly points toward the usefulness of the proposed method.

Distributed Synchronization in Networks of Agent Systems With Nonlinearities and Random Switchings.

PubMed

Tang, Yang; Gao, Huijun; Zou, Wei; Kurths, Jürgen

2013-02-01

In this paper, the distributed synchronization problem of networks of agent systems with controllers and nonlinearities subject to Bernoulli switchings is investigated. Controllers and adaptive updating laws injected in each vertex of networks depend on the state information of its neighborhood. Three sets of Bernoulli stochastic variables are introduced to describe the occurrence probabilities of distributed adaptive controllers, updating laws and nonlinearities, respectively. By the Lyapunov functions method, we show that the distributed synchronization of networks composed of agent systems with multiple randomly occurring nonlinearities, multiple randomly occurring controllers, and multiple randomly occurring updating laws can be achieved in mean square under certain criteria. The conditions derived in this paper can be solved by semi-definite programming. Moreover, by mathematical analysis, we find that the coupling strength, the probabilities of the Bernoulli stochastic variables, and the form of nonlinearities have great impacts on the convergence speed and the terminal control strength. The synchronization criteria and the observed phenomena are demonstrated by several numerical simulation examples. In addition, the advantage of distributed adaptive controllers over conventional adaptive controllers is illustrated.

Multiple sclerosis lesions affect intrinsic functional connectivity of the spinal cord.

PubMed

Conrad, Benjamin N; Barry, Robert L; Rogers, Baxter P; Maki, Satoshi; Mishra, Arabinda; Thukral, Saakshi; Sriram, Subramaniam; Bhatia, Aashim; Pawate, Siddharama; Gore, John C; Smith, Seth A

2018-06-01

Patients with multiple sclerosis present with focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of spinal cord activity and functional organization in multiple sclerosis, given the cord's critical role in the disease. Recent reports of spontaneous blood oxygenation level-dependent fluctuations in the spinal cord using functional MRI suggest that, like the brain, cord activity at rest is organized into distinct, synchronized functional networks among grey matter regions, likely related to motor and sensory systems. Previous studies looking at stimulus-evoked activity in the spinal cord of patients with multiple sclerosis have demonstrated increased levels of activation as well as a more bilateral distribution of activity compared to controls. Functional connectivity studies of brain networks in multiple sclerosis have revealed widespread alterations, which may take on a dynamic trajectory over the course of the disease, with compensatory increases in connectivity followed by decreases associated with structural damage. We build upon this literature by examining functional connectivity in the spinal cord of patients with multiple sclerosis. Using ultra-high field 7 T imaging along with processing strategies for robust spinal cord functional MRI and lesion identification, the present study assessed functional connectivity within cervical cord grey matter of patients with relapsing-remitting multiple sclerosis (n = 22) compared to a large sample of healthy controls (n = 56). Patient anatomical images were rated for lesions by three independent raters, with consensus ratings revealing 19 of 22 patients presented with lesions somewhere in the imaged volume. Linear mixed models were used to assess effects of lesion location on functional connectivity. Analysis in control subjects demonstrated a robust pattern of connectivity among ventral grey matter regions as well as a distinct network among dorsal regions. A gender effect was also observed in controls whereby females demonstrated higher ventral network connectivity. Wilcoxon rank-sum tests detected no differences in average connectivity or power of low frequency fluctuations in patients compared to controls. The presence of lesions was, however, associated with local alterations in connectivity with differential effects depending on columnar location. The patient results suggest that spinal cord functional networks are generally intact in relapsing-remitting multiple sclerosis but that lesions are associated with focal abnormalities in intrinsic connectivity. These findings are discussed in light of the current literature on spinal cord functional MRI and the potential neurological underpinnings.

Detection of Road Surface States from Tire Noise Using Neural Network Analysis

NASA Astrophysics Data System (ADS)

Kongrattanaprasert, Wuttiwat; Nomura, Hideyuki; Kamakura, Tomoo; Ueda, Koji

This report proposes a new processing method for automatically detecting the states of road surfaces from tire noises of passing vehicles. In addition to multiple indicators of the signal features in the frequency domain, we propose a few feature indicators in the time domain to successfully classify the road states into four categories: snowy, slushy, wet, and dry states. The method is based on artificial neural networks. The proposed classification is carried out in multiple neural networks using learning vector quantization. The outcomes of the networks are then integrated by the voting decision-making scheme. Experimental results obtained from recorded signals for ten days in the snowy season demonstrated that an accuracy of approximately 90% can be attained for predicting road surface states using only tire noise data.

Networking CD-ROMs: The Decision Maker's Guide to Local Area Network Solutions.

ERIC Educational Resources Information Center

Elshami, Ahmed M.

In an era when patrons want access to CD-ROM resources but few libraries can afford to buy multiple copies, CD-ROM local area networks (LANs) are emerging as a cost-effective way to provide shared access. To help librarians make informed decisions, this manual offers information on: (1) the basics of LANs, a "local area network primer";…

Optimal Scheduling for Underwater Communications in Multiple-user Scenarios

DTIC Science & Technology

2014-09-30

underwater acoustic sensor networks . These techniques aim at consuming as less energy as... underwater acoustic networks disrupt the behavior of surrounding species of marine mammals. As a consequence of these two studies, we aim at developing...Markov models of incremental redundancy hybrid ARQ over underwater acoustic channels. Elsevier Journal on Ad-hoc Networks (Special Issue on Underwater Communications and Networks ), 2014. 4

Multiple network alignment via multiMAGNA+.

PubMed

Vijayan, Vipin; Milenkovic, Tijana

2017-08-21

Network alignment (NA) aims to find a node mapping that identifies topologically or functionally similar network regions between molecular networks of different species. Analogous to genomic sequence alignment, NA can be used to transfer biological knowledge from well- to poorly-studied species between aligned network regions. Pairwise NA (PNA) finds similar regions between two networks while multiple NA (MNA) can align more than two networks. We focus on MNA. Existing MNA methods aim to maximize total similarity over all aligned nodes (node conservation). Then, they evaluate alignment quality by measuring the amount of conserved edges, but only after the alignment is constructed. Directly optimizing edge conservation during alignment construction in addition to node conservation may result in superior alignments. Thus, we present a novel MNA method called multiMAGNA++ that can achieve this. Indeed, multiMAGNA++ outperforms or is on par with existing MNA methods, while often completing faster than existing methods. That is, multiMAGNA++ scales well to larger network data and can be parallelized effectively. During method evaluation, we also introduce new MNA quality measures to allow for more fair MNA method comparison compared to the existing alignment quality measures. MultiMAGNA++ code is available on the method's web page at http://nd.edu/~cone/multiMAGNA++/.

Contemporary, emerging, and ratified wireless security standards: an update for the networked dental office.

PubMed

Mupparapu, Muralidhar

2006-02-15

Wireless networking is not new to contemporary dental offices around the country. Wireless routers and network cards have made access to patient records within the office handy and, thereby, saving valuable chair side time and increasing productivity. As is the case with any rapidly developing technology, wireless technology also changes with the same rate. Unless, the users of the wireless networking understand the implications of these changes and keep themselves updated periodically, the office network will become obsolete very quickly. This update of the emerging security protocols and pertaining to ratified wireless 802.11 standards will be timely for the contemporary dentist whose office is wirelessly networked. This article brings the practicing dentist up-to-date on the newer versions and standards in wireless networking that are changing at a fast pace. The introduction of newer 802.11 standards like super G, Super AG, Multiple Input Multiple Output (MIMO), and pre-n are changing the pace of adaptation of this technology. Like any other rapidly transforming technology, information pertaining to wireless networking should be a priority for the contemporary dentist, an eventual end-user in order to be a well-informed and techno-savvy consumer.

Using Network Science Measures to Predict the Lexical Decision Performance of Adults Who Stutter.

PubMed

Castro, Nichol; Pelczarski, Kristin M; Vitevitch, Michael S

2017-07-12

Methods from network science have examined various aspects of language processing. Clinical populations may also benefit from these novel analyses. Phonological and lexical factors have been examined in adults who stutter (AWS) as potential contributing factors to stuttering, although differences reported are often subtle. We reexamined the performance of AWS and adults who do not stutter (AWNS) from a previously conducted lexical decision task in an attempt to determine if network science measures would provide additional insight into the phonological network of AWS beyond traditional psycholinguistic measures. Multiple regression was used to examine the influence of several traditional psycholinguistic measures as well as several new measures from network science on response times. AWS responded to low-frequency words more slowly than AWNS; responses for both groups were equivalent for high-frequency words. AWS responded to shorter words more slowly than AWNS, producing a reverse word-length effect. For the network measures, degree/neighborhood density and closeness centrality, but not whether a word was inside or outside the giant component, influenced response times similarly between groups. Network analyses suggest that multiple levels of the phonological network might influence phonological processing, not just the micro-level traditionally considered by mainstream psycholinguistics.

Recognition of Telugu characters using neural networks.

PubMed

Sukhaswami, M B; Seetharamulu, P; Pujari, A K

1995-09-01

The aim of the present work is to recognize printed and handwritten Telugu characters using artificial neural networks (ANNs). Earlier work on recognition of Telugu characters has been done using conventional pattern recognition techniques. We make an initial attempt here of using neural networks for recognition with the aim of improving upon earlier methods which do not perform effectively in the presence of noise and distortion in the characters. The Hopfield model of neural network working as an associative memory is chosen for recognition purposes initially. Due to limitation in the capacity of the Hopfield neural network, we propose a new scheme named here as the Multiple Neural Network Associative Memory (MNNAM). The limitation in storage capacity has been overcome by combining multiple neural networks which work in parallel. It is also demonstrated that the Hopfield network is suitable for recognizing noisy printed characters as well as handwritten characters written by different "hands" in a variety of styles. Detailed experiments have been carried out using several learning strategies and results are reported. It is shown here that satisfactory recognition is possible using the proposed strategy. A detailed preprocessing scheme of the Telugu characters from digitized documents is also described.

A DTN-Based Multiple Access Fast Forward Service for the NASA Space Network

NASA Technical Reports Server (NTRS)

Israel, David; Davis, Faith; Marquart. Jane

2011-01-01

The NASA Space Network provides a demand access return link service capable of providing users a space link "on demand". An equivalent service in the forward link direction is not possible due to Tracking and Data Relay Spacecraft (TDRS) constraints. A Disruption Tolerant Networking (DTN)-based Multiple Access Fast Forward (MAFF) service has been proposed to provide a forward link to a user as soon as possible. Previous concept studies have identified a basic architecture and implementation approach. This paper reviews the user scenarios and benefits of an MAFF service and proposes an implementation approach based on the use of DTN protocols.

A Self-Referenced Optical Intensity Sensor Network Using POFBGs for Biomedical Applications

PubMed Central

Moraleda, Alberto Tapetado; Montero, David Sánchez; Webb, David J.; García, Carmen Vázquez

2014-01-01

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown. PMID:25615736

A self-referenced optical intensity sensor network using POFBGs for biomedical applications.

PubMed

Tapetado Moraleda, Alberto; Sánchez Montero, David; Webb, David J; Vázquez García, Carmen

2014-12-12

This work bridges the gap between the remote interrogation of multiple optical sensors and the advantages of using inherently biocompatible low-cost polymer optical fiber (POF)-based photonic sensing. A novel hybrid sensor network combining both silica fiber Bragg gratings (FBG) and polymer FBGs (POFBG) is analyzed. The topology is compatible with WDM networks so multiple remote sensors can be addressed providing high scalability. A central monitoring unit with virtual data processing is implemented, which could be remotely located up to units of km away. The feasibility of the proposed solution for potential medical environments and biomedical applications is shown.

Full-band TDM-OPDMA for OBI-reduced simultaneous multiple access in a single-wavelength optical access network.

PubMed

Jung, Sun-Young; Kim, Chang-Hun; Han, Sang-Kook

2018-05-14

Simultaneous multiple access (MA) within a single wavelength can increase the data rate and split ratio in a passive optical network while optical beat interference (OBI) becomes serious in the uplink. Previous techniques to reduce OBI were limited by their complexity and lack of extendibility; as well, bandwidth allocation among MA signals is needed for single photo diode (PD) detection. We proposed and experimentally demonstrated full-band optical pulse division multiplexing-based MA (OPDMA) in an optical access network, which can effectively reduce OBI with extendibility and fully utilize frequency resources of optical modulator without bandwidth allocation in a single-wavelength MA.

Efficient Assignment of Multiple E-MBMS Sessions towards LTE

NASA Astrophysics Data System (ADS)

Alexiou, Antonios; Bouras, Christos; Kokkinos, Vasileios

One of the major prerequisites for Long Term Evolution (LTE) networks is the mass provision of multimedia services to mobile users. To this end, Evolved - Multimedia Broadcast/Multicast Service (E-MBMS) is envisaged to play an instrumental role during LTE standardization process and ensure LTE’s proliferation in mobile market. E-MBMS targets at the economic delivery, in terms of power and spectral efficiency, of multimedia data from a single source entity to multiple destinations. This paper proposes a novel mechanism for efficient radio bearer selection during E-MBMS transmissions in LTE networks. The proposed mechanism is based on the concept of transport channels combination in any cell of the network. Most significantly, the mechanism manages to efficiently deliver multiple E-MBMS sessions. The performance of the proposed mechanism is evaluated and compared with several radio bearer selection mechanisms in order to highlight the enhancements that it provides.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

The Face-Processing Network Is Resilient to Focal Resection of Human Visual Cortex.

PubMed

Weiner, Kevin S; Jonas, Jacques; Gomez, Jesse; Maillard, Louis; Brissart, Hélène; Hossu, Gabriela; Jacques, Corentin; Loftus, David; Colnat-Coulbois, Sophie; Stigliani, Anthony; Barnett, Michael A; Grill-Spector, Kalanit; Rossion, Bruno

2016-08-10

Human face perception requires a network of brain regions distributed throughout the occipital and temporal lobes with a right hemisphere advantage. Present theories consider this network as either a processing hierarchy beginning with the inferior occipital gyrus (occipital face area; IOG-faces/OFA) or a multiple-route network with nonhierarchical components. The former predicts that removing IOG-faces/OFA will detrimentally affect downstream stages, whereas the latter does not. We tested this prediction in a human patient (Patient S.P.) requiring removal of the right inferior occipital cortex, including IOG-faces/OFA. We acquired multiple fMRI measurements in Patient S.P. before and after a preplanned surgery and multiple measurements in typical controls, enabling both within-subject/across-session comparisons (Patient S.P. before resection vs Patient S.P. after resection) and between-subject/across-session comparisons (Patient S.P. vs controls). We found that the spatial topology and selectivity of downstream ipsilateral face-selective regions were stable 1 and 8 month(s) after surgery. Additionally, the reliability of distributed patterns of face selectivity in Patient S.P. before versus after resection was not different from across-session reliability in controls. Nevertheless, postoperatively, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1 of the resected hemisphere. Diffusion weighted imaging in Patient S.P. and controls identifies white matter tracts connecting retinotopic areas to downstream face-selective regions, which may contribute to the stable and plastic features of the face network in Patient S.P. after surgery. Together, our results support a multiple-route network of face processing with nonhierarchical components and shed light on stable and plastic features of high-level visual cortex following focal brain damage. Brain networks consist of interconnected functional regions commonly organized in processing hierarchies. Prevailing theories predict that damage to the input of the hierarchy will detrimentally affect later stages. We tested this prediction with multiple brain measurements in a rare human patient requiring surgical removal of the putative input to a network processing faces. Surprisingly, the spatial topology and selectivity of downstream face-selective regions are stable after surgery. Nevertheless, representations of visual space were typical in dorsal face-selective regions but atypical in ventral face-selective regions and V1. White matter connections from outside the face network may support these stable and plastic features. As processing hierarchies are ubiquitous in biological and nonbiological systems, our results have pervasive implications for understanding the construction of resilient networks. Copyright © 2016 the authors 0270-6474/16/368426-16$15.00/0.

Effects of Beta-Amyloid on Resting State Functional Connectivity Within and Between Networks Reflect Known Patterns of Regional Vulnerability

DOE PAGES

Elman, Jeremy A.; Madison, Cindee M.; Baker, Suzanne L.; ...

2014-11-07

In Alzheimer's disease (AD), Beta-amyloid (Aβ) deposition is one of the hallmarks. However, it is also present in some cognitively normal elderly adults and may represent a preclinical disease state. While AD patients exhibit disrupted functional connectivity (FC) both within and between resting-state networks, studies of preclinical cases have focused primarily on the default mode network (DMN). The extent to which Aβ-related effects occur outside of the DMN and between networks remains unclear. In the present study, we examine how within- and between-network FC are related to both global and regional Aβ deposition as measured by [ 11 C]PIB-PET inmore » 92 cognitively normal older people. We found that within-network FC changes occurred in multiple networks, including the DMN. Changes of between-network FC were also apparent, suggesting that regions maintaining connections to multiple networks may be particularly susceptible to Aβ-induced alterations. Cortical regions showing altered FC clustered in parietal and temporal cortex, areas known to be susceptible to AD pathology. These results likely represent a mix of local network disruption, compensatory reorganization, and impaired control network function. They indicate the presence of Aβ-related dysfunction of neural systems in cognitively normal people well before these areas become hypometabolic with the onset of cognitive decline.« less

NASA Integrated Network COOP

NASA Technical Reports Server (NTRS)

Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

2012-01-01

Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

Meeting the Nine Essentials: Winthrop University-School Partnership Network

ERIC Educational Resources Information Center

Johnson, Lisa E.; Rakestraw, Jennie

2014-01-01

Johnson and Rakestraw describe the Winthrop University-School Partnership Network (WUSP) as a dynamic, diverse, and growing group of participants from nine school districts, thirty schools, multiple university programs, and community organizations. As a Network, they are working to emulate John Goodlad's (1984) vision "in order to improve…

Identifying the Key Weaknesses in Network Security at Colleges.

ERIC Educational Resources Information Center

Olsen, Florence

2000-01-01

A new study identifies and ranks the 10 security gaps responsible for most outsider attacks on college computer networks. The list is intended to help campus system administrators establish priorities as they work to increase security. One network security expert urges that institutions utilize multiple security layers. (DB)

A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

PubMed Central

Wang, Runchun M.; Hamilton, Tara J.; Tapson, Jonathan C.; van Schaik, André

2015-01-01

We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP) and Spike Timing Dependent Delay Plasticity (STDDP). We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 226 (64M) synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted or delayed pre-synaptic spike to the post-synaptic neuron in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 236 (64G) synaptic adaptors on a current high-end FPGA platform. PMID:26041985

Computing all hybridization networks for multiple binary phylogenetic input trees.

PubMed

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

PubMed

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Universal filtered multi-carrier system for asynchronous uplink transmission in optical access network

NASA Astrophysics Data System (ADS)

Kang, Soo-Min; Kim, Chang-Hun; Han, Sang-Kook

2016-02-01

In passive optical network (PON), orthogonal frequency division multiplexing (OFDM) has been studied actively due to its advantages such as high spectra efficiency (SE), dynamic resource allocation in time or frequency domain, and dispersion robustness. However, orthogonal frequency division multiple access (OFDMA)-PON requires tight synchronization among multiple access signals. If not, frequency orthogonality could not be maintained. Also its sidelobe causes inter-channel interference (ICI) to adjacent channel. To prevent ICI caused by high sidelobes, guard band (GB) is usually used which degrades SE. Thus, OFDMA-PON is not suitable for asynchronous uplink transmission in optical access network. In this paper, we propose intensity modulation/direct detection (IM/DD) based universal filtered multi-carrier (UFMC) PON for asynchronous multiple access. The UFMC uses subband filtering to subsets of subcarriers. Since it reduces sidelobe of each subband by applying subband filtering, it could achieve better performance compared to OFDM. For the experimental demonstration, different sample delay was applied to subbands to implement asynchronous transmission condition. As a result, time synchronization robustness of UFMC was verified in asynchronous multiple access system.

Terminal-oriented computer-communication networks.

NASA Technical Reports Server (NTRS)

Schwartz, M.; Boorstyn, R. R.; Pickholtz, R. L.

1972-01-01

Four examples of currently operating computer-communication networks are described in this tutorial paper. They include the TYMNET network, the GE Information Services network, the NASDAQ over-the-counter stock-quotation system, and the Computer Sciences Infonet. These networks all use programmable concentrators for combining a multiplicity of terminals. Included in the discussion for each network is a description of the overall network structure, the handling and transmission of messages, communication requirements, routing and reliability consideration where applicable, operating data and design specifications where available, and unique design features in the area of computer communications.

Network Modeling and Energy-Efficiency Optimization for Advanced Machine-to-Machine Sensor Networks

PubMed Central

Jung, Sungmo; Kim, Jong Hyun; Kim, Seoksoo

2012-01-01

Wireless machine-to-machine sensor networks with multiple radio interfaces are expected to have several advantages, including high spatial scalability, low event detection latency, and low energy consumption. Here, we propose a network model design method involving network approximation and an optimized multi-tiered clustering algorithm that maximizes node lifespan by minimizing energy consumption in a non-uniformly distributed network. Simulation results show that the cluster scales and network parameters determined with the proposed method facilitate a more efficient performance compared to existing methods. PMID:23202190

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

PubMed

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available.

Flow Analysis Tool White Paper

NASA Technical Reports Server (NTRS)

Boscia, Nichole K.

2012-01-01

Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

NASA Astrophysics Data System (ADS)

Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

2001-07-01

Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks.

PubMed

Xu, Lina; O'Hare, Gregory M P; Collier, Rem

2017-07-05

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.

Observability and Estimation of Distributed Space Systems via Local Information-Exchange Networks

NASA Technical Reports Server (NTRS)

Fathpour, Nanaz; Hadaegh, Fred Y.; Mesbahi, Mehran; Rahmani, Amirreza

2011-01-01

Spacecraft formation flying involves the coordination of states among multiple spacecraft through relative sensing, inter-spacecraft communication, and control. Most existing formation-flying estimation algorithms can only be supported via highly centralized, all-to-all, static relative sensing. New algorithms are proposed that are scalable, modular, and robust to variations in the topology and link characteristics of the formation exchange network. These distributed algorithms rely on a local information exchange network, relaxing the assumptions on existing algorithms. Distributed space systems rely on a signal transmission network among multiple spacecraft for their operation. Control and coordination among multiple spacecraft in a formation is facilitated via a network of relative sensing and interspacecraft communications. Guidance, navigation, and control rely on the sensing network. This network becomes more complex the more spacecraft are added, or as mission requirements become more complex. The observability of a formation state was observed by a set of local observations from a particular node in the formation. Formation observability can be parameterized in terms of the matrices appearing in the formation dynamics and observation matrices. An agreement protocol was used as a mechanism for observing formation states from local measurements. An agreement protocol is essentially an unforced dynamic system whose trajectory is governed by the interconnection geometry and initial condition of each node, with a goal of reaching a common value of interest. The observability of the interconnected system depends on the geometry of the network, as well as the position of the observer relative to the topology. For the first time, critical GN&C (guidance, navigation, and control estimation) subsystems are synthesized by bringing the contribution of the spacecraft information-exchange network to the forefront of algorithmic analysis and design. The result is a formation estimation algorithm that is modular and robust to variations in the topology and link properties of the underlying formation network.

A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks †

PubMed Central

O’Hare, Gregory M. P.; Collier, Rem

2017-01-01

Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work—Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity. PMID:28678164

Network meta-analysis of diagnostic test accuracy studies identifies and ranks the optimal diagnostic tests and thresholds for health care policy and decision-making.

PubMed

Owen, Rhiannon K; Cooper, Nicola J; Quinn, Terence J; Lees, Rosalind; Sutton, Alex J

2018-07-01

Network meta-analyses (NMA) have extensively been used to compare the effectiveness of multiple interventions for health care policy and decision-making. However, methods for evaluating the performance of multiple diagnostic tests are less established. In a decision-making context, we are often interested in comparing and ranking the performance of multiple diagnostic tests, at varying levels of test thresholds, in one simultaneous analysis. Motivated by an example of cognitive impairment diagnosis following stroke, we synthesized data from 13 studies assessing the efficiency of two diagnostic tests: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), at two test thresholds: MMSE <25/30 and <27/30, and MoCA <22/30 and <26/30. Using Markov chain Monte Carlo (MCMC) methods, we fitted a bivariate network meta-analysis model incorporating constraints on increasing test threshold, and accounting for the correlations between multiple test accuracy measures from the same study. We developed and successfully fitted a model comparing multiple tests/threshold combinations while imposing threshold constraints. Using this model, we found that MoCA at threshold <26/30 appeared to have the best true positive rate, whereas MMSE at threshold <25/30 appeared to have the best true negative rate. The combined analysis of multiple tests at multiple thresholds allowed for more rigorous comparisons between competing diagnostics tests for decision making. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

Interacting epidemics on overlay networks

NASA Astrophysics Data System (ADS)

Funk, Sebastian; Jansen, Vincent A. A.

2010-03-01

The interaction between multiple pathogens spreading on networks connecting a given set of nodes presents an ongoing theoretical challenge. Here, we aim to understand such interactions by studying bond percolation of two different processes on overlay networks of arbitrary joint degree distribution. We find that an outbreak of a first pathogen providing immunity to another one spreading subsequently on a second network connecting the same set of nodes does so most effectively if the degrees on the two networks are positively correlated. In that case, the protection is stronger the more heterogeneous the degree distributions of the two networks are. If, on the other hand, the degrees are uncorrelated or negatively correlated, increasing heterogeneity reduces the potential of the first process to prevent the second one from reaching epidemic proportions. We generalize these results to cases where the edges of the two networks overlap to arbitrary amount, or where the immunity granted is only partial. If both processes grant immunity to each other, we find a wide range of possible situations of coexistence or mutual exclusion, depending on the joint degree distribution of the underlying networks and the amount of immunity granted mutually. These results generalize the concept of a coexistence threshold and illustrate the impact of large-scale network structure on the interaction between multiple spreading agents.

Covariance, correlation matrix, and the multiscale community structure of networks.

PubMed

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Network reconfiguration and neuronal plasticity in rhythm-generating networks.

PubMed

Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

2011-12-01

Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

NASA Astrophysics Data System (ADS)

Gouissem, A.; Hamila, R.; Al-Dhahir, N.; Foufou, S.

2016-12-01

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.

Resting-state fMRI data reflects default network activity rather than null data: A defense of commonly employed methods to correct for multiple comparisons.

PubMed

Slotnick, Scott D

2017-07-01

Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.

Universal principles governing multiple random searchers on complex networks: The logarithmic growth pattern and the harmonic law

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Harandizadeh, Bahareh; Hui, Pan

2018-03-01

We propose a unified framework to evaluate and quantify the search time of multiple random searchers traversing independently and concurrently on complex networks. We find that the intriguing behaviors of multiple random searchers are governed by two basic principles—the logarithmic growth pattern and the harmonic law. Specifically, the logarithmic growth pattern characterizes how the search time increases with the number of targets, while the harmonic law explores how the search time of multiple random searchers varies relative to that needed by individual searchers. Numerical and theoretical results demonstrate these two universal principles established across a broad range of random search processes, including generic random walks, maximal entropy random walks, intermittent strategies, and persistent random walks. Our results reveal two fundamental principles governing the search time of multiple random searchers, which are expected to facilitate investigation of diverse dynamical processes like synchronization and spreading.

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

DTIC Science & Technology

2016-09-01

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

Proactive Problem Avoidance and Quality of Service (QOS) Guarantees for Large Heterogeneous Networks

DTIC Science & Technology

2002-03-01

host, and can be used to monitor and provide problem response data to multiple network elements. A blowup of the components of an RA is shown in...developed based on stati signal processing and learning. T ts to stical here are two salient features on the intelligent gents developed: (1) an...For multiple routers, the physical connections between interfaces along with the respective health of terface are represented. in In addition to

Distributed Containment Control for Multiple Unknown Second-Order Nonlinear Systems With Application to Networked Lagrangian Systems.

PubMed

Mei, Jie; Ren, Wei; Li, Bing; Ma, Guangfu

2015-09-01

In this paper, we consider the distributed containment control problem for multiagent systems with unknown nonlinear dynamics. More specifically, we focus on multiple second-order nonlinear systems and networked Lagrangian systems. We first study the distributed containment control problem for multiple second-order nonlinear systems with multiple dynamic leaders in the presence of unknown nonlinearities and external disturbances under a general directed graph that characterizes the interaction among the leaders and the followers. A distributed adaptive control algorithm with an adaptive gain design based on the approximation capability of neural networks is proposed. We present a necessary and sufficient condition on the directed graph such that the containment error can be reduced as small as desired. As a byproduct, the leaderless consensus problem is solved with asymptotical convergence. Because relative velocity measurements between neighbors are generally more difficult to obtain than relative position measurements, we then propose a distributed containment control algorithm without using neighbors' velocity information. A two-step Lyapunov-based method is used to study the convergence of the closed-loop system. Next, we apply the ideas to deal with the containment control problem for networked unknown Lagrangian systems under a general directed graph. All the proposed algorithms are distributed and can be implemented using only local measurements in the absence of communication. Finally, simulation examples are provided to show the effectiveness of the proposed control algorithms.

Global Synchronization of Multiple Recurrent Neural Networks With Time Delays via Impulsive Interactions.

PubMed

Yang, Shaofu; Guo, Zhenyuan; Wang, Jun

2017-07-01

In this paper, new results on the global synchronization of multiple recurrent neural networks (NNs) with time delays via impulsive interactions are presented. Impulsive interaction means that a number of NNs communicate with each other at impulse instants only, while they are independent at the remaining time. The communication topology among NNs is not required to be always connected and can switch ON and OFF at different impulse instants. By using the concept of sequential connectivity and the properties of stochastic matrices, a set of sufficient conditions depending on time delays is derived to ascertain global synchronization of multiple continuous-time recurrent NNs. In addition, a counterpart on the global synchronization of multiple discrete-time NNs is also discussed. Finally, two examples are presented to illustrate the results.

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

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

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE PAGES

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

2017-01-16

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators.

PubMed

Gutierrez, Gabrielle J; O'Leary, Timothy; Marder, Eve

2013-03-06

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

PubMed

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Screening of differentially expressed genes between multiple trauma patients with and without sepsis.

PubMed

Ji, S C; Pan, Y T; Lu, Q Y; Sun, Z Y; Liu, Y Z

2014-03-17

The purpose of this study was to identify critical genes associated with septic multiple trauma by comparing peripheral whole blood samples from multiple trauma patients with and without sepsis. A microarray data set was downloaded from the Gene Expression Omnibus (GEO) database. This data set included 70 samples, 36 from multiple trauma patients with sepsis and 34 from multiple trauma patients without sepsis (as a control set). The data were preprocessed, and differentially expressed genes (DEGs) were then screened for using packages of the R language. Functional analysis of DEGs was performed with DAVID. Interaction networks were then established for the most up- and down-regulated genes using HitPredict. Pathway-enrichment analysis was conducted for genes in the networks using WebGestalt. Fifty-eight DEGs were identified. The expression levels of PLAU (down-regulated) and MMP8 (up-regulated) presented the largest fold-changes, and interaction networks were established for these genes. Further analysis revealed that PLAT (plasminogen activator, tissue) and SERPINF2 (serpin peptidase inhibitor, clade F, member 2), which interact with PLAU, play important roles in the pathway of the component and coagulation cascade. We hypothesize that PLAU is a major regulator of the component and coagulation cascade, and down-regulation of PLAU results in dysfunction of the pathway, causing sepsis.

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

Multiple Assembly Rules Drive the Co-occurrence of Orthopteran and Plant Species in Grasslands: Combining Network, Functional and Phylogenetic Approaches

PubMed Central

Fournier, Bertrand; Mouly, Arnaud; Gillet, François

2016-01-01

Understanding the factors underlying the co-occurrence of multiple species remains a challenge in ecology. Biotic interactions, environmental filtering and neutral processes are among the main mechanisms evoked to explain species co-occurrence. However, they are most often studied separately or even considered as mutually exclusive. This likely hampers a more global understanding of species assembly. Here, we investigate the general hypothesis that the structure of co-occurrence networks results from multiple assembly rules and its potential implications for grassland ecosystems. We surveyed orthopteran and plant communities in 48 permanent grasslands of the French Jura Mountains and gathered functional and phylogenetic data for all species. We constructed a network of plant and orthopteran species co-occurrences and verified whether its structure was modular or nested. We investigated the role of all species in the structure of the network (modularity and nestedness). We also investigated the assembly rules driving the structure of the plant-orthopteran co-occurrence network by using null models on species functional traits, phylogenetic relatedness and environmental conditions. We finally compared our results to abundance-based approaches. We found that the plant-orthopteran co-occurrence network had a modular organization. Community assembly rules differed among modules for plants while interactions with plants best explained the distribution of orthopterans into modules. Few species had a disproportionately high positive contribution to this modular organization and are likely to have a key importance to modulate future changes. The impact of agricultural practices was restricted to some modules (3 out of 5) suggesting that shifts in agricultural practices might not impact the entire plant-orthopteran co-occurrence network. These findings support our hypothesis that multiple assembly rules drive the modular structure of the plant-orthopteran network. This modular structure is likely to play a key role in the response of grassland ecosystems to future changes by limiting the impact of changes in agricultural practices such as intensification to some modules leaving species from other modules poorly impacted. The next step is to understand the importance of this modular structure for the long-term maintenance of grassland ecosystem structure and functions as well as to develop tools to integrate network structure into models to improve their capacity to predict future changes. PMID:27582754

Enhancing Classroom Effectiveness through Social Networking Tools

ERIC Educational Resources Information Center

Kurthakoti, Raghu; Boostrom, Robert E., Jr.; Summey, John H.; Campbell, David A.

2013-01-01

To determine the usefulness of social networking Web sites such as Ning.com as a communication tool in marketing courses, a study was designed with special concern for social network use in comparison to Blackboard. Students from multiple marketing courses were surveyed. Assessments of Ning.com and Blackboard were performed both to understand how…

Network Financial Support and Conflict as Predictors of Depressive Symptoms among a Highly Disadvantaged Population

ERIC Educational Resources Information Center

Knowlton, Amy R.; Latkin, Carl A.

2007-01-01

The study examined multiple dimensions of social support as predictors of depressive symptoms among a highly vulnerable population. Social network analysis was used to assess perceived and enacted dimensions of support (emotional, financial, instrumental), network conflict, closeness, and composition. Participants were 393 current and former…

Unraveling Appalachia's Rural Economy: The Case of a Flexible Manufacturing Network.

ERIC Educational Resources Information Center

Oberhauser, Ann M.; Pratt, Amy; Turnage, Anne-Marie

2001-01-01

The growing importance of multiple-income strategies in the changing rural Appalachian economy is discussed via a case study of a network of female home-based machine-knitters. Social networks are an important part of the knitters' recruitment and training process, promote leadership development, and help overcome some of women's economic…

Artificial neural networks as quantum associative memory

NASA Astrophysics Data System (ADS)

Hamilton, Kathleen; Schrock, Jonathan; Imam, Neena; Humble, Travis

We present results related to the recall accuracy and capacity of Hopfield networks implemented on commercially available quantum annealers. The use of Hopfield networks and artificial neural networks as content-addressable memories offer robust storage and retrieval of classical information, however, implementation of these models using currently available quantum annealers faces several challenges: the limits of precision when setting synaptic weights, the effects of spurious spin-glass states and minor embedding of densely connected graphs into fixed-connectivity hardware. We consider neural networks which are less than fully-connected, and also consider neural networks which contain multiple sparsely connected clusters. We discuss the effect of weak edge dilution on the accuracy of memory recall, and discuss how the multiple clique structure affects the storage capacity. Our work focuses on storage of patterns which can be embedded into physical hardware containing n < 1000 qubits. This work was supported by the United States Department of Defense and used resources of the Computational Research and Development Programs as Oak Ridge National Laboratory under Contract No. DE-AC0500OR22725 with the U. S. Department of Energy.

Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

PubMed

Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

2018-04-01

A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

Passing Messages between Biological Networks to Refine Predicted Interactions

PubMed Central

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net. PMID:23741402

BioSYNTHESIS: access to a knowledge network of health sciences databases.

PubMed

Broering, N C; Hylton, J S; Guttmann, R; Eskridge, D

1991-04-01

Users of the IAIMS Knowledge Network at the Georgetown University Medical Center have access to multiple in-house and external databases from a single point of entry through BioSYNTHESIS. The IAIMS project has developed a rich environment of biomedical information resources that represent a medical decision support system for campus physicians and students. The BioSYNTHESIS system is an information navigator that provides transparent access to a Knowledge Network of over a dozen databases. These multiple health sciences databases consist of bibliographic, informational, diagnostic, and research systems which reside on diverse computers such as DEC VAXs, SUN 490, AT&T 3B2s, Macintoshes, IBM PC/PS2s and the AT&T ISN and SYTEK network systems. Ethernet and TCP/IP protocols are used in the network architecture. BioSYNTHESIS also provides network links to the other campus libraries and to external institutions. As additional knowledge resources and technological advances have become available. BioSYNTHESIS has evolved from a two phase to a three phase program. Major components of the system including recent achievements and future plans are described.

A method for exploring implicit concept relatedness in biomedical knowledge network.

PubMed

Bai, Tian; Gong, Leiguang; Wang, Ye; Wang, Yan; Kulikowski, Casimir A; Huang, Lan

2016-07-19

Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but implicit information or knowledge from it effectively and efficiently is of paramount importance for precision medicine, and a major challenge facing the biomedical research community. In this study, a hybrid biomedical knowledge network is constructed by linking concepts across multiple biomedical ontologies as well as non-structural biomedical knowledge sources. To discover implicit relatedness between concepts in ontologies for which potentially valuable relationships (implicit knowledge) may exist, we developed a Multi-Ontology Relatedness Model (MORM) within the knowledge network, for which a relatedness network (RN) is defined and computed across multiple ontologies using a formal inference mechanism of set-theoretic operations. Semantic constraints are designed and implemented to prune the search space of the relatedness network. Experiments to test examples of several biomedical applications have been carried out, and the evaluation of the results showed an encouraging potential of the proposed approach to biomedical knowledge discovery.

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

Threshold cascades with response heterogeneity in multiplex networks

NASA Astrophysics Data System (ADS)

Lee, Kyu-Min; Brummitt, Charles D.; Goh, K.-I.

2014-12-01

Threshold cascade models have been used to describe the spread of behavior in social networks and cascades of default in financial networks. In some cases, these networks may have multiple kinds of interactions, such as distinct types of social ties or distinct types of financial liabilities; furthermore, nodes may respond in different ways to influence from their neighbors of multiple types. To start to capture such settings in a stylized way, we generalize a threshold cascade model to a multiplex network in which nodes follow one of two response rules: some nodes activate when, in at least one layer, a large enough fraction of neighbors is active, while the other nodes activate when, in all layers, a large enough fraction of neighbors is active. Varying the fractions of nodes following either rule facilitates or inhibits cascades. Near the inhibition regime, global cascades appear discontinuously as the network density increases; however, the cascade grows more slowly over time. This behavior suggests a way in which various collective phenomena in the real world could appear abruptly yet slowly.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Designing allostery-inspired response in mechanical networks

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

Rocks, Jason W.; Pashine, Nidhi; Bischofberger, Irmgard

Recent advances in designing metamaterials have demonstrated that global mechanical properties of disordered spring networks can be tuned by selectively modifying only a small subset of bonds. Here, using a computationally efficient approach, we extend this idea to tune more general properties of networks. With nearly complete success, we are then able to produce a strain between any two target nodes in a network in response to an applied source strain on any other pair of nodes by removing only ~1% of the bonds. We are also able to control multiple pairs of target nodes, each with a different individualmore » response, from a single source, and to tune multiple independent source/target responses simultaneously into a network. We have fabricated physical networks in macroscopic 2D and 3D systems that exhibit these responses. This work is inspired by the long-range coupled conformational changes that constitute allosteric function in proteins. The fact that allostery is a common means for regulation in biological molecules suggests that it is a relatively easy property to develop through evolution. In analogy, our results show that long-range coupled mechanical responses are similarly easy to achieve in disordered networks.« less

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

Designing allostery-inspired response in mechanical networks

DOE PAGES

Rocks, Jason W.; Pashine, Nidhi; Bischofberger, Irmgard; ...

2017-02-21

Recent advances in designing metamaterials have demonstrated that global mechanical properties of disordered spring networks can be tuned by selectively modifying only a small subset of bonds. Here, using a computationally efficient approach, we extend this idea to tune more general properties of networks. With nearly complete success, we are then able to produce a strain between any two target nodes in a network in response to an applied source strain on any other pair of nodes by removing only ~1% of the bonds. We are also able to control multiple pairs of target nodes, each with a different individualmore » response, from a single source, and to tune multiple independent source/target responses simultaneously into a network. We have fabricated physical networks in macroscopic 2D and 3D systems that exhibit these responses. This work is inspired by the long-range coupled conformational changes that constitute allosteric function in proteins. The fact that allostery is a common means for regulation in biological molecules suggests that it is a relatively easy property to develop through evolution. In analogy, our results show that long-range coupled mechanical responses are similarly easy to achieve in disordered networks.« less

Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

PubMed Central

Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

2016-01-01

Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

A distributed incentive compatible pricing mechanism for P2P networks

NASA Astrophysics Data System (ADS)

Zhang, Jie; Zhao, Zheng; Xiong, Xiao; Shi, Qingwei

2007-09-01

Peer-to-Peer (P2P) systems are currently receiving considerable interest. However, as experience with P2P networks shows, the selfish behaviors of peers may lead to serious problems of P2P network, such as free-riding and white-washing. In order to solve these problems, there are increasing considerations on reputation system design in the study of P2P networks. Most of the existing works is concerning probabilistic estimation or social networks to evaluate the trustworthiness for a peer to others. However, these models can not be efficient all the time. In this paper, our aim is to provide a general mechanism that can maximize P2P networks social welfare in a way of Vickrey-Clarke-Groves family, while assuming every peer in P2P networks is rational and selfish, which means they only concern about their own outcome. This mechanism has some desirable properties using an O(n) algorithm: (1) incentive compatibility, every peer truly report its connection type; (2) individually rationality; and (3) fully decentralized, we design a multiple-principal multiple-agent model, concerning about the service provider and service requester individually.

Cross layer optimization for cloud-based radio over optical fiber networks

NASA Astrophysics Data System (ADS)

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong; Yang, Hui; Meng, Luoming

2016-07-01

To adapt the 5G communication, the cloud radio access network is a paradigm introduced by operators which aggregates all base stations computational resources into a cloud BBU pool. The interaction between RRH and BBU or resource schedule among BBUs in cloud have become more frequent and complex with the development of system scale and user requirement. It can promote the networking demand among RRHs and BBUs, and force to form elastic optical fiber switching and networking. In such network, multiple stratum resources of radio, optical and BBU processing unit have interweaved with each other. In this paper, we propose a novel multiple stratum optimization (MSO) architecture for cloud-based radio over optical fiber networks (C-RoFN) with software defined networking. Additionally, a global evaluation strategy (GES) is introduced in the proposed architecture. MSO can enhance the responsiveness to end-to-end user demands and globally optimize radio frequency, optical spectrum and BBU processing resources effectively to maximize radio coverage. The feasibility and efficiency of the proposed architecture with GES strategy are experimentally verified on OpenFlow-enabled testbed in terms of resource occupation and path provisioning latency.

Designing allostery-inspired response in mechanical networks

PubMed Central

Rocks, Jason W.; Pashine, Nidhi; Bischofberger, Irmgard; Goodrich, Carl P.; Liu, Andrea J.; Nagel, Sidney R.

2017-01-01

Recent advances in designing metamaterials have demonstrated that global mechanical properties of disordered spring networks can be tuned by selectively modifying only a small subset of bonds. Here, using a computationally efficient approach, we extend this idea to tune more general properties of networks. With nearly complete success, we are able to produce a strain between any two target nodes in a network in response to an applied source strain on any other pair of nodes by removing only ∼1% of the bonds. We are also able to control multiple pairs of target nodes, each with a different individual response, from a single source, and to tune multiple independent source/target responses simultaneously into a network. We have fabricated physical networks in macroscopic 2D and 3D systems that exhibit these responses. This work is inspired by the long-range coupled conformational changes that constitute allosteric function in proteins. The fact that allostery is a common means for regulation in biological molecules suggests that it is a relatively easy property to develop through evolution. In analogy, our results show that long-range coupled mechanical responses are similarly easy to achieve in disordered networks. PMID:28223534

Designing allostery-inspired response in mechanical networks.

PubMed

Rocks, Jason W; Pashine, Nidhi; Bischofberger, Irmgard; Goodrich, Carl P; Liu, Andrea J; Nagel, Sidney R

2017-03-07

Recent advances in designing metamaterials have demonstrated that global mechanical properties of disordered spring networks can be tuned by selectively modifying only a small subset of bonds. Here, using a computationally efficient approach, we extend this idea to tune more general properties of networks. With nearly complete success, we are able to produce a strain between any two target nodes in a network in response to an applied source strain on any other pair of nodes by removing only ∼1% of the bonds. We are also able to control multiple pairs of target nodes, each with a different individual response, from a single source, and to tune multiple independent source/target responses simultaneously into a network. We have fabricated physical networks in macroscopic 2D and 3D systems that exhibit these responses. This work is inspired by the long-range coupled conformational changes that constitute allosteric function in proteins. The fact that allostery is a common means for regulation in biological molecules suggests that it is a relatively easy property to develop through evolution. In analogy, our results show that long-range coupled mechanical responses are similarly easy to achieve in disordered networks.

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

Wu, Chase

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align andmore » transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections.« less

Efficient traffic grooming with dynamic ONU grouping for multiple-OLT-based access network

NASA Astrophysics Data System (ADS)

Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Wang, Hongxiang

2015-12-01

Fast bandwidth growth urges large-scale high-density access scenarios, where the multiple Passive Optical Networking (PON) system clustered deployment can be adopted as an appropriate solution to fulfill the huge bandwidth demands, especially for a future 5G mobile network. However, the lack of interaction between different optical line terminals (OLTs) results in part of the bandwidth resources waste. To increase the bandwidth efficiency, as well as reduce bandwidth pressure at the edge of a network, we propose a centralized flexible PON architecture based on Time- and Wavelength-Division Multiplexing PON (TWDM PON). It can provide flexible affiliation for optical network units (ONUs) and different OLTs to support access network traffic localization. Specifically, a dynamic ONU grouping algorithm (DGA) is provided to obtain the minimal OLT outbound traffic. Simulation results show that DGA obtains an average 25.23% traffic gain increment under different OLT numbers within a small ONU number situation, and the traffic gain will increase dramatically with the increment of the ONU number. As the DGA can be deployed easily as an application running above the centralized control plane, the proposed architecture can be helpful to improve the network efficiency for future traffic-intensive access scenarios.

Research on a Queue Scheduling Algorithm in Wireless Communications Network

NASA Astrophysics Data System (ADS)

Yang, Wenchuan; Hu, Yuanmei; Zhou, Qiancai

This paper proposes a protocol QS-CT, Queue Scheduling Mechanism based on Multiple Access in Ad hoc net work, which adds queue scheduling mechanism to RTS-CTS-DATA using multiple access protocol. By endowing different queues different scheduling mechanisms, it makes networks access to the channel much more fairly and effectively, and greatly enhances the performance. In order to observe the final performance of the network with QS-CT protocol, we simulate it and compare it with MACA/C-T without QS-CT protocol. Contrast to MACA/C-T, the simulation result shows that QS-CT has greatly improved the throughput, delay, rate of packets' loss and other key indicators.

Large File Transfers from Space Using Multiple Ground Terminals and Delay-Tolerant Networking

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Paulsen, Phillip; Stewart, Dave; Eddy, Wesley; McKim, James; Taylor, John; Lynch, Scott; Heberle, Jay; Northam, James; Jackson, Chris;

End-to-End Network QoS via Scheduling of Flexible Resource Reservation Requests

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

Sharma, S.; Katramatos, D.; Yu, D.

2011-11-14

Modern data-intensive applications move vast amounts of data between multiple locations around the world. To enable predictable and reliable data transfer, next generation networks allow such applications to reserve network resources for exclusive use. In this paper, we solve an important problem (called SMR3) to accommodate multiple and concurrent network reservation requests between a pair of end-sites. Given the varying availability of bandwidth within the network, our goal is to accommodate as many reservation requests as possible while minimizing the total time needed to complete the data transfers. We first prove that SMR3 is an NP-hard problem. Then we solvemore » it by developing a polynomial-time heuristic, called RRA. The RRA algorithm hinges on an efficient mechanism to accommodate large number of requests by minimizing the bandwidth wastage. Finally, via numerical results, we show that RRA constructs schedules that accommodate significantly larger number of requests compared to other, seemingly efficient, heuristics.« less

DMP: Detouring Using Multiple Paths against Jamming Attack for Ubiquitous Networking System

PubMed Central

Kim, Mihui; Chae, Kijoon

2010-01-01

To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio) and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector), and a conventional JAM (Jammed Area Mapping) service with one reroute. PMID:22319316

On Deployment of Multiple Base Stations for Energy-Efficient Communication in Wireless Sensor Networks

DOE PAGES

Lin, Yunyue; Wu, Qishi; Cai, Xiaoshan; ...

2010-01-01

Data transmission from sensor nodes to a base station or a sink node often incurs significant energy consumption, which critically affects network lifetime. We generalize and solve the problem of deploying multiple base stations to maximize network lifetime in terms of two different metrics under one-hop and multihop communication models. In the one-hop communication model, the sensors far away from base stations always deplete their energy much faster than others. We propose an optimal solution and a heuristic approach based on the minimal enclosing circle algorithm to deploy a base station at the geometric center of each cluster. In themore » multihop communication model, both base station location and data routing mechanism need to be considered in maximizing network lifetime. We propose an iterative algorithm based on rigorous mathematical derivations and use linear programming to compute the optimal routing paths for data transmission. Simulation results show the distinguished performance of the proposed deployment algorithms in maximizing network lifetime.« less

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

NASA Astrophysics Data System (ADS)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

DMP: detouring using multiple paths against jamming attack for ubiquitous networking system.

PubMed

Kim, Mihui; Chae, Kijoon

2010-01-01

To successfully realize the ubiquitous network environment including home automation or industrial control systems, it is important to be able to resist a jamming attack. This has recently been considered as an extremely threatening attack because it can collapse the entire network, despite the existence of basic security protocols such as encryption and authentication. In this paper, we present a method of jamming attack tolerant routing using multiple paths based on zones. The proposed scheme divides the network into zones, and manages the candidate forward nodes of neighbor zones. After detecting an attack, detour nodes decide zones for rerouting, and detour packets destined for victim nodes through forward nodes in the decided zones. Simulation results show that our scheme increases the PDR (Packet Delivery Ratio) and decreases the delay significantly in comparison with rerouting by a general routing protocol on sensor networks, AODV (Ad hoc On Demand Distance Vector), and a conventional JAM (Jammed Area Mapping) service with one reroute.

Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility.

PubMed

Bagot, Rosemary C; Cates, Hannah M; Purushothaman, Immanuel; Lorsch, Zachary S; Walker, Deena M; Wang, Junshi; Huang, Xiaojie; Schlüter, Oliver M; Maze, Ian; Peña, Catherine J; Heller, Elizabeth A; Issler, Orna; Wang, Minghui; Song, Won-Min; Stein, Jason L; Liu, Xiaochuan; Doyle, Marie A; Scobie, Kimberly N; Sun, Hao Sheng; Neve, Rachael L; Geschwind, Daniel; Dong, Yan; Shen, Li; Zhang, Bin; Nestler, Eric J

2016-06-01

Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Collaboration and co-production of climate knowledge: lessons from a network on the front-line

NASA Astrophysics Data System (ADS)

Kettle, N.

2016-12-01

The science-practice gap is broadly considered a major barrier to the production and application of decision-relevant science. This study uses a social network analysis, based on 126 interviews, to analyze the roles and network ties among climate scientists, service providers, and decision makers in Alaska. Our research highlights the importance of key actors and significant differences in bonding and bridging ties across roles - structural characteristics that provide a basis for informing recommendations to build adaptive capacity and support the co-production of knowledge. Our findings also illustrate that some individuals in the network engage in multiple roles, suggesting that conceptualizing the science-practice interface as consisting of "producers" and "consumers" oversimplifies how individuals engage in climate science, services, and decision making. This research supports the notion that the development and use of climate information is a networked phenomenon. It also emphasizes the importance of centralized individuals who are capable of engaging in multiple roles for the transition of knowledge action.

Case Study: An Ethics Case Study of HIV Prevention Research on Facebook: The Just/Us Study

PubMed Central

Breslin, Lindsey T.; Wright, Erin E.; Black, Sandra R.; Levine, Deborah; Santelli, John S.

2011-01-01

Objective To consider issues related to research with youth on social networking sites online. Methods Description of the data collection process from 1,588 participants in a randomized controlled trial testing the efficacy of HIV prevention education delivered on Facebook. Using respondent-driven sampling, staff-recruited participants are encouraged to recruit up to three friends to enroll in the study. Results Researchers should (a) consider whether an online social networking site is an appropriate place to implement a research study; (b) offer opportunities to review informed consent documents at multiple times and in multiple locations throughout the study; and (c) collect data outside the social networking site and store it behind secure firewalls to ensure it will not be accessible to any person on the social networking site. Conclusions Online social networks are growing in popularity. Conducting research on social media sites requires deliberate attention to consent, confidentiality, and security. PMID:21292724

Stability and change in sustainability of daily routines and social networks in families of children with profound intellectual and multiple disabilities.

PubMed

Wilder, Jenny; Granlund, Mats

2015-03-01

Children with profound intellectual and multiple disabilities (PIMD) demand intense family accommodations from birth and onwards. This study used an exploratory and qualitative study design to investigate stability and change in sustainability of daily routines and social networks of Swedish families of children with PIMD. Eight families participated over two years in eco-cultural family interviews and social networks interviews collected at home visits. Data were analyzed descriptively and by manifest contents analysis. Results showed variations in sustainability of daily routines over time across families. The sustainability was linked to fathers' involvement, couples' connectedness and emotional support. Stability and change of social networks were characterized by low overlap between the child and family networks, the children's communicative dependency and low density of able communication partners. The results indicate that patterns of stability and change were linked both to family resources and child characteristics. © 2014 John Wiley & Sons Ltd.

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

PubMed Central

Hsin, Kun-Yi; Ghosh, Samik; Kitano, Hiroaki

2013-01-01

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate. PMID:24391846

Machine Learning Technique to Find Quantum Many-Body Ground States of Bosons on a Lattice

NASA Astrophysics Data System (ADS)

Saito, Hiroki; Kato, Masaya

2018-01-01

We have developed a variational method to obtain many-body ground states of the Bose-Hubbard model using feedforward artificial neural networks. A fully connected network with a single hidden layer works better than a fully connected network with multiple hidden layers, and a multilayer convolutional network is more efficient than a fully connected network. AdaGrad and Adam are optimization methods that work well. Moreover, we show that many-body ground states with different numbers of particles can be generated by a single network.

Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

PubMed Central

2018-01-01

Abstract It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate in multiple spike sequences at multiple between-spike time delays, the possible complexity of networks is prohibitively large. We present a novel approach that is capable of (1) extracting spike timing networks regardless of their sequence complexity, and (2) that describes their spiking sequences with high temporal precision. We achieve this by decomposing frequency-transformed neuronal spiking into separate networks, characterizing each network’s spike sequence by a time delay per neuron, forming a spike sequence timeline. These networks provide a detailed template for an investigation of the experimental relevance of their spike sequences. Using simulated spike timing networks, we show network extraction is robust to spiking noise, spike timing jitter, and partial occurrences of the involved spike sequences. Using rat multineuron recordings, we demonstrate the approach is capable of revealing real spike timing networks with sub-millisecond temporal precision. By uncovering spike timing networks, the prevalence, structure, and function of complex spike sequences can be investigated in greater detail, allowing us to gain a better understanding of their role in neuronal functioning. PMID:29789811