Advanced information processing system: Input/output network management software

Science.gov (United States)

Nagle, Gail; Alger, Linda; Kemp, Alexander

1988-01-01

The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

Intermodel freight terminals: marketing channels and telecommunication networks

NARCIS (Netherlands)

Wiegmans, B.W.; Nijkamp, P.; Masurel, E.

2001-01-01

This paper seeks to highlight the importance of modern telecommunications networks in combined transport marketing channels deployed for intermodal terminals. To develop a customer-based and broadly applicable framework for studying combined freight transport in Europe, the use of the marketing

Virtualized Networks and Virtualized Optical Line Terminal (vOLT)

Science.gov (United States)

Ma, Jonathan; Israel, Stephen

2017-03-01

The success of the Internet and the proliferation of the Internet of Things (IoT) devices is forcing telecommunications carriers to re-architecture a central office as a datacenter (CORD) so as to bring the datacenter economics and cloud agility to a central office (CO). The Open Network Operating System (ONOS) is the first open-source software-defined network (SDN) operating system which is capable of managing and controlling network, computing, and storage resources to support CORD infrastructure and network virtualization. The virtualized Optical Line Termination (vOLT) is one of the key components in such virtualized networks.

An expert system for configuring a network for a Milstar terminal

Science.gov (United States)

Mahoney, Melissa J.; Wilson, Elizabeth J.

1994-01-01

This paper describes a rule-based expert system which assists the user in configuring a network for Air Force terminals using the Milstar satellite system. The network configuration expert system approach uses CLIPS. The complexity of network configuration is discussed, and the methods used to model it are described.

Event-triggered output feedback control for distributed networked systems.

Science.gov (United States)

Mahmoud, Magdi S; Sabih, Muhammad; Elshafei, Moustafa

2016-01-01

This paper addresses the problem of output-feedback communication and control with event-triggered framework in the context of distributed networked control systems. The design problem of the event-triggered output-feedback control is proposed as a linear matrix inequality (LMI) feasibility problem. The scheme is developed for the distributed system where only partial states are available. In this scheme, a subsystem uses local observers and share its information to its neighbors only when the subsystem's local error exceeds a specified threshold. The developed method is illustrated by using a coupled cart example from the literature. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Utilization of INIS output in Czechoslovakia

International Nuclear Information System (INIS)

Stanik, Z.; Blazek, J.

1978-01-01

Information on INIS output materials - INIS magnetic tape, INIS Atomindex, full texts of non-conventional literature on microfiches. Complex is provided of INIS-SDI service by the Nuclear Information Centre for CSSR. The Unified Software System (USS) of the UVTEI-UTZ (the Central Technical Base of the Central Office for Scientific, Technical and Economic Information) is used for the automated processing of INIS magnetic tapes. A survey of INIS-SDI services in the years 1974 to 1978 is given. The further development of the system consists in the use of the terminal network, with direct access to the IAEA computer in Vienna. (author)

A Markovian model of evolving world input-output network.

Directory of Open Access Journals (Sweden)

Vahid Moosavi

Full Text Available The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

A Markovian model of evolving world input-output network.

Science.gov (United States)

Moosavi, Vahid; Isacchini, Giulio

2017-01-01

The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.

Topology Detection for Output-Coupling Weighted Complex Dynamical Networks with Coupling and Transmission Delays

Directory of Open Access Journals (Sweden)

Xinwei Wang

2017-01-01

Full Text Available Topology detection for output-coupling weighted complex dynamical networks with two types of time delays is investigated in this paper. Different from existing literatures, coupling delay and transmission delay are simultaneously taken into account in the output-coupling network. Based on the idea of the state observer, we build the drive-response system and apply LaSalle’s invariance principle to the error dynamical system of the drive-response system. Several convergent criteria are deduced in the form of algebraic inequalities. Some numerical simulations for the complex dynamical network, with node dynamics being chaotic, are given to verify the effectiveness of the proposed scheme.

Modelling innovation performance of European regions using multi-output neural networks.

Science.gov (United States)

Hajek, Petr; Henriques, Roberto

2017-01-01

Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Modelling innovation performance of European regions using multi-output neural networks.

Directory of Open Access Journals (Sweden)

Petr Hajek

Full Text Available Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.

Long-running telemedicine networks delivering humanitarian services: experience, performance and scientific output

Science.gov (United States)

Geissbuhler, Antoine; Jethwani, Kamal; Kovarik, Carrie; Person, Donald A; Vladzymyrskyy, Anton; Zanaboni, Paolo; Zolfo, Maria

2012-01-01

Abstract Objective To summarize the experience, performance and scientific output of long-running telemedicine networks delivering humanitarian services. Methods Nine long-running networks – those operating for five years or more– were identified and seven provided detailed information about their activities, including performance and scientific output. Information was extracted from peer-reviewed papers describing the networks’ study design, effectiveness, quality, economics, provision of access to care and sustainability. The strength of the evidence was scored as none, poor, average or good. Findings The seven networks had been operating for a median of 11 years (range: 5–15). All networks provided clinical tele-consultations for humanitarian purposes using store-and-forward methods and five were also involved in some form of education. The smallest network had 15 experts and the largest had more than 500. The clinical caseload was 50 to 500 cases a year. A total of 59 papers had been published by the networks, and 44 were listed in Medline. Based on study design, the strength of the evidence was generally poor by conventional standards (e.g. 29 papers described non-controlled clinical series). Over half of the papers provided evidence of sustainability and improved access to care. Uncertain funding was a common risk factor. Conclusion Improved collaboration between networks could help attenuate the lack of resources reported by some networks and improve sustainability. Although the evidence base is weak, the networks appear to offer sustainable and clinically useful services. These findings may interest decision-makers in developing countries considering starting, supporting or joining similar telemedicine networks. PMID:22589567

Quaternion-based adaptive output feedback attitude control of spacecraft using Chebyshev neural networks.

Science.gov (United States)

Zou, An-Min; Dev Kumar, Krishna; Hou, Zeng-Guang

2010-09-01

This paper investigates the problem of output feedback attitude control of an uncertain spacecraft. Two robust adaptive output feedback controllers based on Chebyshev neural networks (CNN) termed adaptive neural networks (NN) controller-I and adaptive NN controller-II are proposed for the attitude tracking control of spacecraft. The four-parameter representations (quaternion) are employed to describe the spacecraft attitude for global representation without singularities. The nonlinear reduced-order observer is used to estimate the derivative of the spacecraft output, and the CNN is introduced to further improve the control performance through approximating the spacecraft attitude motion. The implementation of the basis functions of the CNN used in the proposed controllers depends only on the desired signals, and the smooth robust compensator using the hyperbolic tangent function is employed to counteract the CNN approximation errors and external disturbances. The adaptive NN controller-II can efficiently avoid the over-estimation problem (i.e., the bound of the CNNs output is much larger than that of the approximated unknown function, and hence, the control input may be very large) existing in the adaptive NN controller-I. Both adaptive output feedback controllers using CNN can guarantee that all signals in the resulting closed-loop system are uniformly ultimately bounded. For performance comparisons, the standard adaptive controller using the linear parameterization of spacecraft attitude motion is also developed. Simulation studies are presented to show the advantages of the proposed CNN-based output feedback approach over the standard adaptive output feedback approach.

Optical terminal requirements for aeronautical multi-hop networks

Science.gov (United States)

Karras, Kimon; Marinos, Dimitris; Kouros, Pavlos

2008-08-01

High speed free space optical data links are currently finding limited use in military aircraft; however the technology is slowly starting to diffuse to civilian applications, where they could be used to provide a high bandwidth connection. However there are several issues that have to be resolved before the technology is ready for deployment. An important part of these are physical layer issues which deal with the ability to transmit and receive the optical signal reliably, as well as mechanical issues which focus on the construction of high performance, small and lightweight terminals for the optical transceiver. The later in conjunction with the cost of such a terminal create a significant limitation on the number of such equipment that any aircraft might carry on board. This paper attempts to evaluate how various such parameters affect the capability of an aircraft to take part in and help form a mesh network. The study was conducted by modeling the aircraft into a custom built SystemC based simulator tool and evaluating the connectivity achieved for varying several parameters, such as the pointing and acquisition time of the terminal and the number of terminals on board.

Designing a Pattern Recognition Neural Network with a Reject Output and Many Sets of Weights and Biases

OpenAIRE

Dung, Le; Mizukawa, Makoto

2008-01-01

Adding the reject output to the pattern recognition neural network is an approach to help the neural network can classify almost all patterns of a training data set by using many sets of weights and biases, even if the neural network is small. With a smaller number of neurons, we can implement the neural network on a hardware-based platform more easily and also reduce the response time of it. With the reject output the neural network can produce not only right or wrong results but also reject...

Output regulation of large-scale hydraulic networks with minimal steady state power consumption

NARCIS (Netherlands)

Jensen, Tom Nørgaard; Wisniewski, Rafał; De Persis, Claudio; Kallesøe, Carsten Skovmose

2014-01-01

An industrial case study involving a large-scale hydraulic network is examined. The hydraulic network underlies a district heating system, with an arbitrary number of end-users. The problem of output regulation is addressed along with a optimization criterion for the control. The fact that the

Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy

Science.gov (United States)

Khambhati, Ankit N.; Davis, Kathryn A.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.; Litt, Brian; Bassett, Danielle S.

2015-01-01

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. PMID:26680762

Synchronization of chaotic neural networks via output or state coupling

International Nuclear Information System (INIS)

Lu Hongtao; Leeuwen, C. van

2006-01-01

We consider the problem of global exponential synchronization between two identical chaotic neural networks that are linearly and unidirectionally coupled. We formulate a general framework for the synchronization problem in which one chaotic neural network, working as the driving system (or master), sends its output or state values to the other, which serves as the response system (or slave). We use Lyapunov functions to establish general theoretical conditions for designing the coupling matrix. Neither symmetry nor negative (positive) definiteness of the coupling matrix are required; under less restrictive conditions, the two coupled chaotic neural networks can achieve global exponential synchronization regardless of their initial states. Detailed comparisons with existing results are made and numerical simulations are carried out to demonstrate the effectiveness of the established synchronization laws

SOLAR PHOTOVOLTAIC OUTPUT POWER FORECASTING USING BACK PROPAGATION NEURAL NETWORK

Directory of Open Access Journals (Sweden)

B. Jency Paulin

2016-01-01

Full Text Available Solar Energy is an important renewable and unlimited source of energy. Solar photovoltaic power forecasting, is an estimation of the expected power production, that help the grid operators to better manage the electric balance between power demand and supply. Neural network is a computational model that can predict new outcomes from past trends. The artificial neural network is used for photovoltaic plant energy forecasting. The output power for solar photovoltaic cell is predicted on hourly basis. In historical dataset collection process, two dataset was collected and used for analysis. The dataset was provided with three independent attributes and one dependent attributes. The implementation of Artificial Neural Network structure is done by Multilayer Perceptron (MLP and training procedure for neural network is done by error Back Propagation (BP. In order to train and test the neural network, the datasets are divided in the ratio 70:30. The accuracy of prediction can be done by using various error measurement criteria and the performance of neural network is to be noted.

47 CFR 68.110 - Compatibility of the public switched telephone network and terminal equipment.

Science.gov (United States)

2010-10-01

... changes in its communications facilities, equipment, operations or procedures, where such action is... in this part. If such changes can be reasonably expected to render any customer's terminal equipment... network and terminal equipment. 68.110 Section 68.110 Telecommunication FEDERAL COMMUNICATIONS COMMISSION...

A Context-Aware Adaptive Streaming Media Distribution System in a Heterogeneous Network with Multiple Terminals

Directory of Open Access Journals (Sweden)

Yepeng Ni

2016-01-01

Full Text Available We consider the problem of streaming media transmission in a heterogeneous network from a multisource server to home multiple terminals. In wired network, the transmission performance is limited by network state (e.g., the bandwidth variation, jitter, and packet loss. In wireless network, the multiple user terminals can cause bandwidth competition. Thus, the streaming media distribution in a heterogeneous network becomes a severe challenge which is critical for QoS guarantee. In this paper, we propose a context-aware adaptive streaming media distribution system (CAASS, which implements the context-aware module to perceive the environment parameters and use the strategy analysis (SA module to deduce the most suitable service level. This approach is able to improve the video quality for guarantying streaming QoS. We formulate the optimization problem of QoS relationship with the environment parameters based on the QoS testing algorithm for IPTV in ITU-T G.1070. We evaluate the performance of the proposed CAASS through 12 types of experimental environments using a prototype system. Experimental results show that CAASS can dynamically adjust the service level according to the environment variation (e.g., network state and terminal performances and outperforms the existing streaming approaches in adaptive streaming media distribution according to peak signal-to-noise ratio (PSNR.

Justification of the project a network of freight terminals unitized cargo

Directory of Open Access Journals (Sweden)

Ilesaliev D.I.

2016-12-01

Full Text Available In this paper we consider the question of Uzbekistan in promoting the development of international transport in supply chains. The development of transport infrastructure to ensure timely delivery of goods is one of the main tasks in supply chain management. The aim is to study of the project network terminal unitized cargo Uzbekistan in supply chains. Methods the study is based on analysis of existing methods and techniques of Russian scientists in the field of place-ment of objects. The method of searching the most rational location of logistics facility in the supply chain. Also pre-justified the project network terminal unitized cargo in Uzbekistan. Given the state of the problems and prospects of transport logistics of Uzbekistan, the developed method can be used by experts when performing the supporting calcula-tions location of logistic objects.

47 CFR 15.115 - TV interface devices, including cable system terminal devices.

Science.gov (United States)

2010-10-01

... output terminal(s) of the device terminated by a resistance equal to the rated output impedance. The...: (1) At any RF output terminal, the maximum measured RMS voltage, in microvolts, corresponding to the peak envelope power of the modulated signal during maximum amplitude peaks across a resistance (R in...

LARGE-scale forest fuel supply solution trough a regional terminal network; Terminaalitoimintoihin perustuvan metsaepolttoaineen hankintalogistiikkajaerjestelmaen kehittaeminen

Energy Technology Data Exchange (ETDEWEB)

Leppaenen, T. [Etelae-Savon Energia Oy, Mikkeli (Finland)

2006-12-19

The aim of the study is to develop logistic systems for supply of forest fuel where a terminal is part of the supply chain. Operations in the terminal, supply chains of the forest fuel and joining them to the terminal network are testing and following p. Also operation and business models are under analyzing. Costs, cost factors, benefits and space requirement of the terminal and cost-effectiveness of the entrepreneurship of the terminal are carried out. (orig.)

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

OpenAIRE

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-01-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solv...

A Dual-Buck–Boost AC/DC Converter for DC Nanogrid With Three Terminal Outputs

DEFF Research Database (Denmark)

Wu, Weimin; Wang, Houqing; Liu, Yuan

2017-01-01

Due to the widely used dc characterized loads and more distributed power generation sources, the dc nanogrid becomes more and more popular, and it is seen as an alternative to the ac grid. For safety considerations, the dc nanogrid should provide reliable grounding for the residential loads...... such as the low-voltage ac power system. There are three typical grounding configurations for a dc nanogrid: the united grounding, the unidirectional grounding, and the virtual isolated grounding. Each grounding configuration has its own specifications to ac/dc converters. In this paper, a dual-buck-boost ac/dc...... converter for use in the united-grounding-configuration-based dc nanogrid with three terminal outputs is proposed. The working principle of this converter is presented in detail through analyzing the equivalent circuits. Experiments are carried out to verify the theoretical analysis....

Network Patterns of Inventor Collaboration and Their Effects on Innovation Outputs

Directory of Open Access Journals (Sweden)

Wonchang Hur

2016-03-01

Full Text Available The purpose of this study is to examine how the collaboration structure among inventors in an R and D organization affects its capability to create impactful innovations. Specifically, this study is focused on examining whether a certain type of network mechanism found in collaboration among inventors contributes more to enhancing the future impacts of collaboration outputs, which is represented by the forward citations of their patents. To this end, co-invention networks for R and D organizations are constructed from an inventor-patent database, and the three structural patterns are measured by using network analytic constructs, namely, structural holes, strength of ties, and centralization. The results show that the presence of structural holes and strong ties are positively associated with the increasing forward citations, and that decentralized collaboration has also a positive impact. The findings offer support for both structural hole and network closure perspectives on social capital, which have been considered contradictive in the literature.

Analysis of network motifs in cellular regulation: Structural similarities, input-output relations and signal integration.

Science.gov (United States)

Straube, Ronny

2017-12-01

Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.

Visual communication and terminal equipment

International Nuclear Information System (INIS)

Kang, Cheol Hui

1988-06-01

This book is divided two parts about visual communication and terminal equipment. The first part introduces visual communication, which deals with foundation of visual communication, technique of visual communication, equipment of visual communication, a facsimile and pictorial image system. The second part contains terminal equipment such as telephone, terminal equipment for data transmission on constitution and constituent of terminal equipment for data transmission, input device and output device, terminal device and up-to-date terminal device.

Visual communication and terminal equipment

Energy Technology Data Exchange (ETDEWEB)

Kang, Cheol Hui

1988-06-15

This book is divided two parts about visual communication and terminal equipment. The first part introduces visual communication, which deals with foundation of visual communication, technique of visual communication, equipment of visual communication, a facsimile and pictorial image system. The second part contains terminal equipment such as telephone, terminal equipment for data transmission on constitution and constituent of terminal equipment for data transmission, input device and output device, terminal device and up-to-date terminal device.

Lazy Productivity via Termination

NARCIS (Netherlands)

Endrullis, J.; Hendriks, R.D.A.

2011-01-01

We present a procedure for transforming strongly sequential constructor-based term rewriting systems (TRSs) into context-sensitive TRSs in such a way that productivity of the input system is equivalent to termination of the output system. Thereby automated termination provers become available for

GBNV encoded movement protein (NSm) remodels ER network via C-terminal coiled coil domain

Energy Technology Data Exchange (ETDEWEB)

Singh, Pratibha; Savithri, H.S., E-mail: bchss@biochem.iisc.ernet.in

2015-08-15

Plant viruses exploit the host machinery for targeting the viral genome–movement protein complex to plasmodesmata (PD). The mechanism by which the non-structural protein m (NSm) of Groundnut bud necrosis virus (GBNV) is targeted to PD was investigated using Agrobacterium mediated transient expression of NSm and its fusion proteins in Nicotiana benthamiana. GFP:NSm formed punctuate structures that colocalized with mCherry:plasmodesmata localized protein 1a (PDLP 1a) confirming that GBNV NSm localizes to PD. Unlike in other movement proteins, the C-terminal coiled coil domain of GBNV NSm was shown to be involved in the localization of NSm to PD, as deletion of this domain resulted in the cytoplasmic localization of NSm. Treatment with Brefeldin A demonstrated the role of ER in targeting GFP NSm to PD. Furthermore, mCherry:NSm co-localized with ER–GFP (endoplasmic reticulum targeting peptide (HDEL peptide fused with GFP). Co-expression of NSm with ER–GFP showed that the ER-network was transformed into vesicles indicating that NSm interacts with ER and remodels it. Mutations in the conserved hydrophobic region of NSm (residues 130–138) did not abolish the formation of vesicles. Additionally, the conserved prolines at positions 140 and 142 were found to be essential for targeting the vesicles to the cell membrane. Further, systematic deletion of amino acid residues from N- and C-terminus demonstrated that N-terminal 203 amino acids are dispensable for the vesicle formation. On the other hand, the C-terminal coiled coil domain when expressed alone could also form vesicles. These results suggest that GBNV NSm remodels the ER network by forming vesicles via its interaction through the C-terminal coiled coil domain. Interestingly, NSm interacts with NP in vitro and coexpression of these two proteins in planta resulted in the relocalization of NP to PD and this relocalization was abolished when the N-terminal unfolded region of NSm was deleted. Thus, the NSm

Optimizing the Number of Cooperating Terminals for Energy Aware Task Computing in Wireless Networks

DEFF Research Database (Denmark)

Olsen, Anders Brødløs; Fitzek, Frank H. P.; Koch, Peter

2005-01-01

It is generally accepted that energy consumption is a significant design constraint for mobile handheld systems, therefore motivations for methods optimizing the energy consumption making better use of the restricted battery resources are evident. A novel concept of distributed task computing...... is previously proposed (D2VS), where the overall idea of selective distribution of tasks among terminals is made. In this paper the optimal number of terminals for cooperative task computing in a wireless network will be investigated. The paper presents an energy model for the proposed scheme. Energy...... consumption of the terminals with respect to their workload and the overhead of distributing tasks among terminals are taken into account. The paper shows, that the number of cooperating terminals is in general limited to a few, though alternating with respect to the various system parameters....

Trends of the World Input and Output Network of Global Trade.

Science.gov (United States)

Del Río-Chanona, Rita María; Grujić, Jelena; Jeldtoft Jensen, Henrik

2017-01-01

The international trade naturally maps onto a complex networks. Theoretical analysis of this network gives valuable insights about the global economic system. Although different economic data sets have been investigated from the network perspective, little attention has been paid to its dynamical behaviour. Here we take the World Input Output Data set, which has values of the annual transactions between 40 different countries of 35 different sectors for the period of 15 years, and infer the time interdependence between countries and sectors. As a measure of interdependence we use correlations between various time series of the network characteristics. First we form 15 primary networks for each year of the data we have, where nodes are countries and links are annual exports from one country to the other. Then we calculate the strengths (weighted degree) and PageRank of each country in each of the 15 networks for 15 different years. This leads to sets of time series and by calculating the correlations between these we form a secondary network where the links are the positive correlations between different countries or sectors. Furthermore, we also form a secondary network where the links are negative correlations in order to study the competition between countries and sectors. By analysing this secondary network we obtain a clearer picture of the mutual influences between countries. As one might expect, we find that political and geographical circumstances play an important role. However, the derived correlation network reveals surprising aspects which are hidden in the primary network. Sometimes countries which belong to the same community in the original network are found to be competitors in the secondary networks. E.g. Spain and Portugal are always in the same trade flow community, nevertheless secondary network analysis reveal that they exhibit contrary time evolution.

Trends of the World Input and Output Network of Global Trade.

Directory of Open Access Journals (Sweden)

Rita María Del Río-Chanona

Full Text Available The international trade naturally maps onto a complex networks. Theoretical analysis of this network gives valuable insights about the global economic system. Although different economic data sets have been investigated from the network perspective, little attention has been paid to its dynamical behaviour. Here we take the World Input Output Data set, which has values of the annual transactions between 40 different countries of 35 different sectors for the period of 15 years, and infer the time interdependence between countries and sectors. As a measure of interdependence we use correlations between various time series of the network characteristics. First we form 15 primary networks for each year of the data we have, where nodes are countries and links are annual exports from one country to the other. Then we calculate the strengths (weighted degree and PageRank of each country in each of the 15 networks for 15 different years. This leads to sets of time series and by calculating the correlations between these we form a secondary network where the links are the positive correlations between different countries or sectors. Furthermore, we also form a secondary network where the links are negative correlations in order to study the competition between countries and sectors. By analysing this secondary network we obtain a clearer picture of the mutual influences between countries. As one might expect, we find that political and geographical circumstances play an important role. However, the derived correlation network reveals surprising aspects which are hidden in the primary network. Sometimes countries which belong to the same community in the original network are found to be competitors in the secondary networks. E.g. Spain and Portugal are always in the same trade flow community, nevertheless secondary network analysis reveal that they exhibit contrary time evolution.

The Input-Output Relationship of the Cholinergic Basal Forebrain

Directory of Open Access Journals (Sweden)

Matthew R. Gielow

2017-02-01

Full Text Available Basal forebrain cholinergic neurons influence cortical state, plasticity, learning, and attention. They collectively innervate the entire cerebral cortex, differentially controlling acetylcholine efflux across different cortical areas and timescales. Such control might be achieved by differential inputs driving separable cholinergic outputs, although no input-output relationship on a brain-wide level has ever been demonstrated. Here, we identify input neurons to cholinergic cells projecting to specific cortical regions by infecting cholinergic axon terminals with a monosynaptically restricted viral tracer. This approach revealed several circuit motifs, such as central amygdala neurons synapsing onto basolateral amygdala-projecting cholinergic neurons or strong somatosensory cortical input to motor cortex-projecting cholinergic neurons. The presence of input cells in the parasympathetic midbrain nuclei contacting frontally projecting cholinergic neurons suggest that the network regulating the inner eye muscles are additionally regulating cortical state via acetylcholine efflux. This dataset enables future circuit-level experiments to identify drivers of known cortical cholinergic functions.

Integration of TMVA Output into Jupyter notebooks

CERN Document Server

Saliji, Albulena

2016-01-01

The purpose of this report is to describe the work that I have been doing during these past eight weeks as a Summer Student at CERN. The task which was assigned to me had to do with the integration of TMVA Output into Jupyter notebooks. In order to integrate the TMVA Output into the Jupyter notebook, first, improvement of the TMVA Output in the terminal was required. Once the output was improved, it needed to be transformed into HTML output and at the end it would be possible to integrate that output into the Jupyter notebook.

Output feedback control of a quadrotor UAV using neural networks.

Science.gov (United States)

Dierks, Travis; Jagannathan, Sarangapani

2010-01-01

In this paper, a new nonlinear controller for a quadrotor unmanned aerial vehicle (UAV) is proposed using neural networks (NNs) and output feedback. The assumption on the availability of UAV dynamics is not always practical, especially in an outdoor environment. Therefore, in this work, an NN is introduced to learn the complete dynamics of the UAV online, including uncertain nonlinear terms like aerodynamic friction and blade flapping. Although a quadrotor UAV is underactuated, a novel NN virtual control input scheme is proposed which allows all six degrees of freedom (DOF) of the UAV to be controlled using only four control inputs. Furthermore, an NN observer is introduced to estimate the translational and angular velocities of the UAV, and an output feedback control law is developed in which only the position and the attitude of the UAV are considered measurable. It is shown using Lyapunov theory that the position, orientation, and velocity tracking errors, the virtual control and observer estimation errors, and the NN weight estimation errors for each NN are all semiglobally uniformly ultimately bounded (SGUUB) in the presence of bounded disturbances and NN functional reconstruction errors while simultaneously relaxing the separation principle. The effectiveness of proposed output feedback control scheme is then demonstrated in the presence of unknown nonlinear dynamics and disturbances, and simulation results are included to demonstrate the theoretical conjecture.

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

Science.gov (United States)

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.

Neural network for recognizing signal-shape of nuclear detector output

International Nuclear Information System (INIS)

Mardiyanto M Panitra

2006-01-01

The use of artificial intelligent technique in the engineering field has been familiar especially in the field of pattern recognition. By using this technique, either simple routine works or complicated routine works can be done by the help of a digital camera and a personal computer. One of the complicated works that can not be solved easily is how to separate two kinds of nuclear radiation types which are mixed in the same field. The separation of the two kinds of radiation become is very important for the radiation dosimetry purposes. For doing this we have carried out a preliminary research in applying a neural network technique for recognizing C and T letters with right, left, up, and down positions. We arranged a three-layer neural network i.e. input layer (9 neurons with/without bias neuron), hidden layer (11 neurons), and output layer (1 neuron). From this preliminary study the use of a bias neuron gave faster learning process compared with the one without the bias neuron. The neural network could work successfully in determining the letter S and T without any mistake. (author)

Mobile Termination and Mobile Penetration

OpenAIRE

Hurkens, Sjaak; Jeon, Doh-Shin

2009-01-01

In this paper, we study how access pricing affects network competition when subscription demand is elastic and each network uses non-linear prices and can apply termination-based price discrimination. In the case of a fixed per minute termination charge, we find that a reduction of the termination charge below cost has two oppos- ing effects: it softens competition but helps to internalize network externalities. The former reduces mobile penetration while the latter boosts it. We find that fi...

Mobile termination and mobile penetration

OpenAIRE

Hurkens, Sjaak

2009-01-01

In this paper, we study how access pricing affects network competition when subscription demand is elastic and each network uses non-linear prices and can apply termination-based price discrimination. In the case of a fixed per minute termination charge, we find that a reduction of the termination charge below cost has two opposing effects: it softens competition but helps to internalize network externalities. The former reduces mobile penetration while the latter boosts it. We find that firm...

A methodology based on dynamic artificial neural network for short-term forecasting of the power output of a PV generator

International Nuclear Information System (INIS)

Almonacid, F.; Pérez-Higueras, P.J.; Fernández, Eduardo F.; Hontoria, L.

2014-01-01

Highlights: • The output of the majority of renewables energies depends on the variability of the weather conditions. • The short-term forecast is going to be essential for effectively integrating solar energy sources. • A new method based on artificial neural network to predict the power output of a PV generator one hour ahead is proposed. • This new method is based on dynamic artificial neural network to predict global solar irradiance and the air temperature. • The methodology developed can be used to estimate the power output of a PV generator with a satisfactory margin of error. - Abstract: One of the problems of some renewables energies is that the output of these kinds of systems is non-dispatchable depending on variability of weather conditions that cannot be predicted and controlled. From this point of view, the short-term forecast is going to be essential for effectively integrating solar energy sources, being a very useful tool for the reliability and stability of the grid ensuring that an adequate supply is present. In this paper a new methodology for forecasting the output of a PV generator one hour ahead based on dynamic artificial neural network is presented. The results of this study show that the proposed methodology could be used to forecast the power output of PV systems one hour ahead with an acceptable degree of accuracy

An improved robust model predictive control for linear parameter-varying input-output models

NARCIS (Netherlands)

Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.

2018-01-01

This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal

A Review of Communications Protocol for Intelligent Remote Terminal Unit Development

Directory of Open Access Journals (Sweden)

Mohd Ruddin Ab. Ghani

2013-11-01

Full Text Available This paper reviewed all the possible interfacing communication protocols for remote terminal unit (RTU. Supervisory Control and Data Acquisition (SCADA system is a central station that can communicate with other network using the protocol. Fundamentally, the architectures of all networks are based on the seven layers of open system interconnection (OSI and International Standard Organization (ISO. The objective of designing the protocols is to check the status of all the input and output field devices and send the report according to that status. The corresponding protocol and communication parameters between the connecting devices will be included in designing a complex SCADA system. The available protocols to develop the communication of RTU are Modbus/ASCII, distributed network protocol (DNP3, controller area network (CAN, International Electro-technical Commission (IEC 60870, transmission control protocol/internet protocol (TCP/IP.

Two-terminal reliability of a mobile ad hoc network under the asymptotic spatial distribution of the random waypoint model

International Nuclear Information System (INIS)

Chen, Binchao; Phillips, Aaron; Matis, Timothy I.

2012-01-01

The random waypoint (RWP) mobility model is frequently used in describing the movement pattern of mobile users in a mobile ad hoc network (MANET). As the asymptotic spatial distribution of nodes under a RWP model exhibits central tendency, the two-terminal reliability of the MANET is investigated as a function of the source node location. In particular, analytical expressions for one and two hop connectivities are developed as well as an efficient simulation methodology for two-terminal reliability. A study is then performed to assess the effect of nodal density and network topology on network reliability.

De-optical-line-terminal hybrid access-aggregation optical network for time-sensitive services based on software-defined networking orchestration

Science.gov (United States)

Bai, Wei; Yang, Hui; Xiao, Hongyun; Yu, Ao; He, Linkuan; Zhang, Jie; Li, Zhen; Du, Yi

2017-11-01

With the increase in varieties of services in network, time-sensitive services (TSSs) appear and bring forward an impending need for delay performance. Ultralow-latency communication has become one of the important development goals for many scenarios in the coming 5G era (e.g., robotics and driverless cars). However, the conventional methods, which decrease delay by promoting the available resources and the network transmission speed, have limited effect; a new breakthrough for ultralow-latency communication is necessary. We propose a de-optical-line-terminal (De-OLT) hybrid access-aggregation optical network (DAON) for TSS based on software-defined networking (SDN) orchestration. In this network, low-latency all-optical communication based on optical burst switching can be achieved by removing OLT. For supporting this network and guaranteeing the quality of service for TSSs, we design SDN-driven control method and service provision method. Numerical results demonstrate the proposed DAON promotes network service efficiency and avoids traffic congestion.

Interpenetrating polymer networks from acetylene terminated materials

Science.gov (United States)

Connell, J. W.; Hergenrother, P. M.

1989-01-01

As part of a program to develop high temperature/high performance structural resins for aerospace applications, the chemistry and properties of a novel class of interpenetrating polymer networks (IPNs) were investigated. These IPNs consist of a simple diacetylenic compound (aspartimide) blended with an acetylene terminated arylene ether oligomer. Various compositional blends were prepared and thermally cured to evaluate the effect of crosslink density on resin properties. The cured IPNs exhibited glass transition temperatures ranging from 197 to 254 C depending upon the composition and cure temperature. The solvent resistance, fracture toughness and coefficient of thermal expansion of the cured blends were related to the crosslink density. Isothermal aging of neat resin moldings, adhesive and composite specimens showed a postcure effect which resulted in improved elevated temperature properties. The chemistry, physical and mechanical properties of these materials will be discussed.

Construct mine environment monitoring system based on wireless mesh network

Science.gov (United States)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

Harvesting full-duplex rate gains in cellular networks with half-duplex user terminals

KAUST Repository

AlAmmouri, Ahmad

2016-07-26

Full-Duplex (FD) transceivers may be expensive in terms of complexity, power consumption, and price to be implemented in all user terminals. Therefore, techniques to exploit in-band full-duplex communication with FD base stations (BSs) and half-duplex (HD) users\\' equipment (UEs) are required. In this context, 3-node topology (3NT) has been recently proposed for FD BSs to reuse the uplink (UL) and downlink (DL) channels with HD terminals within the same cell. In this paper, we present a tractable mathematical framework, based on stochastic geometry, for 3NT in cellular networks. To this end, we propose a design paradigm via pulse-shaping and partial overlap between UL and DL channels to maximize the harvested rate gains in 3NT. The results show that 3NT achieves a close performance to networks with FD BSs and FD UEs, denoted by 2-node topology (2NT) networks. A maximum of 5% rate loss is reported when 3NT is compared to 2NT with efficient self-interference cancellation (SIC). If the SIC in 2NT is not efficient, 3NT highly outperforms 2NT. Consequently, we conclude that, irrespective to the UE duplexing scheme, it is sufficient to have FD BSs to harvest FD rate gains.

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

International Nuclear Information System (INIS)

Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

2012-01-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

Science.gov (United States)

Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

2012-10-01

The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

Science.gov (United States)

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Dynamic Output Feedback Control for Nonlinear Networked Control Systems with Random Packet Dropout and Random Delay

Directory of Open Access Journals (Sweden)

Shuiqing Yu

2013-01-01

Full Text Available This paper investigates the dynamic output feedback control for nonlinear networked control systems with both random packet dropout and random delay. Random packet dropout and random delay are modeled as two independent random variables. An observer-based dynamic output feedback controller is designed based upon the Lyapunov theory. The quantitative relationship of the dropout rate, transition probability matrix, and nonlinear level is derived by solving a set of linear matrix inequalities. Finally, an example is presented to illustrate the effectiveness of the proposed method.

Study on New Smart Transformer Terminal Unit Based on ARM and GPRS Network

Directory of Open Access Journals (Sweden)

Na Wu

2013-12-01

Full Text Available Distribution transformer is one of the most important power equipments in distribution network, whose running state exercises a great influence on the stability of the network. Transformer Terminal Unit (TTU is an effective device to monitor the running state of transformers in the distribution automation system. In this paper, we study a new smart TTU which uses ARM7 series chip as processor, equipped with ATT7022B based electric meter module and GPRS module for remote data transmission control. We focus on the corresponding hardware, software design and the measurement principle of harmonics of TTU. The new TTU can measure the electric parameters of the distribution transformer precisely. Taking advantage of the powerful ARM processor, it can analyze harmonic of the power line effectively. Due to the always-on-line feature of GPRS, TTU can achieve reliable communication with the remote terminal and the master station. Compared with other similar units, the new unit outperforms in terms of real-time, precision and reliability, which can fully meet with the high-speed development of distribution automation system.

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

Science.gov (United States)

Wang, W.; Wang, D.; Peng, Z. H.

2017-09-01

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

Neural network-based optimal adaptive output feedback control of a helicopter UAV.

Science.gov (United States)

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

Universal Voltage Conveyor and its Novel Dual-Output Fully-Cascadable VM APF Application

Directory of Open Access Journals (Sweden)

Norbert Herencsar

2017-03-01

Full Text Available This letter presents a novel realization of a voltage-mode (VM first-order all-pass filter (APF with attractive features. The proposed circuit employs a single readily available six-terminal active device called as universal voltage conveyor (UVC and only grounded passive components, which predict its easy monolithic integration with desired circuit simplicity. The auxiliary voltage input (W and output (ZP, ZN terminals of the device fully ensure easy cascadability of VM APF, since the input and output terminal impedances are theoretically infinitely high and zero, respectively. Moreover, thanks to mutually inverse outputs of the UVC, the proposed filter simultaneously provides both inverting and non-inverting outputs from the same configuration. All of these features make the UVC a unique active device currently available in the literature. The behavior of the filter was experimentally measured using the readily available UVC-N1C 0520 chip, which was produced in cooperation with ON Semiconductor Czech Republic, Ltd.

Concept Layout Model of Transportation Terminals

OpenAIRE

Yao, Li-ya; Sun, Li-shan; Wang, Wu-hong; Xiong, Hui

2012-01-01

Transportation terminal is the key node in transport systems. Efficient terminals can improve operation of passenger transportation networks, adjust the layout of public transportation networks, provide a passenger guidance system, and regulate the development of commercial forms, as well as optimize the assembly and distribution of modern logistic modes, among others. This study aims to clarify the relationship between the function and the structure of transportation terminals and establish ...

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

Science.gov (United States)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Adaptative synchronization in multi-output fractional-order complex dynamical networks and secure communications

Science.gov (United States)

Mata-Machuca, Juan L.; Aguilar-López, Ricardo

2018-01-01

This work deals with the adaptative synchronization of complex dynamical networks with fractional-order nodes and its application in secure communications employing chaotic parameter modulation. The complex network is composed of multiple fractional-order systems with mismatch parameters and the coupling functions are given to realize the network synchronization. We introduce a fractional algebraic synchronizability condition (FASC) and a fractional algebraic identifiability condition (FAIC) which are used to know if the synchronization and parameters estimation problems can be solved. To overcome these problems, an adaptative synchronization methodology is designed; the strategy consists in proposing multiple receiver systems which tend to follow asymptotically the uncertain transmitters systems. The coupling functions and parameters of the receiver systems are adjusted continually according to a convenient sigmoid-like adaptative controller (SLAC), until the measurable output errors converge to zero, hence, synchronization between transmitter and receivers is achieved and message signals are recovered. Indeed, the stability analysis of the synchronization error is based on the fractional Lyapunov direct method. Finally, numerical results corroborate the satisfactory performance of the proposed scheme by means of the synchronization of a complex network consisting of several fractional-order unified chaotic systems.

Neural Network Molecule: a Solution of the Inverse Biometry Problem through Software Support of Quantum Superposition on Outputs of the Network of Artificial Neurons

Directory of Open Access Journals (Sweden)

Vladimir I. Volchikhin

2017-12-01

Full Text Available Introduction: The aim of the study is to accelerate the solution of neural network biometrics inverse problem on an ordinary desktop computer. Materials and Methods: To speed up the calculations, the artificial neural network is introduced into the dynamic mode of “jittering” of the states of all 256 output bits. At the same time, too many output states of the neural network are logarithmically folded by transitioning to the Hamming distance space between the code of the image “Own” and the codes of the images “Alien”. From the database of images of “Alien” 2.5 % of the most similar images are selected. In the next generation, 97.5 % of the discarded images are restored with GOST R 52633.2-2010 procedures by crossing parent images and obtaining descendant images from them. Results: Over a period of about 10 minutes, 60 generations of directed search for the solution of the inverse problem can be realized that allows inversing matrices of neural network functionals of dimension 416 inputs to 256 outputs with restoration of up to 97 % information on unknown biometric parameters of the image “Own”. Discussion and Conclusions: Supporting for 10 minutes of computer time the 256 qubit quantum superposition allows on a conventional computer to bypass the actual infinity of analyzed states in 5050 (50 to 50 times more than the same computer could process realizing the usual calculations. The increase in the length of the supported quantum superposition by 40 qubits is equivalent to increasing the processor clock speed by about a billion times. It is for this reason that it is more profitable to increase the number of quantum superpositions supported by the software emulator in comparison with the creation of a more powerful processor.

Advanced Communication Technology Satellite (ACTS) Very Small Aperture Terminal (VSAT) Network Control Performance

Science.gov (United States)

Coney, T. A.

1996-01-01

This paper discusses the performance of the network control function for the Advanced Communications Technology Satellite (ACTS) very small aperture terminal (VSAT) full mesh network. This includes control of all operational activities such as acquisition, synchronization, timing and rain fade compensation as well as control of all communications activities such as on-demand integrated services (voice, video, and date) connects and disconnects Operations control is provided by an in-band orderwire carried in the baseboard processor (BBP) control burst, the orderwire burst, the reference burst, and the uplink traffic burst. Communication services are provided by demand assigned multiple access (DAMA) protocols. The ACTS implementation of DAMA protocols ensures both on-demand and integrated voice, video and data services. Communications services control is also provided by the in-band orderwire but uses only the reference burst and the uplink traffic burst. The performance of the ACTS network control functions have been successfully tested during on-orbit checkout and in various VSAT networks in day to day operations. This paper discusses the network operations and services control performance.

Power Terminal Communication Access Network Monitoring System Scheme Based on Design Patterns

Science.gov (United States)

Yan, Shengchao; Wu, Desheng; Zhu, Jiang

2018-01-01

In order to realize patterns design for terminal communication monitoring system, this paper introduces manager-workers, tasks-workers design patterns, based on common design patterns such as factory method, chain of responsibility, facade. Using these patterns, the communication monitoring system which combines module-groups like networking communication, business data processing and the peripheral support has been designed successfully. Using these patterns makes this system have great flexibility and scalability and improves the degree of systematic pattern design structure.

Period meter output in response to terminated ramps of reactivity

Energy Technology Data Exchange (ETDEWEB)

Cummins, J D [Dynamics Group, Control and Instrumentation Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)

1962-07-15

The time behaviour of the period meter output has been determined for a range of total reactivity injections and reactivity rates. Some results which are directly applicable to graphite gas cooled reactors are given. (author)

System program for MICRO-CAMAC terminal system

International Nuclear Information System (INIS)

Sasajima, Yoji; Yamada, Takayuki; Yagi, Hideyuki; Ishiguro, Misako

1979-08-01

A JAERI on-line network system was developed and exists for on-line data processing of nuclear instrumentation. As terminal systems for the network system, the one with a Micro -8 micro-computer is used. By modifying the control program for Micro-8 terminal system, a system program has been developed for a MICRO-CAMAC terminal system, which is controlled by a micro-computer framed within the CAMAC Crate Controller. In this report are described software specifications of the MICRO -CAMAC terminal system and its operation method. (author)

Social networks and research output

NARCIS (Netherlands)

Ductor, L.; Fafchamps, M.; Goyal, S.; van der Leij, M.J.

2014-01-01

We study how knowledge about the social network of an individual researcher - as embodied in his coauthor relations - helps us in developing a more accurate prediction of his future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the

Digital Autonomous Terminal Access Communication (DATAC) system

Science.gov (United States)

Novacki, Stanley M., III

1987-01-01

In order to accommodate the increasing number of computerized subsystems aboard today's more fuel efficient aircraft, the Boeing Co. has developed the DATAC (Digital Autonomous Terminal Access Control) bus to minimize the need for point-to-point wiring to interconnect these various systems, thereby reducing total aircraft weight and maintaining an economical flight configuration. The DATAC bus is essentially a local area network providing interconnections for any of the flight management and control systems aboard the aircraft. The task of developing a Bus Monitor Unit was broken down into four subtasks: (1) providing a hardware interface between the DATAC bus and the Z8000-based microcomputer system to be used as the bus monitor; (2) establishing a communication link between the Z8000 system and a CP/M-based computer system; (3) generation of data reduction and display software to output data to the console device; and (4) development of a DATAC Terminal Simulator to facilitate testing of the hardware and software which transfer data between the DATAC's bus and the operator's console in a near real time environment. These tasks are briefly discussed.

Analysis of inter-country input-output table based on bibliographic coupling network: How industrial sectors on the GVC compete for production resources

Science.gov (United States)

Guan, Jun; Xu, Xiaoyu; Xing, Lizhi

2018-03-01

The input-output table is comprehensive and detailed in describing national economic systems with abundance of economic relationships depicting information of supply and demand among industrial sectors. This paper focuses on how to quantify the degree of competition on the global value chain (GVC) from the perspective of econophysics. Global Industrial Strongest Relevant Network models are established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output (ICIO) tables and then have them transformed into Global Industrial Resource Competition Network models to analyze the competitive relationships based on bibliographic coupling approach. Three indicators well suited for the weighted and undirected networks with self-loops are introduced here, including unit weight for competitive power, disparity in the weight for competitive amplitude and weighted clustering coefficient for competitive intensity. Finally, these models and indicators were further applied empirically to analyze the function of industrial sectors on the basis of the latest World Input-Output Database (WIOD) in order to reveal inter-sector competitive status during the economic globalization.

Automatic control and detector for three-terminal resistance measurement

Science.gov (United States)

Fasching, George E.

1976-10-26

A device is provided for automatic control and detection in a three-terminal resistance measuring instrument. The invention is useful for the rapid measurement of the resistivity of various bulk material with a three-terminal electrode system. The device maintains the current through the sample at a fixed level while measuring the voltage across the sample to detect the sample resistance. The three-electrode system contacts the bulk material and the current through the sample is held constant by means of a control circuit connected to a first of the three electrodes and works in conjunction with a feedback controlled amplifier to null the voltage between the first electrode and a second electrode connected to the controlled amplifier output. An A.C. oscillator provides a source of sinusoidal reference voltage of the frequency at which the measurement is to be executed. Synchronous reference pulses for synchronous detectors in the control circuit and an output detector circuit are provided by a synchronous pulse generator. The output of the controlled amplifier circuit is sampled by an output detector circuit to develop at an output terminal thereof a D.C. voltage which is proportional to the sample resistance R. The sample resistance is that segment of the sample between the area of the first electrode and the third electrode, which is connected to ground potential.

Modular approach for satellite communication ground terminals

Science.gov (United States)

Gould, G. R.

1984-01-01

The trend in satellite communications is toward completely digital, time division multiple access (TDMA) systems with uplink and downlink data rates dictated by the type of service offered. Trunking terminals will operate in the 550 MBPS (megabit per second) region uplink and downlink, whereas customer premise service (CPS) terminals will operate in the 25 to 10 MBPS region uplink and in the 200 MBPS region downlink. Additional criteria for the ground terminals will be to maintain clock sychronization with the system and burst time integrity to within a matter of nanoseconds, to process required order-fire information, to provide adaptive data scrambing, and to compensate for variations in the user input output data rates, and for changes in range in the satellite communications links resulting from satellite perturbations in orbit. To achieve the required adaptability of a ground terminal to the above mentioned variables, programmable building blocks can be developed that will meet all of these requirements. To maintain system synchronization, i.e., all bursted data arriving at the satellite within assigned TDMA windows, ground terminal transmit data rates and burst timing must be maintained within tight tolerances. With a programmable synchronizer as the heart of the terminal timing generation, variable data rates and burst timing tolerances are achievable. In essence, the unit inputs microprocessor generated timing words and outputs discrete timing pulses.

Impaired clock output by altered connectivity in the circadian network.

Science.gov (United States)

Fernández, María de la Paz; Chu, Jessie; Villella, Adriana; Atkinson, Nigel; Kay, Steve A; Ceriani, María Fernanda

2007-03-27

Substantial progress has been made in elucidating the molecular processes that impart a temporal control to physiology and behavior in most eukaryotes. In Drosophila, dorsal and ventral neuronal networks act in concert to convey rhythmicity. Recently, the hierarchical organization among the different circadian clusters has been addressed, but how molecular oscillations translate into rhythmic behavior remains unclear. The small ventral lateral neurons can synchronize certain dorsal oscillators likely through the release of pigment dispersing factor (PDF), a neuropeptide central to the control of rhythmic rest-activity cycles. In the present study, we have taken advantage of flies exhibiting a distinctive arrhythmic phenotype due to mutation of the potassium channel slowpoke (slo) to examine the relevance of specific neuronal populations involved in the circadian control of behavior. We show that altered neuronal function associated with the null mutation specifically impaired PDF accumulation in the dorsal protocerebrum and, in turn, desynchronized molecular oscillations in the dorsal clusters. However, molecular oscillations in the small ventral lateral neurons are properly running in the null mutant, indicating that slo is acting downstream of these core pacemaker cells, most likely in the output pathway. Surprisingly, disrupted PDF signaling by slo dysfunction directly affects the structure of the underlying circuit. Our observations demonstrate that subtle structural changes within the circadian network are responsible for behavioral arrhythmicity.

Research on information security system of waste terminal disposal process

Science.gov (United States)

Zhou, Chao; Wang, Ziying; Guo, Jing; Guo, Yajuan; Huang, Wei

2017-05-01

Informatization has penetrated the whole process of production and operation of electric power enterprises. It not only improves the level of lean management and quality service, but also faces severe security risks. The internal network terminal is the outermost layer and the most vulnerable node of the inner network boundary. It has the characteristics of wide distribution, long depth and large quantity. The user and operation and maintenance personnel technical level and security awareness is uneven, which led to the internal network terminal is the weakest link in information security. Through the implementation of security of management, technology and physics, we should establish an internal network terminal security protection system, so as to fully protect the internal network terminal information security.

Distributed control design for nonlinear output agreement in convergent systems

NARCIS (Netherlands)

Weitenberg, Erik; De Persis, Claudio

2015-01-01

This work studies the problem of output agreement in homogeneous networks of nonlinear dynamical systems under time-varying disturbances using controllers placed at the nodes of the networks. For the class of contractive systems, necessary and sufficient conditions for output agreement are derived,

A neural network approach to local downscaling of GCM output for assessing wind power implications of climate change

International Nuclear Information System (INIS)

Sailor, D.J.; Hu, T.; Li, X.; Rosen, J.N.

2000-01-01

A methodology is presented for downscaling General Circulation Model (GCM) output to predict surface wind speeds at scales of interest in the wind power industry under expected future climatic conditions. The approach involves a combination of Neural Network tools and traditional weather forecasting techniques. A Neural Network transfer function is developed to relate local wind speed observations to large scale GCM predictions of atmospheric properties under current climatic conditions. By assuming the invariability of this transfer function under conditions of doubled atmospheric carbon dioxide, the resulting transfer function is then applied to GCM output for a transient run of the National Center for Atmospheric Research coupled ocean-atmosphere GCM. This methodology is applied to three test sites in regions relevant to the wind power industry - one in Texas and two in California. Changes in daily mean wind speeds at each location are presented and discussed with respect to potential implications for wind power generation. (author)

Network effects of subthalamic deep brain stimulation drive a unique mixture of responses in basal ganglia output.

Science.gov (United States)

Humphries, Mark D; Gurney, Kevin

2012-07-01

Deep brain stimulation (DBS) is a remarkably successful treatment for the motor symptoms of Parkinson's disease. High-frequency stimulation of the subthalamic nucleus (STN) within the basal ganglia is a main clinical target, but the physiological mechanisms of therapeutic STN DBS at the cellular and network level are unclear. We set out to begin to address the hypothesis that a mixture of responses in the basal ganglia output nuclei, combining regularized firing and inhibition, is a key contributor to the effectiveness of STN DBS. We used our computational model of the complete basal ganglia circuit to show how such a mixture of responses in basal ganglia output naturally arises from the network effects of STN DBS. We replicated the diversification of responses recorded in a primate STN DBS study to show that the model's predicted mixture of responses is consistent with therapeutic STN DBS. We then showed how this 'mixture of response' perspective suggests new ideas for DBS mechanisms: first, that the therapeutic frequency of STN DBS is above 100 Hz because the diversification of responses exhibits a step change above this frequency; and second, that optogenetic models of direct STN stimulation during DBS have proven therapeutically ineffective because they do not replicate the mixture of basal ganglia output responses evoked by electrical DBS. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Phrenic motoneurons: output elements of a highly organized intraspinal network.

Science.gov (United States)

Ghali, Michael George Zaki

2018-03-01

pontomedullary respiratory network generates the respiratory pattern and relays it to bulbar and spinal respiratory motor outputs. The phrenic motor system controlling diaphragm contraction receives and processes descending commands to produce orderly, synchronous, and cycle-to-cycle-reproducible spatiotemporal firing. Multiple investigators have studied phrenic motoneurons (PhMNs) in an attempt to shed light on local mechanisms underlying phrenic pattern formation. I and colleagues (Marchenko V, Ghali MG, Rogers RF. Am J Physiol Regul Integr Comp Physiol 308: R916-R926, 2015.) recorded PhMNs in unanesthetized, decerebrate rats and related their activity to simultaneous phrenic nerve (PhN) activity by creating a time-frequency representation of PhMN-PhN power and coherence. On the basis of their temporal firing patterns and relationship to PhN activity, we categorized PhMNs into three classes, each of which emerges as a result of intrinsic biophysical and network properties and organizes the orderly contraction of diaphragm motor fibers. For example, early inspiratory diaphragmatic activation by the early coherent burst generated by high-frequency PhMNs may be necessary to prime it to overcome its initial inertia. We have also demonstrated the existence of a prominent role for local intraspinal inhibitory mechanisms in shaping phrenic pattern formation. The objective of this review is to relate and synthesize recent findings with those of previous studies with the aim of demonstrating that the phrenic nucleus is a region of active local processing, rather than a passive relay of descending inputs.

Concept Layout Model of Transportation Terminals

Directory of Open Access Journals (Sweden)

Li-ya Yao

2012-01-01

Full Text Available Transportation terminal is the key node in transport systems. Efficient terminals can improve operation of passenger transportation networks, adjust the layout of public transportation networks, provide a passenger guidance system, and regulate the development of commercial forms, as well as optimize the assembly and distribution of modern logistic modes, among others. This study aims to clarify the relationship between the function and the structure of transportation terminals and establish the function layout design. The mapping mechanism of demand, function, and structure was analyzed, and a quantitative relationship between function and structure was obtained from a design perspective. Passenger demand and terminal structure were decomposed into several demand units and structural elements following the principle of reverse engineering. The relationship maps between these two kinds of elements were then analyzed. Function-oriented concept layout model of transportation terminals was established using the previous method. Thus, a technique in planning and design of transportation structures was proposed. Meaningful results were obtained from the optimization of transportation terminal facilities, which guide the design of the functional layout of transportation terminals and improve the development of urban passenger transportation systems.

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain

Science.gov (United States)

2017-01-01

The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization. PMID:28873432

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain.

Science.gov (United States)

Xing, Lizhi

2017-01-01

The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.

Analysis of inter-country input-output table based on citation network: How to measure the competition and collaboration between industrial sectors on the global value chain.

Directory of Open Access Journals (Sweden)

Lizhi Xing

Full Text Available The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.

Multi-regional input–output model and ecological network analysis for regional embodied energy accounting in China

International Nuclear Information System (INIS)

Zhang, Yan; Zheng, Hongmei; Yang, Zhifeng; Su, Meirong; Liu, Gengyuan; Li, Yanxian

2015-01-01

Chinese regions frequently exchange materials, but regional differences in economic development create unbalanced flows of these resources. In this study, we examined energy by assessing embodied energy consumption to describe the energy-flow structure in China's seven regions. Based on multi-regional monetary input–output tables and energy statistical yearbooks for Chinese provinces in 2002 and 2007, we accounted for both direct and indirect energy consumption, respectively, and the integral input and output of the provinces. Most integral inputs of energy flowed from north to south or from east to west, whereas integral output flows were mainly from northeast to southwest. This differed from the direct flows, which were predominantly from north to south and west to east. This demonstrates the importance of calculating both direct and indirect energy flows. Analysis of the distance and direction traveled by the energy consumption centers of gravity showed that the centers for embodied energy consumption and inputs moved southeast because of the movements of the centers of the Eastern region. However, the center for outputs moved northeast because the movement of the Central region. These analyses provide a basis for identifying how regional economic development policies influence the embodied energy consumption and its flows among regions. - Highlights: • We integrated multi-regional input–output analysis with ecological network analysis. • We accounted for both direct and indirect energy consumption. • The centers of gravity for embodied energy flows moved southeast from 2002 to 2007. • The results support planning of energy consumption and energy flows among regions.

Age-dependent terminal declines in reproductive output in a wild bird

NARCIS (Netherlands)

Hammers, Martijn; Richardson, David S.; Burke, Terry; Komdeur, Jan

2012-01-01

In many iteroparous species individual fitness components, such as reproductive output, first increase with age and then decline during late-life. However, individuals differ greatly in reproductive lifespan, but reproductive declines may only occur in the period just before their death as a result

Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

International Nuclear Information System (INIS)

Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

2012-01-01

Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Science.gov (United States)

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

Science.gov (United States)

Meng, Su; Chen, Jie; Sun, Jian

2017-10-01

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Directory of Open Access Journals (Sweden)

WenBo Xiao

Full Text Available In this article, we introduced an artificial neural network (ANN based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-, multi-crystalline (multi-, and amorphous (amor- crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

A Discrete-Time Recurrent Neural Network for Solving Rank-Deficient Matrix Equations With an Application to Output Regulation of Linear Systems.

Science.gov (United States)

Liu, Tao; Huang, Jie

2017-04-17

This paper presents a discrete-time recurrent neural network approach to solving systems of linear equations with two features. First, the system of linear equations may not have a unique solution. Second, the system matrix is not known precisely, but a sequence of matrices that converges to the unknown system matrix exponentially is known. The problem is motivated from solving the output regulation problem for linear systems. Thus, an application of our main result leads to an online solution to the output regulation problem for linear systems.

47 CFR 25.134 - Licensing provisions of Very Small Aperture Terminal (VSAT) and C-band Small Aperture Terminal...

Science.gov (United States)

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Licensing provisions of Very Small Aperture Terminal (VSAT) and C-band Small Aperture Terminal (CSAT) networks. 25.134 Section 25.134 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES SATELLITE COMMUNICATIONS...

Probing transcription-specific outputs of β-catenin in vivo.

Science.gov (United States)

Valenta, Tomas; Gay, Max; Steiner, Sarah; Draganova, Kalina; Zemke, Martina; Hoffmans, Raymond; Cinelli, Paolo; Aguet, Michel; Sommer, Lukas; Basler, Konrad

2011-12-15

β-Catenin, apart from playing a cell-adhesive role, is a key nuclear effector of Wnt signaling. Based on activity assays in Drosophila, we generated mouse strains where the endogenous β-catenin protein is replaced by mutant forms, which retain the cell adhesion function but lack either or both of the N- and the C-terminal transcriptional outputs. The C-terminal activity is essential for mesoderm formation and proper gastrulation, whereas N-terminal outputs are required later during embryonic development. By combining the double-mutant β-catenin with a conditional null allele and a Wnt1-Cre driver, we probed the role of Wnt/β-catenin signaling in dorsal neural tube development. While loss of β-catenin protein in the neural tube results in severe cell adhesion defects, the morphology of cells and tissues expressing the double-mutant form is normal. Surprisingly, Wnt/β-catenin signaling activity only moderately regulates cell proliferation, but is crucial for maintaining neural progenitor identity and for neuronal differentiation in the dorsal spinal cord. Our model animals thus allow dissecting signaling and structural functions of β-catenin in vivo and provide the first genetic tool to generate cells and tissues that entirely and exclusively lack canonical Wnt pathway activity. © 2011 by Cold Spring Harbor Laboratory Press

Energy efficient design for MIMO two-way AF multiple relay networks

KAUST Repository

Alsharoa, Ahmad M.

2014-04-01

This paper studies the energy efficient transmission and the power allocation problem for multiple two-way relay networks equipped with multi-input multi-output antennas where each relay employs an amplify-and-forward strategy. The goal is to minimize the total power consumption without degrading the quality of service of the terminals. In our analysis, we start by deriving closed-form expressions of the optimal powers allocated to terminals. We then employ a strong optimization tool based on the particle swarm optimization technique to find the optimal power allocated at each relay antenna. Our numerical results illustrate the performance of the proposed scheme and show that it achieves a sub-optimal solution very close to the optimal one.

Design of a search and rescue terminal based on the dual-mode satellite and CDMA network

Science.gov (United States)

Zhao, Junping; Zhang, Xuan; Zheng, Bing; Zhou, Yubin; Song, Hao; Song, Wei; Zhang, Meikui; Liu, Tongze; Zhou, Li

2010-12-01

The current goal is to create a set of portable terminals with GPS/BD2 dual-mode satellite positioning, vital signs monitoring and wireless transmission functions. The terminal depends on an ARM processor to collect and combine data related to vital signs and GPS/BD2 location information, and sends the message to headquarters through the military CDMA network. It integrates multiple functions as a whole. The satellite positioning and wireless transmission capabilities are integrated into the motherboard, and the vital signs sensors used in the form of belts communicate with the board through Bluetooth. It can be adjusted according to the headquarters' instructions. This kind of device is of great practical significance for operations during disaster relief, search and rescue of the wounded in wartime, non-war military operations and other special circumstances.

Risk management communication system between a local government and residents using several network systems and terminal devices

Science.gov (United States)

Ohyama, Takashi; Enomoto, Hiroyuki; Takei, Yuichiro; Maeda, Yuji

2009-05-01

Most of Japan's local governments utilize municipal disaster-management radio communications systems to communicate information on disasters or terrorism to residents. The national government is progressing in efforts toward digitalization by local governments of these systems, but only a small number (approx. 10%) have introduced such equipment due to its requiring large amounts of investment. On the other hand, many local governments are moving forward in installation of optical fiber networks for the purpose of eliminating the "digital divide." We herein propose a communication system as an alternative or supplement to municipal disaster-management radio communications systems, which utilizes municipal optical fiber networks, the internet and similar networks and terminals. The system utilizes the multiple existing networks and is capable of instantly distributing to all residents, and controlling, risk management information. We describe the system overview and the field trials conducted with a local government using this system.

Network effects of subthalamic deep brain stimulation drive a unique mixture of responses in basal ganglia output

OpenAIRE

Humphries, Mark D.; Gurney, Kevin

2012-01-01

Deep brain stimulation (DBS) is a remarkably successful treatment for the motor symptoms of Parkinson's disease. High-frequency stimulation of the subthalamic nucleus (STN) within the basal ganglia is a main clinical target, but the physiological mechanisms of therapeutic STN DBS at the cellular and network level are unclear. We set out to begin to address the hypothesis that a mixture of responses in the basal ganglia output nuclei, combining regularized firing and inhibition, is a key contr...

Solar Power Station Output Inverter Control Design

Directory of Open Access Journals (Sweden)

J. Bauer

2011-04-01

Full Text Available The photovoltaic applications spreads in these days fast, therefore they also undergo great development. Because the amount of the energy obtained from the panel depends on the surrounding conditions, as intensity of the sun exposure or the temperature of the solar array, the converter must be connected to the panel output. The Solar system equipped with inverter can supply small loads like notebooks, mobile chargers etc. in the places where the supplying network is not present. Or the system can be used as a generator and it shall deliver energy to the supply network. Each type of the application has different requirements on the converter and its control algorithm. But for all of them the one thing is common – the maximal efficiency. The paper focuses on design and simulation of the low power inverter that acts as output part of the whole converter. In the paper the design of the control algorithm of the inverter for both types of inverter application – for islanding mode and for operation on the supply grid – is discussed. Attention is also paid to the design of the output filter that should reduce negative side effects of the converter on the supply network.

Social networking for language learners: Creating meaningful output with Web 2.0 tools

Directory of Open Access Journals (Sweden)

Robert Chartrand

2012-03-01

Full Text Available The Internet has the potential to provide language learners with vast resources of authentic written, audio, and video materials to supplement lessons. Educators can find a wide assortment of materials for learners to study in class or after class for independent learning and to encourage learner autonomy. More recently, however, the immense popularity of social networking websites has created new opportunities for language learners to interact in authentic ways that were previously difficult to achieve. Advances in technology mean that today, learners of a language can easily interact with their peers in meaningful practice that helps foster language acquisition and motivation. That is, tasks that make use of Web 2.0 interactivity can significantly raise students’ potential to generate meaningful output and stimulate their interest in language learning.

Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

Science.gov (United States)

Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S

2013-08-01

How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures. Copyright © 2013 Elsevier B.V. All rights reserved.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

Science.gov (United States)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are

Modeling of four-terminal solar photovoltaic systems for field application

Science.gov (United States)

Vahanka, Harikrushna; Purohit, Zeel; Tripathi, Brijesh

2018-05-01

In this article a theoretical framework for mechanically stacked four-terminal solar photovoltaic (FTSPV) system has been proposed. In a mechanical stack arrangement, a semitransparent CdTe panel has been used as a top sub-module, whereas a μc-Si solar panel has been used as bottom sub-module. Theoretical modeling has been done to analyze the physical processes in the system and to estimate reliable prediction of the performance. To incorporate the effect of material, the band gap and the absorption coefficient data for CdTe and μc-Si panels have been considered. The electrical performance of the top and bottom panels operated in a mechanical stack has been obtained experimentally for various inter-panel separations in the range of 0-3 cm. Maximum output power density has been obtained for a separation of 0.75 cm. The mean value of output power density from CdTe (top panel) has been calculated as 32.3 Wm-2 and the mean value of output power density from μc-Si, the bottom panel of four-terminal photovoltaic system has been calculated as ˜3.5 Wm-2. Results reported in this study reveal the potential of mechanically stacked four-terminal tandem solar photovoltaic system towards an energy-efficient configuration.

Determinants of mobile phone output power in a multinational study: implications for exposure assessment

DEFF Research Database (Denmark)

Vrijheid, M; Madsen, Stine Mann; di Vecchia, Paolo

2009-01-01

OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemi......OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure...... on the average output power and the percentage call time at maximum power for each call. RESULTS: Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators...

Bidirectional multi-optical line terminals incorporated converged WSN-PON network using M/M/1 queuing

Science.gov (United States)

Kumar, Love; Sharma, Vishal; Singh, Amarpal

2017-12-01

Wireless Sensor Networks (WSNs) have an assortment of application areas, for instance, civil, military, and video surveillance with restricted power resources and transmission link. To accommodate the massive traffic load in hefty sensor networks is another key issue. Subsequently, there is a necessity to backhaul the sensed information of such networks and prolong the transmission link to access the distinct receivers. Passive Optical Network (PON), a next-generation access technology, comes out as a suitable candidate for the convergence of the sensed data to the core system. The earlier demonstrated work with single-OLT-PON introduces an overloaded buffer akin to video surveillance scenarios. In this paper, to combine the bandwidth potential of PONs with the mobility capability of WSNs, the viability for the convergence of PONs and WSNs incorporating multi-optical line terminals is demonstrated to handle the overloaded OLTs. The existing M/M/1 queue theory with interleaving polling with adaptive cycle time as dynamic bandwidth algorithm is used to shun the probability of packets clash. Further, the proposed multi-sink WSN and multi-OLT PON converged structure is investigated in bidirectional mode analytically and through computer simulations. The observations establish the proposed structure competent to accommodate the colossal data traffic through less time consumption.

SOS based robust H(∞) fuzzy dynamic output feedback control of nonlinear networked control systems.

Science.gov (United States)

Chae, Seunghwan; Nguang, Sing Kiong

2014-07-01

In this paper, a methodology for designing a fuzzy dynamic output feedback controller for discrete-time nonlinear networked control systems is presented where the nonlinear plant is modelled by a Takagi-Sugeno fuzzy model and the network-induced delays by a finite state Markov process. The transition probability matrix for the Markov process is allowed to be partially known, providing a more practical consideration of the real world. Furthermore, the fuzzy controller's membership functions and premise variables are not assumed to be the same as the plant's membership functions and premise variables, that is, the proposed approach can handle the case, when the premise of the plant are not measurable or delayed. The membership functions of the plant and the controller are approximated as polynomial functions, then incorporated into the controller design. Sufficient conditions for the existence of the controller are derived in terms of sum of square inequalities, which are then solved by YALMIP. Finally, a numerical example is used to demonstrate the validity of the proposed methodology.

International network competition

OpenAIRE

Tangerås, Thomas P.; Tåg, Joacim

2014-01-01

We analyse network competition in a market with international calls. National regulatory agencies (NRAs) have incentives to set regulated termination rates above marginal cost to extract rent from international call termination. International network ownership and deregulation are alternatives to combat the incentives of NRAs to distort termination rates. We provide conditions under which each of these policies increase efficiency and aggregate welfare. Our findings provide theoretical suppor...

Universal and inductorless DC/DC converter for multi-output power supplies in sensor and actuator networks

Science.gov (United States)

Saponara, Sergio; Ciarpi, Gabriele

2017-05-01

This work proposes a universal and inductorless DC/DC converter that can be used for a wide input range, from few V to 60 V, to regulate output voltages from 5 V down to 1 V in Sensor and Actuator Network nodes. The proposed converter has been developed within the Athenis3D European project. It is composed by a cascade of multiple switching capacitor stages, with a proper skip-mode control to implement both step-down and step-up converting ratios, thus regulating all input sources to a voltage of about 6 V. These switching stages are further cascaded with linear regulators, which can provide stable output voltages down to 1 V. The multi-output regulator has been realized as a single-chip in a low-cost 0.35 μm CMOS technology. It is available as a naked die or in a ceramic package. The only needed external components are surface mount capacitors, which can be integrated on top of the naked chip die, creating a 3D structure, using trench capacitors embedded in a passive interposing layer. This way the size of the power management unit is further minimized. An advantage of the proposed converter is that it isn't optimized for a particular input voltage, therefore it can be used with no constant input power, like power harvesting systems (e.g. solar cells, wind and water turbines) and very disturbed power supplies.

NetAcet: prediction of N-terminal acetylation sites

DEFF Research Database (Denmark)

Kiemer, Lars; Bendtsen, Jannick Dyrløv; Blom, Nikolaj

2005-01-01

Summary: We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N-acetylation for ......Summary: We present here a neural network based method for prediction of N-terminal acetylation-by far the most abundant post-translational modification in eukaryotes. The method was developed on a yeast dataset for N-acetyltransferase A (NatA) acetylation, which is the type of N...

A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China

Directory of Open Access Journals (Sweden)

Jianhuan Huang

2014-01-01

Full Text Available There are two typical subprocesses in bank production—deposit generation and loan generation. Aiming to open the black box of input-output production of banks and provide comprehensive and accurate assessment on the efficiency of each stage, this paper proposes a two-stage network model with bad outputs and supper efficiency (US-NSBM. Empirical comparisons show that the US-NSBM may be promising and practical for taking the nonperforming loans into account and being able to rank all samples. Applying it to measure the efficiency of Chinese commercial banks from 2008 to 2012, this paper explores the characteristics of overall and divisional efficiency, as well as the determinants of them. Some interesting results are discovered. The polarization of efficiency occurs in the bank level and deposit generation, yet does not in the loan generation. Five hypotheses work as expected in the bank level, but not all of them are supported in the stage level. Our results extend and complement some earlier empirical publications in the bank level.

A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors

International Nuclear Information System (INIS)

Liu, Xiuli; Moreno, Blanca; García, Ana Salomé

2016-01-01

A combined forecast of Grey forecasting method and neural network back propagation model, which is called Grey Neural Network and Input-Output Combined Forecasting Model (GNF-IO model), is proposed. A real case of energy consumption forecast is used to validate the effectiveness of the proposed model. The GNF-IO model predicts coal, crude oil, natural gas, renewable and nuclear primary energy consumption volumes by Spain's 36 sub-sectors from 2010 to 2015 according to three different GDP growth scenarios (optimistic, baseline and pessimistic). Model test shows that the proposed model has higher simulation and forecasting accuracy on energy consumption than Grey models separately and other combination methods. The forecasts indicate that the primary energies as coal, crude oil and natural gas will represent on average the 83.6% percent of the total of primary energy consumption, raising concerns about security of supply and energy cost and adding risk for some industrial production processes. Thus, Spanish industry must speed up its transition to an energy-efficiency economy, achieving a cost reduction and increase in the level of self-supply. - Highlights: • Forecasting System Using Grey Models combined with Input-Output Models is proposed. • Primary energy consumption in Spain is used to validate the model. • The grey-based combined model has good forecasting performance. • Natural gas will represent the majority of the total of primary energy consumption. • Concerns about security of supply, energy cost and industry competitiveness are raised.

Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs.

Science.gov (United States)

Andrews, Steven S; Peria, William J; Yu, Richard C; Colman-Lerner, Alejandro; Brent, Roger

2016-11-23

Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control. Copyright © 2016 Elsevier Inc. All rights reserved.

Control design for a wind turbine-generator using output feedback

Science.gov (United States)

Javid, S. H.; Murdoch, A.; Winkelman, J. R.

1981-01-01

The modeling and approach to control design for a large horizontal axis wind turbine (WT) generator are presented. The control design is based on a suboptimal output regulator which allows coordinated control of WT blade pitch angle and field voltage for the purposes of regulating electrical power and terminal voltage. Results of detailed non-linear simulation tests of this controller are shown.

A Simulation Platform for Combined Rail/Road Transport in Multiyards Intermodal Terminals

OpenAIRE

Chen, Xuchao; He, Shiwei; Li, Tingting; Li, Yubin

2018-01-01

With the rapid development of multiyards railway intermodal terminal (MYRIT) construction in China, performance evaluation has become an important issue for terminal design and management departments. Due to the complexity of the multiyards terminal and the associated rail network, the train moving process and related terminal operations have become more complicated compared with the traditional intermodal container terminal. However, in general simulation platforms, the train moving process ...

A Novel Output Filter Topology to Reduce Motor Overvoltage

DEFF Research Database (Denmark)

Hanigovszki, Norbert; Poulsen, Joern; Blaabjerg, Frede

2004-01-01

When an induction machine is supplied with a voltage-source pulsewidth-modulation (PWM) inverter, a ringing voltage overshoot appears at motor terminals due to steep PWM voltage pulse propagation along the motor cable. It has been reported that in particular situations, when very long motor cable....... The proposed filter drastically reduces the voltage overshoot at the motor terminals, thus reducing motor insulation stress. This is a cheap alternative to more known industrial solutions. LC...... are used and retrofit installations, the overvoltage could stress motors with poor insulation. This paper presents a novel inverter output filter topology consisting of an filter which has the star point of the common-mode capacitors clamped to the + and ? dc-link rails by the means of two diodes...

Termination factor Rho: From the control of pervasive transcription to cell fate determination in Bacillus subtilis

Science.gov (United States)

Nicolas, Pierre; Repoila, Francis; Bardowski, Jacek; Aymerich, Stéphane

2017-01-01

In eukaryotes, RNA species originating from pervasive transcription are regulators of various cellular processes, from the expression of individual genes to the control of cellular development and oncogenesis. In prokaryotes, the function of pervasive transcription and its output on cell physiology is still unknown. Most bacteria possess termination factor Rho, which represses pervasive, mostly antisense, transcription. Here, we investigate the biological significance of Rho-controlled transcription in the Gram-positive model bacterium Bacillus subtilis. Rho inactivation strongly affected gene expression in B. subtilis, as assessed by transcriptome and proteome analysis of a rho–null mutant during exponential growth in rich medium. Subsequent physiological analyses demonstrated that a considerable part of Rho-controlled transcription is connected to balanced regulation of three mutually exclusive differentiation programs: cell motility, biofilm formation, and sporulation. In the absence of Rho, several up-regulated sense and antisense transcripts affect key structural and regulatory elements of these differentiation programs, thereby suppressing motility and biofilm formation and stimulating sporulation. We dissected how Rho is involved in the activity of the cell fate decision-making network, centered on the master regulator Spo0A. We also revealed a novel regulatory mechanism of Spo0A activation through Rho-dependent intragenic transcription termination of the protein kinase kinB gene. Altogether, our findings indicate that distinct Rho-controlled transcripts are functional and constitute a previously unknown built-in module for the control of cell differentiation in B. subtilis. In a broader context, our results highlight the recruitment of the termination factor Rho, for which the conserved biological role is probably to repress pervasive transcription, in highly integrated, bacterium-specific, regulatory networks. PMID:28723971

Kualitas Jaringan Pada Jaringan Virtual Local Area Network (VLAN Yang Menerapkan Linux Terminal Server Project (LTSP

Directory of Open Access Journals (Sweden)

Lipur Sugiyanta

2017-12-01

Full Text Available Virtual Local Area Network (VLAN merupakan sebuah teknik dalam jaringan komputer untuk menciptakan beberapa jaringan yang berbeda tetapi masih merupakan sebuah jaringan lokal yang tidak terbatas pada lokasi fisik seperti LAN sedangkan Linux Terminal Server Project (LTSP merupakan sebuah teknik terminal server yang dapat memperbanyak workstation dengan hanya menggunakan sebuah Linux server. Dalam membangun sebuah jaringan komputer perlu memperhatikan beberapa hal dan salah satunya adalah kualitas jaringan dari jaringan yang dibangun. Pada penelitian ini bertujuan untuk mengetahui pengaruh jumlah client terhadap kualitas jaringan berdasarkan parameter delay dan packet loss pada jaringan VLAN yang menerapkan LTSP. Oleh karena itu, penelitian ini menggunakan jenis metode penelitian kualitatif dengan memperhatikan standar yang digunakan dalam penelitian yaitu standar International Telecommunication Union – Telecommunication (ITU-T. Penerapan penelitian ini menggunakan sistem operasi pada server adalah Ubuntu Desktop 14.04 LTS. Berdasarkan dari hasil penelitian yang ditemukan dapat disimpulkan bahwa benar terbukti bahwa makin banyak client yang dilayani oleh server maka akan menurunkan kualitas jaringan berdasarkan parameter Quality of Service (QoS yang digunakan yaitu delay dan packet loss.

In-Network Performance of Handheld Mobile Terminals

DEFF Research Database (Denmark)

Nielsen, Jesper Ødum; Pedersen, Gert Frølund

2006-01-01

are compared with the equivalent performance obtained in a live GSM network using data from the Abis network interface. This method does not require altering of the handsets and the testing uses normal calls in the network. The investigation is based on measurements with four different commercially available...

High-Voltage, Low-Power BNC Feedthrough Terminator

Science.gov (United States)

Bearden, Douglas

2012-01-01

This innovation is a high-voltage, lowpower BNC (Bayonet Neill-Concelman) feedthrough that enables the user to terminate an instrumentation cable properly while connected to a high voltage, without the use of a voltage divider. This feedthrough is low power, which will not load the source, and will properly terminate the instrumentation cable to the instrumentation, even if the cable impedance is not constant. The Space Shuttle Program had a requirement to measure voltage transients on the orbiter bus through the Ground Lightning Measurement System (GLMS). This measurement has a bandwidth requirement of 1 MHz. The GLMS voltage measurement is connected to the orbiter through a DC panel. The DC panel is connected to the bus through a nonuniform cable that is approximately 75 ft (approximately equal to 23 m) long. A 15-ft (approximately equal to 5-m), 50-ohm triaxial cable is connected between the DC panel and the digitizer. Based on calculations and simulations, cable resonances and reflections due to mismatched impedances of the cable connecting the orbiter bus and the digitizer causes the output not to reflect accurately what is on the bus. A voltage divider at the DC panel, and terminating the 50-ohm cable properly, would eliminate this issue. Due to implementation issues, an alternative design was needed to terminate the cable properly without the use of a voltage divider. Analysis shows how the cable resonances and reflections due to the mismatched impedances of the cable connecting the orbiter bus and the digitizer causes the output not to reflect accurately what is on the bus. After simulating a dampening circuit located at the digitizer, simulations were performed to show how the cable resonances were dampened and the accuracy was improved significantly. Test cables built to verify simulations were accurate. Since the dampening circuit is low power, it can be packaged in a BNC feedthrough.

Metagovernance, network structure, and legitimacy

DEFF Research Database (Denmark)

Daugbjerg, Carsten; Fawcett, Paul

2017-01-01

This article develops a heuristic for comparative governance analysis. The heuristic depicts four network types by combining network structure with the state’s capacity to metagovern. It suggests that each network type produces a particular combination of input and output legitimacy. We illustrate...... the heuristic and its utility using a comparative study of agri-food networks (organic farming and land use) in four countries, which each exhibit different combinations of input and output legitimacy respectively. The article concludes by using a fifth case study to illustrate what a network type that produces...... high levels of input and output legitimacy might look like....

Intermodal terminals simulation for operation management

OpenAIRE

Baldassarra, Alessandro; Impastato, Stefano; Ricci, Stefano

2010-01-01

A freight terminal is a key node in a transportation network and the transit time of containers through this terminal represents one of the most relevant bottlenecks in logistic chains. The system performance reduction and the corresponding increase of transit time are often due to the increase of the freight flow without a corresponding increase of stacking and handling capacity. For this purpose it was decided to approach the problem by a discrete event simulation model, in order to reprodu...

5G Terminals with Multi-Streaming Features for Real-Time Mobile Broadband Applications

Directory of Open Access Journals (Sweden)

T. Shuminoski

2017-06-01

Full Text Available In this paper we present a novel QoS framework on the network layer for 5G terminals with vertical multi-homing and multi-streaming capabilities by using radio networks aggregation. The proposed framework is leading to high performance utility networks with QoS provisioning for real-time multimedia services by achieving low packet delays, stochastic queuing network stability and highest mobile broadband capabilities i.e. bitrates. The proposed QoS algorithm is implemented within the mobile terminals on one side, and in dedicated proxy servers on mobile core network side. It is based on Lyapunov optimization techniques and it is targeted to handle simultaneously multiple multimedia service flows via multiple radio network interfaces in parallel.

EPICS Input/Output Controller (IOC) application developer's guide. APS Release 3.12

International Nuclear Information System (INIS)

Kraimer, M.R.

1994-11-01

This document describes the core software that resides in an Input/Output Controller (IOC), one of the major components of EPICS. The basic components are: (OPI) Operator Interface; this is a UNIX based workstation which can run various EPICS tools; (IOC) Input/Output Controller; this is a VME/VXI based chassis containing a Motorola 68xxx processor, various I/O modules, and VME modules that provide access to other I/O buses such as GPIB, (LAN), Local Area Network; and this is the communication network which allows the IOCs and OPIs to communicate. Epics provides a software component, Channel Access, which provides network transparent communication between a Channel Access client and an arbitrary number of Channel Access servers

Cold as ice. Baltic Sea's first liquefied natural gas terminal; Eiskalt verschifft. Erstes Fluessigerdgas-Terminal in der Ostsee

Energy Technology Data Exchange (ETDEWEB)

Anon.

2011-07-01

In liquid form, natural gas can be transported by ship or truck to remote areas that are not on a pipeline network. Near Stockholm, The Linde Group has now built the Baltic region's first LNG terminal. The company also provided the building blocks along the entire LNG value chain - from the liquefaction plants through the transport ship tanks to the actual terminal. (orig.)

A hybrid method for forecasting the energy output of photovoltaic systems

International Nuclear Information System (INIS)

Ramsami, Pamela; Oree, Vishwamitra

2015-01-01

Highlights: • We propose a novel hybrid technique for predicting the daily PV energy output. • Multiple linear regression, FFNN and GRNN artificial neural networks are used. • Stepwise regression is used to select the most relevant meteorological parameters. • SR-FFNN reduces the average dispersion and overall bias in prediction errors. • Accuracy metrics of hybrid models are better than those of single-stage models. - Abstract: The intermittent nature of solar energy poses many challenges to renewable energy system operators in terms of operational planning and scheduling. Predicting the output of photovoltaic systems is therefore essential for managing the operation and assessing the economic performance of power systems. This paper presents a new technique for forecasting the 24-h ahead stochastic energy output of photovoltaic systems based on the daily weather forecasts. A comparison of the performances of the hybrid technique with conventional linear regression and artificial neural network models has also been reported. Initially, three single-stage models were designed, namely the generalized regression neural network, feedforward neural network and multiple linear regression. Subsequently, a hybrid-modeling approach was adopted by applying stepwise regression to select input variables of greater importance. These variables were then fed to the single-stage models resulting in three hybrid models. They were then validated by comparing the forecasts of the models with measured dataset from an operational photovoltaic system. The accuracy of the each model was evaluated based on the correlation coefficient, mean absolute error, mean bias error and root mean square error values. Simulation results revealed that the hybrid models perform better than their corresponding single-stage models. Stepwise regression-feedforward neural network hybrid model outperformed the other models with root mean square error, mean absolute error, mean bias error and

TMACS I/O termination point listing. Revision 1

International Nuclear Information System (INIS)

Scaief, C.C. III.

1994-01-01

This document provides a listing of all analog and discrete input/output (I/O) points connected to the Tank Monitor and Control System (TMACS). The list also provides other information such as the point tag name, termination location, description, drawing references and other parameters. The purpose is to define each point's unique tag name and to cross reference the point with other associated information that may be necessary for activities such as maintenance, calibration, diagnostics, or design changes. It provides a list in one document of all I/O points that would otherwise only be available by referring to all I/O termination drawings

TMACS I/O termination point listing. Revision 1

Energy Technology Data Exchange (ETDEWEB)

Scaief, C.C. III

1994-09-13

This document provides a listing of all analog and discrete input/output (I/O) points connected to the Tank Monitor and Control System (TMACS). The list also provides other information such as the point tag name, termination location, description, drawing references and other parameters. The purpose is to define each point`s unique tag name and to cross reference the point with other associated information that may be necessary for activities such as maintenance, calibration, diagnostics, or design changes. It provides a list in one document of all I/O points that would otherwise only be available by referring to all I/O termination drawings.

Adaptive multi-node multiple input and multiple output (MIMO) transmission for mobile wireless multimedia sensor networks.

Science.gov (United States)

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.

Hindcasting of storm waves using neural networks

Digital Repository Service at National Institute of Oceanography (India)

Rao, S.; Mandal, S.

Department NN neural network net i weighted sum of the inputs of neuron i o k network output at kth output node P total number of training pattern s i output of neuron i t k target output at kth output node 1. Introduction Severe storms occur in Bay of Bengal...), forecasting of runoff (Crespo and Mora, 1993), concrete strength (Kasperkiewicz et al., 1995). The uses of neural network in the coastal the wave conditions will change from year to year, thus a proper statistical and climatological treatment requires several...

Three-terminal ferroelectric synapse device with concurrent learning function for artificial neural networks

International Nuclear Information System (INIS)

Nishitani, Y.; Kaneko, Y.; Ueda, M.; Fujii, E.; Morie, T.

2012-01-01

Spike-timing-dependent synaptic plasticity (STDP) is demonstrated in a synapse device based on a ferroelectric-gate field-effect transistor (FeFET). STDP is a key of the learning functions observed in human brains, where the synaptic weight changes only depending on the spike timing of the pre- and post-neurons. The FeFET is composed of the stacked oxide materials with ZnO/Pr(Zr,Ti)O 3 (PZT)/SrRuO 3 . In the FeFET, the channel conductance can be altered depending on the density of electrons induced by the polarization of PZT film, which can be controlled by applying the gate voltage in a non-volatile manner. Applying a pulse gate voltage enables the multi-valued modulation of the conductance, which is expected to be caused by a change in PZT polarization. This variation depends on the height and the duration of the pulse gate voltage. Utilizing these characteristics, symmetric and asymmetric STDP learning functions are successfully implemented in the FeFET-based synapse device by applying the non-linear pulse gate voltage generated from a set of two pulses in a sampling circuit, in which the two pulses correspond to the spikes from the pre- and post-neurons. The three-terminal structure of the synapse device enables the concurrent learning, in which the weight update can be performed without canceling signal transmission among neurons, while the neural networks using the previously reported two-terminal synapse devices need to stop signal transmission for learning.

Service network design for an intermodal container network with flexible due dates/times and the possibility of using subcontracted transport

NARCIS (Netherlands)

B. van Riessen (Bart); R.R. Negenborn (Rudy); R. Dekker (Rommert); G. Lodewijks (Gabriel)

2013-01-01

textabstractAn intermodal container transportation network is being developed between Rotterdam and several inland terminals in North West Europe: the EUROPEAN GATEWAY SERVICES (EGS) network. This network is developed and operated by the seaports of EUROPE CONTAINER TERMINALS (ECT). To use this

Metropolitan all-pass and inter-city quantum communication network.

Science.gov (United States)

Chen, Teng-Yun; Wang, Jian; Liang, Hao; Liu, Wei-Yue; Liu, Yang; Jiang, Xiao; Wang, Yuan; Wan, Xu; Cai, Wei-Qi; Ju, Lei; Chen, Luo-Kan; Wang, Liu-Jun; Gao, Yuan; Chen, Kai; Peng, Cheng-Zhi; Chen, Zeng-Bing; Pan, Jian-Wei

2010-12-20

We have demonstrated a metropolitan all-pass quantum communication network in field fiber for four nodes. Any two nodes of them can be connected in the network to perform quantum key distribution (QKD). An optical switching module is presented that enables arbitrary 2-connectivity among output ports. Integrated QKD terminals are worked out, which can operate either as a transmitter, a receiver, or even both at the same time. Furthermore, an additional link in another city of 60 km fiber (up to 130 km) is seamless integrated into this network based on a trusted relay architecture. On all the links, we have implemented protocol of decoy state scheme. All of necessary electrical hardware, synchronization, feedback control, network software, execution of QKD protocols are made by tailored designing, which allow a completely automatical and stable running. Our system has been put into operation in Hefei in August 2009, and publicly demonstrated during an evaluation conference on quantum network organized by the Chinese Academy of Sciences on August 29, 2009. Real-time voice telephone with one-time pad encoding between any two of the five nodes (four all-pass nodes plus one additional node through relay) is successfully established in the network within 60 km.

Electronically Tunable Quadrature Sinusoidal Oscillator with Equal Output Amplitudes during Frequency Tuning Process

Directory of Open Access Journals (Sweden)

Den Satipar

2017-01-01

Full Text Available A new configuration of voltage-mode quadrature sinusoidal oscillator is proposed. The proposed oscillator employs two voltage differencing current conveyors (VDCCs, two resistors, and two grounded capacitors. In this design, the use of multiple/dual output terminal active building block is not required. The tuning of frequency of oscillation (FO can be done electronically by adjusting the bias current of active device without affecting condition of oscillation (CO. The electronic tuning can be done by controlling the bias current using a digital circuit. The amplitude of two sinusoidal outputs is equal when the frequency of oscillation is tuned. This makes the sinusoidal output voltages meet good total harmonic distortions (THD. Moreover, the proposed circuit can provide the sinusoidal output current with high impedance which is connected to external load or to another circuit without the use of buffer device. To confirm that the oscillator can generate the quadrature sinusoidal output signal, the experimental results using VDCC constructed from commercially available ICs are also included. The experimental results agree well with theoretical anticipation.

Graphic terminal based on storage tube display with microcomputer

International Nuclear Information System (INIS)

Leich, H.; Levchanovsky, F.; Nikulnikov, A.; Polyntsev, A.; Prikhodko, V.

1981-01-01

This paper describes a graphic terminal where a microcomputer realizes functions like the generation of picture elements (points, symbols, vectors), display control, processing of data received from keyboard and trackball, communication with a host computer and others. The terminal has been designed for operating in a local network as well as in autonomous control systems for data acquisition and processing in physical experiments [ru

A network-based Macintosh serial host interface program

International Nuclear Information System (INIS)

Wight, J.

1991-03-01

A program has been written for the Apple Macintosh to replace conventional host RS232 terminals with customizable user interfaces. Serial port NuBus cards in the Macintosh allow many simultaneous sessions to be maintained. A powerful system is attained by connecting multiple Macintoshes on a network, each running this program. Each is then able to share incoming data from any of its serial ports with any other Macintosh, as well as accept data from any other Macintosh for output to any of its serial ports. The program has been used to eliminate multiple host terminals, modernize the user interface, and to centralize operation of a complex control system. Minimal changes to host software have been required. By making extensive use of Macintosh resources, the same executable code serves in a variety of roles. An object oriented C language with a class library made the development straightforward and easy to modify. This program is used to control a 2 MW neutral beam system on the DIII-D magnetic fusion tokamak. 7 figs

Operation and Power Flow Control of Multi-Terminal DC Networks for Grid Integration of Offshore Wind Farms Using Genetic Algorithms

Directory of Open Access Journals (Sweden)

Rodrigo Teixeira Pinto

2012-12-01

Full Text Available For achieving the European renewable electricity targets, a significant contribution is foreseen to come from offshore wind energy. Considering the large scale of the future planned offshore wind farms and the increasing distances to shore, grid integration through a transnational DC network is desirable for several reasons. This article investigates a nine-node DC grid connecting three northern European countries — namely UK, The Netherlands and Germany. The power-flow control inside the multi-terminal DC grid based on voltage-source converters is achieved through a novel method, called distributed voltage control (DVC. In this method, an optimal power flow (OPF is solved in order to minimize the transmission losses in the network. The main contribution of the paper is the utilization of a genetic algorithm (GA to solve the OPF problem while maintaining an N-1 security constraint. After describing main DC network component models, several case studies illustrate the dynamic behavior of the proposed control method.

Comparing between predicted output temperature of flat-plate solar collector and experimental results: computational fluid dynamics and artificial neural network

Directory of Open Access Journals (Sweden)

F Nadi

2017-05-01

Full Text Available Introduction The significant of solar energy as a renewable energy source, clean and without damage to the environment, for the production of electricity and heat is of great importance. Furthermore, due to the oil crisis as well as reducing the cost of home heating by 70%, solar energy in the past two decades has been a favorite of many researchers. Solar collectors are devices for collecting solar radiant energy through which this energy is converted into heat and then heat is transferred to a fluid (usually air or water. Therefore, a key component in performance improvement of solar heating system is a solar collector optimization under different testing conditions. However, estimation of output parameters under different testing conditions is costly, time consuming and mostly impossible. As a result, smart use of neural networks as well as CFD (computational fluid dynamics to predict the properties with which desired output would have been acquired is valuable. To the best of our knowledge, there are no any studies that compare experimental results with CFD and ANN. Materials and Methods A corrugated galvanized iron sheet of 2 m length, 1 m wide and 0.5 mm in thickness was used as an absorber plate for absorbing the incident solar radiation (Fig. 1 and 2. Corrugations in absorber were caused turbulent air and improved heat transfer coefficient. Computational fluid dynamics K-ε turbulence model was used for simulation. The following assumptions are made in the analysis. (1 Air is a continuous medium and incompressible. (2 The flow is steady and possesses have turbulent flow characteristics, due to the high velocity of flow. (3 The thermal-physical properties of the absorber sheet and the absorber tube are constant with respect to the operating temperature. (4 The bottom side of the absorber tube and the absorber plate are assumed to be adiabatic. Artificial neural network In this research a one-hidden-layer feed-forward network based on the

Implementation of medical monitor system based on networks

Science.gov (United States)

Yu, Hui; Cao, Yuzhen; Zhang, Lixin; Ding, Mingshi

2006-11-01

In this paper, the development trend of medical monitor system is analyzed and portable trend and network function become more and more popular among all kinds of medical monitor devices. The architecture of medical network monitor system solution is provided and design and implementation details of medical monitor terminal, monitor center software, distributed medical database and two kind of medical information terminal are especially discussed. Rabbit3000 system is used in medical monitor terminal to implement security administration of data transfer on network, human-machine interface, power management and DSP interface while DSP chip TMS5402 is used in signal analysis and data compression. Distributed medical database is designed for hospital center according to DICOM information model and HL7 standard. Pocket medical information terminal based on ARM9 embedded platform is also developed to interactive with center database on networks. Two kernels based on WINCE are customized and corresponding terminal software are developed for nurse's routine care and doctor's auxiliary diagnosis. Now invention patent of the monitor terminal is approved and manufacture and clinic test plans are scheduled. Applications for invention patent are also arranged for two medical information terminals.

A unifying view of synchronization for data assimilation in complex nonlinear networks

Science.gov (United States)

Abarbanel, Henry D. I.; Shirman, Sasha; Breen, Daniel; Kadakia, Nirag; Rey, Daniel; Armstrong, Eve; Margoliash, Daniel

2017-12-01

Networks of nonlinear systems contain unknown parameters and dynamical degrees of freedom that may not be observable with existing instruments. From observable state variables, we want to estimate the connectivity of a model of such a network and determine the full state of the model at the termination of a temporal observation window during which measurements transfer information to a model of the network. The model state at the termination of a measurement window acts as an initial condition for predicting the future behavior of the network. This allows the validation (or invalidation) of the model as a representation of the dynamical processes producing the observations. Once the model has been tested against new data, it may be utilized as a predictor of responses to innovative stimuli or forcing. We describe a general framework for the tasks involved in the "inverse" problem of determining properties of a model built to represent measured output from physical, biological, or other processes when the measurements are noisy, the model has errors, and the state of the model is unknown when measurements begin. This framework is called statistical data assimilation and is the best one can do in estimating model properties through the use of the conditional probability distributions of the model state variables, conditioned on observations. There is a very broad arena of applications of the methods described. These include numerical weather prediction, properties of nonlinear electrical circuitry, and determining the biophysical properties of functional networks of neurons. Illustrative examples will be given of (1) estimating the connectivity among neurons with known dynamics in a network of unknown connectivity, and (2) estimating the biophysical properties of individual neurons in vitro taken from a functional network underlying vocalization in songbirds.

双卡双待移动终端锁网方案研究%Research on network locking scheme for DCDS mobile terminal

Institute of Scientific and Technical Information of China (English)

高杰; 张岳彤; 包志祥

2015-01-01

Since the competition of mobile communication market becomes more intense with the arrival of 3G & 4G mobile communication era,communication operators launch series marketing strategies including charging phone calls for free mobile phone or cheap sale of mobile phone. In this situation,to ensure operators′ legal rights and interests,network locking function has become the operators′ basic requirements for customized mobile terminal gradually. How to meet the demands of customers′personalization and intelligentization to the utmost while ensuring operators′ legal rights and interests,becomes the important problem that the DCDS mobile terminal network locking is faced. As for current DCDS mobile terminal network locking tech⁃niques,three different kinds of network locking technologies were formed. In this paper,three DCDS network locking schemes are introduced,and a new DCDS network locking scheme based on them is proposed.%随着3G乃至4G移动通信时代的到来，移动通信市场的竞争越来越激烈，各运营商推出了充话费送手机或廉价出售手机等一系列的营销策略。这种情况下，为了充分保证自己的合法权益，锁网功能逐渐成为运营商定制移动终端的基本需求。同时，双卡双待移动终端在整个终端市场上的占比也越来越高。如何能在满足运营商合法权益的前提下，最大限度地兼顾到客户的个性化和智能化需求，成为双卡双待移动终端锁网所面临的重要问题。就当前双卡双待移动终端锁网技术领域的发展而言，形成了三种方式各异的锁网技术，对这三种锁网技术方案进行了介绍，并在此基础上提出了一种新的双卡双待移动终端锁网方案。

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Uncovering the spatially distant feedback loops of global trade: A network and input-output approach.

Science.gov (United States)

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; He, Jiaying; Hubacek, Klaus

2017-05-15

Land-use change is increasingly driven by global trade. The term "telecoupling" has been gaining ground as a means to describe how human actions in one part of the world can have spatially distant impacts on land and land-use in another. These interactions can, over time, create both direct and spatially distant feedback loops, in which human activity and land use mutually impact one another over great expanses. In this paper, we develop an analytical framework to clarify spatially distant feedbacks in the case of land use and global trade. We use an innovative mix of multi-regional input-output (MRIO) analysis and stochastic actor-oriented models (SAOMs) for analyzing the co-evolution of changes in trade network patterns with those of land use, as embodied in trade. Our results indicate that the formation of trade ties and changes in embodied land use mutually impact one another, and further, that these changes are linked to disparities in countries' wealth. Through identifying this feedback loop, our results support ongoing discussions about the unequal trade patterns between rich and poor countries that result in uneven distributions of negative environmental impacts. Finally, evidence for this feedback loop is present even when controlling for a number of underlying mechanisms, such as countries' land endowments, their geographical distance from one another, and a number of endogenous network tendencies. Copyright © 2017 Elsevier B.V. All rights reserved.

A Study on the Efficiency of Container Terminals in Korea and China

Directory of Open Access Journals (Sweden)

Xue Bin Zheng

2016-12-01

Full Text Available The objective of this study is to derive implications required for efficiency improvement and management level enhancement by selecting container terminals within major large ports of Korea and China as comparison units, evaluating their relative efficiencies and analyzing the trend of changes in their efficiencies. Since the scope of comparison subjects has been narrowed down to container terminals unlike previous studies, it is expected that the study results would have significant meaning due to the fact that it would be possible to compare and analyze in more detail. To achieve the objective, 30 major container terminals in both countries are selected, input and output variables are defined for each terminal and the DEA (data envelopment analysis model is used to conduct an analysis. The results show that the efficiency of major terminals in Korea (CCR: 0.815, BCC: 0.886 showed similar efficiency with China's terminals (CCR: 0.817, BCC: 0.887. While previous studies conclude that the efficiency of ports in Korea is far lower than that of ports in China.

Urban energy consumption: Different insights from energy flow analysis, input–output analysis and ecological network analysis

International Nuclear Information System (INIS)

Chen, Shaoqing; Chen, Bin

2015-01-01

Highlights: • Urban energy consumption was assessed from three different perspectives. • A new concept called controlled energy was developed from network analysis. • Embodied energy and controlled energy consumption of Beijing were compared. • The integration of all three perspectives will elucidate sustainable energy use. - Abstract: Energy consumption has always been a central issue for sustainable urban assessment and planning. Different forms of energy analysis can provide various insights for energy policy making. This paper brought together three approaches for energy consumption accounting, i.e., energy flow analysis (EFA), input–output analysis (IOA) and ecological network analysis (ENA), and compared their different perspectives and the policy implications for urban energy use. Beijing was used to exemplify the different energy analysis processes, and the 42 economic sectors of the city were aggregated into seven components. It was determined that EFA quantifies both the primary and final energy consumption of the urban components by tracking the different types of fuel used by the urban economy. IOA accounts for the embodied energy consumption (direct and indirect) used to produce goods and services in the city, whereas the control analysis of ENA quantifies the specific embodied energy that is regulated by the activities within the city’s boundary. The network control analysis can also be applied to determining which economic sectors drive the energy consumption and to what extent these sectors are dependent on each other for energy. So-called “controlled energy” is a new concept that adds to the analysis of urban energy consumption, indicating the adjustable energy consumed by sectors. The integration of insights from all three accounting perspectives further our understanding of sustainable energy use in cities

Training spiking neural networks to associate spatio-temporal input-output spike patterns

OpenAIRE

Mohemmed, A; Schliebs, S; Matsuda, S; Kasabov, N

2013-01-01

In a previous work (Mohemmed et al., Method for training a spiking neuron to associate input–output spike trains) [1] we have proposed a supervised learning algorithm based on temporal coding to train a spiking neuron to associate input spatiotemporal spike patterns to desired output spike patterns. The algorithm is based on the conversion of spike trains into analogue signals and the application of the Widrow–Hoff learning rule. In this paper we present a mathematical formulation of the prop...

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

Science.gov (United States)

Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

2016-01-01

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network

Directory of Open Access Journals (Sweden)

Dragan Pamučar

2016-01-01

Full Text Available The paper herein presents green p-median problem (GMP which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM, negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

On and off controlled resonant dc-dc power converter

DEFF Research Database (Denmark)

2015-01-01

The present invention relates to a resonant DC-DC power converter comprising an input side circuit comprising a positive and a negative input terminal for receipt of an input voltage or current and an output side circuit comprising positive and negative output terminals for supply of a converter...... output voltage and connection to a converter load. The resonant DC-DC power converter further comprises a rectification circuit connected between an output of a resonant network and the output side circuit. The resonant network is configured for alternatingly being charged from the input voltage...... or current and discharged through the rectification circuit by a first controllable switch arrangement in accordance with a first switch control signal. A second controllable switch arrangement of the resonant DC-DC power converter is configured to select a first impedance characteristic of the resonant...

Flow Batteries for Microfluidic Networks – Configuring An Electroosmotic Pump for Non-Terminal Positions

Science.gov (United States)

He, Chiyang; Lu, Joann J.; Jia, Zhijian; Wang, Wei; Wang, Xiayan; Dasgupta, Purnendu K.; Liu, Shaorong

2011-01-01

A micropump provides flow and pressure for a lab-on-chip device, just as a battery supplies current and voltage for an electronic system. Numerous micropumps have been developed, but none is as versatile as a battery. One cannot easily insert a micropump into a nonterminal position of a fluidic line without affecting the rest of the fluidic system, one cannot simply connect several micropumps in series to enhance the pressure output, etc. In this work we develop a flow battery (or pressure power supply) to address this issue. A flow battery consists of a +EOP (in which the liquid flows in the same direction as the field gradient) and a −EOP (in which the liquid flows opposite to the electric field gradient), and the outlet of the +EOP is directly connected to the inlet of the −EOP. An external high voltage is applied to this outlet-inlet joint via a short gel-filled capillary that allows ions but not bulk liquid flow, while the +EOP’s inlet and the −EOP’s outlet (the flow battery’s inlet and outlet) are grounded. This flow battery can be deployed anywhere in a fluidic network without electrically affecting the rest of the system. Several flow batteries can be connected in series to enhance the pressure output to drive HPLC separations. In a fluidic system powered by flow batteries, a hydraulic Ohm’s law can be applied to analyze system pressures and flow rates. PMID:21375230

Sliding-mode control of single input multiple output DC-DC converter

Science.gov (United States)

Zhang, Libo; Sun, Yihan; Luo, Tiejian; Wan, Qiyang

2016-10-01

Various voltage levels are required in the vehicle mounted power system. A conventional solution is to utilize an independent multiple output DC-DC converter whose cost is high and control scheme is complicated. In this paper, we design a novel SIMO DC-DC converter with sliding mode controller. The proposed converter can boost the voltage of a low-voltage input power source to a controllable high-voltage DC bus and middle-voltage output terminals, which endow the converter with characteristics of simple structure, low cost, and convenient control. In addition, the sliding mode control (SMC) technique applied in our converter can enhance the performances of a certain SIMO DC-DC converter topology. The high-voltage DC bus can be regarded as the main power source to the high-voltage facility of the vehicle mounted power system, and the middle-voltage output terminals can supply power to the low-voltage equipment on an automobile. In the respect of control algorithm, it is the first time to propose the SMC-PID (Proportion Integration Differentiation) control algorithm, in which the SMC algorithm is utilized and the PID control is attended to the conventional SMC algorithm. The PID control increases the dynamic ability of the SMC algorithm by establishing the corresponding SMC surface and introducing the attached integral of voltage error, which endow the sliding-control system with excellent dynamic performance. At last, we established the MATLAB/SIMULINK simulation model, tested performance of the system, and built the hardware prototype based on Digital Signal Processor (DSP). Results show that the sliding mode control is able to track a required trajectory, which has robustness against the uncertainties and disturbances.

Regulation of Floral Stem Cell Termination in Arabidopsis

Directory of Open Access Journals (Sweden)

Toshiro eIto

2015-02-01

Full Text Available In Arabidopsis, floral stem cells are maintained only at the initial stages of flower development, and they are terminated at a specific time to ensure proper development of the reproductive organs. Floral stem cell termination is a dynamic and multi-step process involving many transcription factors, chromatin remodeling factors and signaling pathways. In this review, we discuss the mechanisms involved in floral stem cell maintenance and termination, highlighting the interplay between transcriptional regulation and epigenetic machinery in the control of specific floral developmental genes. In addition, we discuss additional factors involved in floral stem cell regulation, with the goal of untangling the complexity of the floral stem cell regulatory network.

The C-terminal domains of NF-H and NF-M subunits maintain axonal neurofilament content by blocking turnover of the stationary neurofilament network.

Directory of Open Access Journals (Sweden)

Mala V Rao

Full Text Available Newly synthesized neurofilaments or protofilaments are incorporated into a highly stable stationary cytoskeleton network as they are transported along axons. Although the heavily phosphorylated carboxyl-terminal tail domains of the heavy and medium neurofilament (NF subunits have been proposed to contribute to this process and particularly to stability of this structure, their function is still obscure. Here we show in NF-H/M tail deletion [NF-(H/M(tailΔ] mice that the deletion of both of these domains selectively lowers NF levels 3-6 fold along optic axons without altering either rates of subunit synthesis or the rate of slow axonal transport of NF. Pulse labeling studies carried out over 90 days revealed a significantly faster rate of disappearance of NF from the stationary NF network of optic axons in NF-(H/M(tailΔ mice. Faster NF disappearance was accompanied by elevated levels of NF-L proteolytic fragments in NF-(H/M(tailΔ axons. We conclude that NF-H and NF-M C-terminal domains do not normally regulate NF transport rates as previously proposed, but instead increase the proteolytic resistance of NF, thereby stabilizing the stationary neurofilament cytoskeleton along axons.

Enzyme-Based Logic Gates and Networks with Output Signals Analyzed by Various Methods.

Science.gov (United States)

Katz, Evgeny

2017-07-05

The paper overviews various methods that are used for the analysis of output signals generated by enzyme-based logic systems. The considered methods include optical techniques (optical absorbance, fluorescence spectroscopy, surface plasmon resonance), electrochemical techniques (cyclic voltammetry, potentiometry, impedance spectroscopy, conductivity measurements, use of field effect transistor devices, pH measurements), and various mechanoelectronic methods (using atomic force microscope, quartz crystal microbalance). Although each of the methods is well known for various bioanalytical applications, their use in combination with the biomolecular logic systems is rather new and sometimes not trivial. Many of the discussed methods have been combined with the use of signal-responsive materials to transduce and amplify biomolecular signals generated by the logic operations. Interfacing of biocomputing logic systems with electronics and "smart" signal-responsive materials allows logic operations be extended to actuation functions; for example, stimulating molecular release and switchable features of bioelectronic devices, such as biofuel cells. The purpose of this review article is to emphasize the broad variability of the bioanalytical systems applied for signal transduction in biocomputing processes. All bioanalytical systems discussed in the article are exemplified with specific logic gates and multi-gate networks realized with enzyme-based biocatalytic cascades. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Burst firing enhances neural output correlation

Directory of Open Access Journals (Sweden)

Ho Ka eChan

2016-05-01

Full Text Available Neurons communicate and transmit information predominantly through spikes. Given that experimentally observed neural spike trains in a variety of brain areas can be highly correlated, it is important to investigate how neurons process correlated inputs. Most previous work in this area studied the problem of correlation transfer analytically by making significant simplifications on neural dynamics. Temporal correlation between inputs that arises from synaptic filtering, for instance, is often ignored when assuming that an input spike can at most generate one output spike. Through numerical simulations of a pair of leaky integrate-and-fire (LIF neurons receiving correlated inputs, we demonstrate that neurons in the presence of synaptic filtering by slow synapses exhibit strong output correlations. We then show that burst firing plays a central role in enhancing output correlations, which can explain the above-mentioned observation because synaptic filtering induces bursting. The observed changes of correlations are mostly on a long time scale. Our results suggest that other features affecting the prevalence of neural burst firing in biological neurons, e.g., adaptive spiking mechanisms, may play an important role in modulating the overall level of correlations in neural networks.

Reciprocal synapses between outer hair cells and their afferent terminals: evidence for a local neural network in the mammalian cochlea.

Science.gov (United States)

Thiers, Fabio A; Nadol, Joseph B; Liberman, M Charles

2008-12-01

Cochlear outer hair cells (OHCs) serve both as sensory receptors and biological motors. Their sensory function is poorly understood because their afferent innervation, the type-II spiral ganglion cell, has small unmyelinated axons and constitutes only 5% of the cochlear nerve. Reciprocal synapses between OHCs and their type-II terminals, consisting of paired afferent and efferent specialization, have been described in the primate cochlea. Here, we use serial and semi-serial-section transmission electron microscopy to quantify the nature and number of synaptic interactions in the OHC area of adult cats. Reciprocal synapses were found in all OHC rows and all cochlear frequency regions. They were more common among third-row OHCs and in the apical half of the cochlea, where 86% of synapses were reciprocal. The relative frequency of reciprocal synapses was unchanged following surgical transection of the olivocochlear bundle in one cat, confirming that reciprocal synapses were not formed by efferent fibers. In the normal ear, axo-dendritic synapses between olivocochlear terminals and type-II terminals and/or dendrites were as common as synapses between olivocochlear terminals and OHCs, especially in the first row, where, on average, almost 30 such synapses were seen in the region under a single OHC. The results suggest that a complex local neuronal circuitry in the OHC area, formed by the dendrites of type-II neurons and modulated by the olivocochlear system, may be a fundamental property of the mammalian cochlea, rather than a curiosity of the primate ear. This network may mediate local feedback control of, and bidirectional communication among, OHCs throughout the cochlear spiral.

Interpenetrating polymer networks based on cyanate ester and fluorinated ethynyl-terminated imide oligomers

Directory of Open Access Journals (Sweden)

Y. Wen

2017-12-01

Full Text Available Highly soluble fluorinated ethynyl-terminated imide (FETI oligomers were prepared via a conventional one-step method in m-cresol, using 4, 4′-(hexafluoroisopropylidene diphthalic anhydride and 2, 2′-bis(trifluoromethyl benzidine as the monomers, and ethynylphthalic anhydride as the end-capper; then interpenetrating polymer networks (IPN were formulated from FETI oligomers and bisphenol A dicyanate ester (BADCy through a solvent-free procedure, and their thermal, mechanical, and dielectric properties were fully characterized. The curing mechanism was studied by model reactions using nitrogen nuclear magnetic resonance. As evidenced by differential scanning calorimetry analysis and rheological measurements, the FETI/BADCy blends exhibited lower curing temperature and shorter gelation time in comparison with pure BADCy due to the catalytic effects of ethynyl and residue amic acid groups. The properties of IPNs were fully compared with those of polycyanurate, and the results revealed that the incorporation of FETI into cyanate ester resins could significantly improve the toughness, glass transition temperatures, mechanical and dielectric properties of the resultant IPNs.

The APS control system network

International Nuclear Information System (INIS)

Sidorowicz, K.V.; McDowell, W.P.

1995-01-01

The APS accelerator control system is a distributed system consisting of operator interfaces, a network, and computer-controlled interfaces to hardware. This implementation of a control system has come to be called the open-quotes Standard Model.close quotes The operator interface is a UNDC-based workstation with an X-windows graphical user interface. The workstation may be located at any point on the facility network and maintain full functionality. The function of the network is to provide a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The crate or input/output controller (IOC) provides direct control and input/output interfaces for each accelerator subsystem. The network is an integral part of all modem control systems and network performance will determine many characteristics of a control system. This paper will describe the overall APS network and examine the APS control system network in detail. Metrics are provided on the performance of the system under various conditions

Neural Networks in Control Applications

DEFF Research Database (Denmark)

Sørensen, O.

are examined. The models are separated into three groups representing input/output descriptions as well as state space descriptions: - Models, where all in- and outputs are measurable (static networks). - Models, where some inputs are non-measurable (recurrent networks). - Models, where some in- and some...... outputs are non-measurable (recurrent networks with incomplete state information). The three groups are ordered in increasing complexity, and for each group it is shown how to solve the problems concerning training and application of the specific model type. Of particular interest are the model types...... Kalmann filter) representing state space description. The potentials of neural networks for control of non-linear processes are also examined, focusing on three different groups of control concepts, all considered as generalizations of known linear control concepts to handle also non-linear processes...

Video quality-of-service for consumer terminals : a novel system for programmable components

NARCIS (Netherlands)

Hentschel, C.; Bril, R.J.; Chen, Y.; Braspenning, R.A.C.; Lan, T-H.

2003-01-01

Future consumer terminals will be more and more based on programmable platforms instead of only dedicated hardware. Novel scalable video algorithm (SVA) software modules trade off resource usage against quality of the output signal. SVAs together with a strategy manager and a quality-of-service

VSAT communications networks - An overview

Science.gov (United States)

Chakraborty, D.

1988-05-01

The very-small-aperture-terminal (VSAT) fixed satellite communication network is a star network in which many dispersed micro terminals attempt to send data in a packet form through a random access/time-division multiple-access (RA/TDMA) satellite channel with transmission delay. The basic concept of the VSAT and its service potential are discussed. Two classes of traffic are addressed, namely, business-oriented low-rate-data traffic and bulk data traffic of corporate networks. Satellite access, throughput, and delay are considered. The size of the network population that can be served in an RA/TDMA environment is calculated. User protocols are examined. A typical VSAT business scenario is described.

Analytical methods and simulation models to assess innovative operational measures and technologies for rail port terminals: the case of Valencia Principe Felipe terminal

Energy Technology Data Exchange (ETDEWEB)

Ricci, S.

2016-07-01

The topic of freight transport by rail is a complex theme and, in recent years, a main issue of European policy. The legislation evolution and the White Paper 2011 have demonstrated the European intention to re-launch this sector. The challenge is to promote the intermodal transport system to the detriment of road freight transport. In this context intermodal freight terminals, play a primary role for the supply chain, they are the connection point between the various transport nodes and the nodal points where the freight are handled, stored and transferred between different modes to final customer. To achieve the purpose, it is strengthen the improvement of existing intermodal freight terminals and the development of innovative intermodal freight terminals towards higher performance (ERRAC, 2012). Many terminal performances improvements have been proposed and sometime experimented. They are normally basing on combinations of operational measures and innovative technologies (e.g. automatic horizontal and parallel storage and handling, automated gate and sensors for tracking systems data exchange) tested in various terminals, with often-contradictory results. The research work described in this paper (developed within the Capacity4Rail EU project) focusses on the assessment of effects that these innovations can have in the intermodal freight terminals combined in various alternative consistent effective scenarios. The methodological framework setup to assess these innovations is basing on a combination of analytical methods based on sequential algorithms and discrete events simulation models. The output of this assessment method are key performance indicators (KPIs) selected according to terminals typologies and related to different aspects (e.g. management, operation and organization). The present paper illustrates the application of the methodological framework, tuned on the operation of various intermodal terminals, for the validation on today operation and the

Recurrent Spatial Transformer Networks

DEFF Research Database (Denmark)

Sønderby, Søren Kaae; Sønderby, Casper Kaae; Maaløe, Lars

2015-01-01

We integrate the recently proposed spatial transformer network (SPN) [Jaderberg et. al 2015] into a recurrent neural network (RNN) to form an RNN-SPN model. We use the RNN-SPN to classify digits in cluttered MNIST sequences. The proposed model achieves a single digit error of 1.5% compared to 2.......9% for a convolutional networks and 2.0% for convolutional networks with SPN layers. The SPN outputs a zoomed, rotated and skewed version of the input image. We investigate different down-sampling factors (ratio of pixel in input and output) for the SPN and show that the RNN-SPN model is able to down-sample the input...

Theoretical Evaluation of Crosslink Density of Chain Extended Polyurethane Networks Based on Hydroxyl Terminated Polybutadiene and Butanediol and Comparison with Experimental Data

Science.gov (United States)

Sekkar, Venkataraman; Alex, Ancy Smitha; Kumar, Vijendra; Bandyopadhyay, G. G.

2018-01-01

Polyurethane networks between hydroxyl terminated polybutadiene (HTPB) and butanediol (BD) were prepared using toluene diisocyanate (TDI) as the curative. HTPB and BD were taken at equivalent ratios viz.: 1:0, 1:1, 1:2, 1:4, and 1:8. Crosslink density (CLD) was theoretically calculated using α-model equations developed by Marsh. CLD for the polyurethane networks was experimentally evaluated from equilibrium swell and stress-strain data. Young's modulus and Mooney-Rivlin approaches were adopted to calculate CLD from stress-strain data. Experimentally obtained CLD values were enormously higher than theoretical values especially at higher BD/HTPB equivalent ratios. The difference in the theoretical and experimental values for CLD was explained in terms of local crystallization due to the formation of hard segments and hydrogen bonded interactions.

Dissipation, Voltage Profile and Levy Dragon in a Special Ladder Network

Science.gov (United States)

Ucak, C.

2009-01-01

A ladder network constructed by an elementary two-terminal network consisting of a parallel resistor-inductor block in series with a parallel resistor-capacitor block sometimes is said to have a non-dispersive dissipative response. This special ladder network is created iteratively by replacing the elementary two-terminal network in place of the…

Angle Control-Based Multi-Terminal Out-of-Step Protection System

Directory of Open Access Journals (Sweden)

Antans Sauhats

2017-03-01

Full Text Available From time to time a sequence of unexpected and overlapping contingencies may lead to power system angular instability and even blackouts if not addressed adequately by means of an out-of-step (OOS protection system. The motivation of the paper is an attempt to develop a workable prototype of the OOS protection system. The deficiencies of the protection currently used in the Latvian Power System network are highlighted and a new protection structure is proposed. The protection system comprises of several strategically located terminals, exchanging information in real time by means of a communication network. The OOS condition detection method is based on system-wide generation sources, electromotive forces, vectors, and angle control. The network splitting decision is based on generator coherence evaluation. Protection terminals determine online the groups of coherent generators and choose the splitting boundary from a predefined transmission lines (TLs cut sets list. The protection system structure, algorithm of operation, and possible IEC 61850 communication standard-based implementation are described.

Adaptive Neural Control for a Class of Outputs Time-Delay Nonlinear Systems

Directory of Open Access Journals (Sweden)

Ruliang Wang

2012-01-01

Full Text Available This paper considers an adaptive neural control for a class of outputs time-delay nonlinear systems with perturbed or no. Based on RBF neural networks, the radius basis function (RBF neural networks is employed to estimate the unknown continuous functions. The proposed control guarantees that all closed-loop signals remain bounded. The simulation results demonstrate the effectiveness of the proposed control scheme.

Linear summation of outputs in a balanced network model of motor cortex.

Science.gov (United States)

Capaday, Charles; van Vreeswijk, Carl

2015-01-01

Given the non-linearities of the neural circuitry's elements, we would expect cortical circuits to respond non-linearly when activated. Surprisingly, when two points in the motor cortex are activated simultaneously, the EMG responses are the linear sum of the responses evoked by each of the points activated separately. Additionally, the corticospinal transfer function is close to linear, implying that the synaptic interactions in motor cortex must be effectively linear. To account for this, here we develop a model of motor cortex composed of multiple interconnected points, each comprised of reciprocally connected excitatory and inhibitory neurons. We show how non-linearities in neuronal transfer functions are eschewed by strong synaptic interactions within each point. Consequently, the simultaneous activation of multiple points results in a linear summation of their respective outputs. We also consider the effects of reduction of inhibition at a cortical point when one or more surrounding points are active. The network response in this condition is linear over an approximately two- to three-fold decrease of inhibitory feedback strength. This result supports the idea that focal disinhibition allows linear coupling of motor cortical points to generate movement related muscle activation patterns; albeit with a limitation on gain control. The model also explains why neural activity does not spread as far out as the axonal connectivity allows, whilst also explaining why distant cortical points can be, nonetheless, functionally coupled by focal disinhibition. Finally, we discuss the advantages that linear interactions at the cortical level afford to motor command synthesis.

Output Tracking Control of Switched Hybrid Systems: A Fliess Functional Expansion Approach

Directory of Open Access Journals (Sweden)

Fenghua He

2013-01-01

Full Text Available The output tracking problem is investigated for a nonlinear affine system with multiple modes of continuous control inputs. We convert the family of nonlinear affine systems under consideration into a switched hybrid system by introducing a multiple-valued logic variable. The Fliess functional expansion is adopted to express the input and output relationship of the switched hybrid system. The optimal switching control is determined for a multiple-step output tracking performance index. The proposed approach is applied to a multitarget tracking problem for a flight vehicle aiming for one real target with several decoys flying around it in the terminal guidance course. These decoys appear as apparent targets and have to be distinguished with the approaching of the flight vehicle. The guidance problem of one flight vehicle versus multiple apparent targets should be considered if no large miss distance might be caused due to the limitation of the flight vehicle maneuverability. The target orientation at each time interval is determined. Simulation results show the effectiveness of the proposed method.

X window terminals in TRIUMF's central control system

International Nuclear Information System (INIS)

Kadantsev, S.G.; Kadantseva, T.P.; Davison, B.; Diel, D.A.; Grant, P.A.; Klassen, E.; Lee, K.S.; Mouat, M.M.; Richards, J.E.; Yogendran, P.J.

1994-08-01

TRIUMF's Central Control System is being upgraded. In this process, an environment that suits the needs of cyclotron operational use and the Controls Group's development and maintenance duties has been sought. Over the years since TRIUMF's inception, workstations and a variety of dedicated input/output devices have been introduced into the main console of the Control Room and into the offices of the Controls Group personnel. A number of factors including the overhead of system management, price/performance, time to obsolescence, flexibility, and reliability have affected the suitability of workstations and the other I/O devices. In the new configuration, a generic display device plays a very important role in the Central Control System. X terminals have proven to be superior to workstations and other display devices and are now the display medium of choice in TRIUMF's Controls Group. This paper reviews the TRIUMF Controls Group's experiences with X terminals. A number of aspects of X terminal use in a particle accelerator environment are discussed. Topics include functionality, hardware configuration, software management, relative cost, performance, reliability, boot mechanisms, application suitability, and operator acceptance. (author). 8 refs., 3 figs

V1 spinal neurons regulate the speed of vertebrate locomotor outputs

DEFF Research Database (Denmark)

Gosgnach, Simon; Lanuza, Guillermo M.; Butt, Simon J B

2006-01-01

The neuronal networks that generate vertebrate movements such as walking and swimming are embedded in the spinal cord1-3. These networks, which are referred to as central pattern generators (CPGs), are ideal systems for determining how ensembles of neurons generate simple behavioural outputs...... for inhibition in regulating the frequency of the locomotor CPG rhythm, and also suggest that V1 neurons may have an evolutionarily conserved role in controlling the speed of vertebrate locomotor movements....

Means and method for controlling the neutron output of a neutron generator tube

International Nuclear Information System (INIS)

Langford, O.M.; Peelman, H.E.

1980-01-01

A gas filled neutron tube in a nuclear well logging tool has a target an ion source voltage and a replenisher connected to ground. A negative high voltage is applied to the target by a power supply also providing a target current corresponding to the neutron output of the neutron generator tube. A constant current source provides a constant current. A network receiving the target current and the constant current provides a portion of the constant current as a replenisher current which is applied to the replenisher in a neutron generating tube. The network controls the magnitude of the replenisher current in accordance with the target current so as to control the neutron output of the neutron generating tube. (auth)

Location of Urban Logistic Terminals as Hub Location Problem

Directory of Open Access Journals (Sweden)

Jasmina Pašagić Škrinjar

2012-09-01

Full Text Available In this paper the problems of locating urban logistic terminals are studied as hub location problems that due to a large number of potential nodes in big cities belong to hard non-polynomial problems, the so-called NP-problems. The hub location problems have found wide application in physical planning of transport and telecommunication systems, especially systems of fast delivery, networks of logistic and distribution centres and cargo traffic terminals of the big cities, etc. The paper defines single and multiple allocations and studies the numerical examples. The capacitated single allocation hub location problems have been studied, with the provision of a mathematical model of selecting the location for the hubs on the network. The paper also presents the differences in the possibilities of implementing the exact and heuristic methods to solve the actual location problems of big dimensions i.e. hub problems of the big cities.

Output-Feedback Control for Discrete-Time Spreading Models in Complex Networks

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Luis A. Alarcón Ramos

2018-03-01

Full Text Available The problem of stabilizing the spreading process to a prescribed probability distribution over a complex network is considered, where the dynamics of the nodes in the network is given by discrete-time Markov-chain processes. Conditions for the positioning and identification of actuators and sensors are provided, and sufficient conditions for the exponential stability of the desired distribution are derived. Simulations results for a network of N = 10 6 corroborate our theoretical findings.

Terminal Sliding Mode Control with Unidirectional Auxiliary Surfaces for Hypersonic Vehicles Based on Adaptive Disturbance Observer

Directory of Open Access Journals (Sweden)

Naibao He

2015-01-01

Full Text Available A novel flight control scheme is proposed using the terminal sliding mode technique, unidirectional auxiliary surfaces and the disturbance observer model. These proposed dynamic attitude control systems can improve control performance of hypersonic vehicles despite uncertainties and external disturbances. The terminal attractor is employed to improve the convergence rate associated with the critical damping characteristics problem noted in short-period motions of hypersonic vehicles. The proposed robust attitude control scheme uses a dynamic terminal sliding mode with unidirectional auxiliary surfaces. The nonlinear disturbance observer is designed to estimate system uncertainties and external disturbances. The output of the disturbance observer aids the robust adaptive control scheme and improves robust attitude control performance. Finally, simulation results are presented to illustrate the effectiveness of the proposed terminal sliding mode with unidirectional auxiliary surfaces.

Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model

Directory of Open Access Journals (Sweden)

Fuh-hwa Franklin Liu

2017-01-01

Full Text Available Network DEA models assess production systems that contain a set of network-structured subsystems. Each subsystem has input and output measures from and to the external network and has intermediate measures that link to other subsystems. Most published studies demonstrate how to employ DEA models to establish network DEA models. Neither static nor dynamic network DEA models adjust the links. This paper applies the virtual gap measurement (VGM model to construct a mixed integer program to solve dynamic network DEA problems. The mixed integer program sets the total numbers of “as-input” and “as-output” equal to the total number of links in the objective function. To obtain the best-practice efficiency, each DMU determines a set of weights for inputs, outputs, and links. The links are played either “as-input” or “as-output.” Input and as-input measures reduce slack, whereas output and as-output measures increase slacks to attain their target on the production frontier.

The quality of service in passenger transport terminals

Science.gov (United States)

Oprea, C.; Roşca, E.; Popa, M.; Ilie, A.; Dinu, O.; Roşca, M.

2016-11-01

The quality of service in transport terminals is differently perceived by engineers, economists, transport operators and sociologists. The traveler's perception is nevertheless decisive. The quality of service is well connected with the inside design of terminals, with the facilities in terminals and with the provided service standards. In order to provide a high level of service, the activities taking place in the public transport terminal and the maximum travelers flow size must be carefully analyzed and dimensioned. The purpose of modelling is to find the best route for each traveler from origin (entrance) to destination (exit) through all the intermediate service points, taking into consideration the instant network conditions. In developing the model we consider the walking, the waiting and the serving time. Using a simulation program written in ARENA we determine the waiting time. For validation, the model is used to evaluate the performance level in Bucharest Basarab station. By comparing the total walking distance for the possible routes and the utility function that describes the utility of all activities from entrance to exit we can find the optimal route.

Stand-Alone Microgrid Inverter Controller Design for Nonlinear, Unbalanced Load with Output Transformer

Directory of Open Access Journals (Sweden)

Jae-Uk Lim

2018-04-01

Full Text Available This paper proposes a technique that compensates for unbalance and nonlinearity in microgrid inverters with power transformers operating in stand-alone mode. When a microgrid inverter is operating in stand-alone mode, providing high-quality power is very important. When an unbalanced, nonlinear load is connected, zero sequence current and negative sequence current occur, which leads to an unbalanced output voltage. This paper examines why the zero sequence component occurs differently depending on the structure of a three-phase transformer connected to the inverter output terminal, and it proposes a method for controlling the zero sequence component. It also uses a resonant controller to remove the harmonics that correspond to the negative sequence component and the nonlinear component. The proposed elements were verified by a Powersim (PSIM simulation.

Nonlinear behavior of three-terminal graphene junctions at room temperature

International Nuclear Information System (INIS)

Kim, Wonjae; Riikonen, Juha; Lipsanen, Harri; Pasanen, Pirjo

2012-01-01

We demonstrate nonlinear behavior in three-terminal T-branch graphene devices at room temperature. A rectified nonlinear output at the center branch is observed when the device is biased by a push–pull configuration. Nonlinearity is assumed to arise from a difference in charge transfer through the metal–graphene contact barrier between two contacts. The sign of the rectification can be altered by changing the carrier type using the back-gate voltage. (paper)

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

2005-07-01

Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

Polling-Based High-Bit-Rate Packet Transfer in a Microcellular Network to Allow Fast Terminals

Science.gov (United States)

Hoa, Phan Thanh; Lambertsen, Gaute; Yamada, Takahiko

A microcellular network will be a good candidate for the future broadband mobile network. It is expected to support high-bit-rate connection for many fast mobile users if the handover is processed fast enough to lessen its impact on QoS requirements. One of the promising techniques is believed to use for the wireless interface in such a microcellular network is the WLAN (Wireless LAN) technique due to its very high wireless channel rate. However, the less capability of mobility support of this technique must be improved to be able to expand its utilization for the microcellular environment. The reason of its less support mobility is large handover latency delay caused by contention-based handover to the new BS (base station) and delay of re-forwarding data from the old to new BS. This paper presents a proposal of multi-polling and dynamic LMC (Logical Macro Cell) to reduce mentioned above delays. Polling frame for an MT (Mobile Terminal) is sent from every BS belonging to the same LMC — a virtual single macro cell that is a multicast group of several adjacent micro-cells in which an MT is communicating. Instead of contending for the medium of a new BS during handover, the MT responds to the polling sent from that new BS to enable the transition. Because only one BS of the LMC receives the polling ACK (acknowledgement) directly from the MT, this ACK frame has to be multicast to all BSs of the same LMC through the terrestrial network to continue sending the next polling cycle at each BS. Moreover, when an MT hands over to a new cell, its current LMC is switched over to a newly corresponding LMC to prevent the future contending for a new LMC. By this way, an MT can do handover between micro-cells of an LMC smoothly because the redundant resource is reserved for it at neighboring cells, no need to contend with others. Our simulation results using the OMNeT++ simulator illustrate the performance achievements of the multi-polling and dynamic LMC scheme in eliminating

Chinese very small aperture terminal system for ministries

Science.gov (United States)

Dan, Sen

The objective and technologic approach of the Chinese very small aperture terminal (VSAT) system of data communications is described in this paper. The system is primarily designed for the management business of many governmental ministries and administrations. It consists of a centralized processing and switching facility and a number of groups of remote terminals. The network is constructed in a star configuration because of simplicity and the inherent nature of the management business. Either Intelsat of Chinese domestic communications satellite can be used for the space segment. The system performance has been verified by field trials. Some results of system analysis can be used for traffic design.

Implementation method of multi-terminal DC control system

Science.gov (United States)

Yi, Liu; Hao-Ran, Huang; Jun-Wen, Zhou; Hong-Guang, Guo; Yu-Yong, Zhou

2018-04-01

Currently the multi-terminal DC system (MTDC) has more stations. Each station needs operators to monitor and control the device. It needs much more operation and maintenance, low efficiency and small reliability; for the most important reason, multi-terminal DC system has complex control mode. If one of the stations has some problem, the control of the whole system should have problems. According to research of the characteristics of multi-terminal DC (VSC-MTDC) systems, this paper presents a strong implementation of the multi-terminal DC Supervisory Control and Data Acquisition (SCADA) system. This system is intelligent, can be networking, integration and intelligent. A master control system is added in each station to communication with the other stations to send current and DC voltage value to pole control system for each station. Based on the practical application and information feedback in the China South Power Grid research center VSC-MTDC project, this system is higher efficiency and save the cost on the maintenance of convertor station to improve the intelligent level and comprehensive effect. And because of the master control system, a multi-terminal system hierarchy coordination control strategy is formed, this make the control and protection system more efficiency and reliability.

Design and implementation of a 3-A source and sink linear regulator for bus terminators

International Nuclear Information System (INIS)

Li Yanming; Wen Changbao; Wen Limin; Mao Xiangyu

2012-01-01

According to the requirements of the bus terminal regulator, a linear regulator with 3-A source-sink current ability is presented. The use of the NMOS pass transistor and load current feedback technique enhances the system current ability and response speed. The method of adaptive zero compensation realizes loop stability over the whole load range for either source or sink loop. Furthermore, the transconductance matching technique reduces the shoot-through current through the output stage to less than 3 μA. The regulator has been fabricated with a 0.6-μm 30 V BCD process successfully, and the area size is about 1 mm 2 . With a 20 μF output capacitor, the maximum transient output-voltage variation is within 3.5% of the output voltage with load step changes of ±2 A/1 μs. At the load range of ±3 A, the variation of output voltage is less than ±15 mV.

Network analysis of Chinese provincial economies

Science.gov (United States)

Sun, Xiaoqi; An, Haizhong; Liu, Xiaojia

2018-02-01

Global economic system is a huge network formed by national subnetworks that contains the provincial networks. As the second largest world economy, China has "too big to fail" impact on the interconnected global economy. Detecting the critical sectors and vital linkages inside Chinese economic network is meaningful for understanding the origin of this Chinese impact. Different from tradition network research at national level, this paper focuses on the provincial networks and inter-provincial network. Using Chinese inter-regional input-output table to construct 30 provincial input-output networks and one inter-provincial input-output network, we identify central sectors and vital linkages, as well as analyze economic structure similarity. Results show that (1) Communication Devices sector in Guangdong and that in Jiangsu, Transportation and Storage sector in Shanghai play critical roles in Chinese economy. (2) Advanced manufactures and services industry occupy the central positions in eastern provincial economies, while Construction sector, Heavy industry, and Wholesale and Retail Trades sector are influential in middle and western provinces. (3) The critical monetary flow paths in Chinese economy are Communication Devices sector to Communication Devices sector in Guangdong, Metals Mining sector to Iron and Steel Smelting sector in Henan, Communication Devices sector to Communication Devices sector in Jiangsu, as well as Petroleum Mining sector in Heilongjiang to Petroleum Processing sector in Liaoning. (4) Collective influence results suggest that Finance sector, Transportation and Storage sector, Production of Electricity and Heat sector, and Rubber and Plastics sector in Hainan are strategic influencers, despite being weakly connected. These sectors and input-output relations are worthy of close attention for monitoring Chinese economy.

Parallel consensual neural networks.

Science.gov (United States)

Benediktsson, J A; Sveinsson, J R; Ersoy, O K; Swain, P H

1997-01-01

A new type of a neural-network architecture, the parallel consensual neural network (PCNN), is introduced and applied in classification/data fusion of multisource remote sensing and geographic data. The PCNN architecture is based on statistical consensus theory and involves using stage neural networks with transformed input data. The input data are transformed several times and the different transformed data are used as if they were independent inputs. The independent inputs are first classified using the stage neural networks. The output responses from the stage networks are then weighted and combined to make a consensual decision. In this paper, optimization methods are used in order to weight the outputs from the stage networks. Two approaches are proposed to compute the data transforms for the PCNN, one for binary data and another for analog data. The analog approach uses wavelet packets. The experimental results obtained with the proposed approach show that the PCNN outperforms both a conjugate-gradient backpropagation neural network and conventional statistical methods in terms of overall classification accuracy of test data.

Multi-terminal direct-current grids modeling, analysis, and control

CERN Document Server

Chaudhuri, Nilanjan; Majumder, Rajat; Yazdani, Amirnaser

2014-01-01

A comprehensive modeling, analysis, and control design framework for multi-terminal direct current (MTDC) grids is presented together with their interaction with the surrounding AC networks and the impact on overall stability. The first book of its kind on the topic of multi-terminal DC (MTDC) grids  Presents a comprehensive modeling framework for MTDC grids which is compatible with the standard AC system modeling for stability studies Includes modal analysis and study of the interactions between the MTDC grid and the surrounding AC systems Addresses the problems of autonomous power sharing an

Development of A 402.5 MHz 140 kW Inductive Output Tube

International Nuclear Information System (INIS)

Ives, R. Lawrence; Read, Michael; Jackson, Robert

2012-01-01

This report contains the results of Phase I of an SBIR to develop a Pulsed Inductive Output Tube (IOT) with 140 kW at 400 MHz for powering H-proton beams. A number of sources, including single beam and multiple beam klystrons, can provide this power, but the IOT provides higher efficiency. Efficiencies exceeding 70% are routinely achieved. The gain is typically limited to approximately 24 dB; however, the availability of highly efficient, solid state drivers reduces the significance of this limitation, particularly at lower frequencies. This program initially focused on developing a 402 MHz IOT; however, the DOE requirement for this device was terminated during the program. The SBIR effort was refocused on improving the IOT design codes to more accurately simulate the time dependent behavior of the input cavity, electron gun, output cavity, and collector. Significant improvement was achieved in modeling capability and simulation accuracy.

Downscaling Global Weather Forecast Outputs Using ANN for Flood Prediction

Directory of Open Access Journals (Sweden)

Nam Do Hoai

2011-01-01

Full Text Available Downscaling global weather prediction model outputs to individual locations or local scales is a common practice for operational weather forecast in order to correct the model outputs at subgrid scales. This paper presents an empirical-statistical downscaling method for precipitation prediction which uses a feed-forward multilayer perceptron (MLP neural network. The MLP architecture was optimized by considering physical bases that determine the circulation of atmospheric variables. Downscaled precipitation was then used as inputs to the super tank model (runoff model for flood prediction. The case study was conducted for the Thu Bon River Basin, located in Central Vietnam. Study results showed that the precipitation predicted by MLP outperformed that directly obtained from model outputs or downscaled using multiple linear regression. Consequently, flood forecast based on the downscaled precipitation was very encouraging. It has demonstrated as a robust technology, simple to implement, reliable, and universal application for flood prediction through the combination of downscaling model and super tank model.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

Science.gov (United States)

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass

Directory of Open Access Journals (Sweden)

Mohammad Hasan Shojaeefard

2013-01-01

Full Text Available Al-Mg and CuZn34 alloys were lap joined using friction stir welding while the aluminum alloy sheet was placed on the CuZn34. In addition, the mechanical properties of each sample were characterized using shear tests. Scanning electron microscopy (SEM and X-ray diffraction analysis were used to probe chemical compositions. An artificial neural network model was developed to simulate the correlation between the Friction Stir Lap Welding (FSLW parameters and mechanical properties. Subsequently, a sensitivity analysis was performed to investigate the effect of each input parameter on the output in terms of magnitude and direction. Four methods, namely, the “PaD” method, the “Weights” method, the “Profile” method, and the “backward stepwise” method, which can give the relative contribution and/or the contribution profile of the input factors, were compared. The PaD method, giving the most complete results, was found to be the most useful, followed by the Profile method that gave the contribution profile of the input variables.

Stochastic simulation of off-shore oil terminal systems

International Nuclear Information System (INIS)

Frankel, E.G.; Oberle, J.

1991-01-01

To cope with the problem of uncertainty and conditionality in the planning, design, and operation of offshore oil transshipment terminal systems, a conditional stochastic simulation approach is presented. Examples are shown, using SLAM II, a computer simulation language based on GERT, a conditional stochastic network analysis methodology in which use of resources such as time and money are expressed by the moment generating function of the statistics of the resource requirements. Similarly each activity has an associated conditional probability of being performed and/or of requiring some of the resources. The terminal system is realistically represented by modelling the statistics of arrivals, loading and unloading times, uncertainties in costs and availabilities, etc

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

Science.gov (United States)

Liang, Yaping; Chang, Qing; Li, Xianxu

2018-04-01

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

Driver compliance to take-over requests with different auditory outputs in conditional automation.

Science.gov (United States)

Forster, Yannick; Naujoks, Frederik; Neukum, Alexandra; Huestegge, Lynn

2017-12-01

Conditionally automated driving (CAD) systems are expected to improve traffic safety. Whenever the CAD system exceeds its limit of operation, designers of the system need to ensure a safe and timely enough transition from automated to manual mode. An existing visual Human-Machine Interface (HMI) was supplemented by different auditory outputs. The present work compares the effects of different auditory outputs in form of (1) a generic warning tone and (2) additional semantic speech output on driver behavior for the announcement of an upcoming take-over request (TOR). We expect the information carried by means of speech output to lead to faster reactions and better subjective evaluations by the drivers compared to generic auditory output. To test this assumption, N=17 drivers completed two simulator drives, once with a generic warning tone ('Generic') and once with additional speech output ('Speech+generic'), while they were working on a non-driving related task (NDRT; i.e., reading a magazine). Each drive incorporated one transition from automated to manual mode when yellow secondary lanes emerged. Different reaction time measures, relevant for the take-over process, were assessed. Furthermore, drivers evaluated the complete HMI regarding usefulness, ease of use and perceived visual workload just after experiencing the take-over. They gave comparative ratings on usability and acceptance at the end of the experiment. Results revealed that reaction times, reflecting information processing time (i.e., hands on the steering wheel, termination of NDRT), were shorter for 'Speech+generic' compared to 'Generic' while reaction time, reflecting allocation of attention (i.e., first glance ahead), did not show this difference. Subjective ratings were in favor of the system with additional speech output. Copyright © 2017 Elsevier Ltd. All rights reserved.

Physical properties of a high molecular weight hydroxyl-terminated polydimethylsiloxane modified castor oil based polyurethane/epoxy interpenetrating polymer network composites

Science.gov (United States)

Chen, Shoubing; Wang, Qihua; Wang, Tingmei

2011-06-01

A series of polyurethane (PU)/epoxy resin (EP) graft interpenetrating polymer network (IPN) composites modified by a high molecular weight hydroxyl-terminated polydimethylsiloxane (HTPDMS) were prepared. The effects of HTPDMS content on the phase structure, damping properties and the glass transition temperature ( Tg) of the HTPDMS-modified PU/EP IPN composites were studied by scanning electron microscopy (SEM) and dynamic mechanical analysis (DMA). Thermogravimetric analysis (TGA) showed that the thermal decomposition temperature of the composites increased with the increase of HTPDMS content. The tensile strength and impact strength of the IPN composites were also significantly improved, especially when the HTPDMS content was 10%. The modified IPN composites were expected to be used as structural damping materials in the future.

3D PLUS HI-REL DDR2 Termination Regulator Module- A Building Block Function for High Reliability SDRAM DDR2 System Architecture

Science.gov (United States)

Perrot, Nicolas; Dubus, Patrick; Garcia-Sanchez, Esther

2015-09-01

Memory system architectures using DDR2 technology need to be compliant with JEDEC JESD8-15A standard [1]. Therefore a bus termination regulator able to sink and source current while regulating VTT voltage is used for this purpose. Such module has been developed by 3D PLUS and is the first space qualified DDR Termination Regulator (DDR2-TR) available on the market. It is based on an innovative Bang-Bang regulation principle, chosen for its speed performance and to guarantee an output voltage that remains within the predefined limits regardless of any output current transients. The output filter type is selected to make the module rugged to any overload condition without complex protection circuits. The module has been specifically designed for low input voltage, low noise and high reliability systems where space is a key consideration. The module uses the 3D PLUS SIP (System-In-Package) technology embedding 3 stacked PCBs. No external filters or decoupling capacitors are needed.

Networks and Transaction Costs

DEFF Research Database (Denmark)

Henning, Christian; Henningsen, Geraldine; Henningsen, Arne

2011-01-01

Based on the well-known fact that social networks can provide effective mechanisms that help to increase the trust level between two trade partners, we apply a simple game-theoretical framework to derive transaction costs as a high risk of opportunistic behavior in a repeated trade relation...... determined by the density and size of trading networks. In the empirical part of the paper we apply a two stage procedure to estimate the impact of social network structures on farm’s transaction costs observed for different input and output markets. At a first stage we estimate a multiple input...... transaction cost functions for all traded farm inputs and outputs. Estimation results based on a sample of 315 Polish farms imply a significant influence of social network structures on farm’s transaction costs. Moreover, estimated transaction costs correspond to a reasonable amount of farm specific shadow...

Networks and Transaction Costs

DEFF Research Database (Denmark)

Henning, Christian; Henningsen, Geraldine; Henningsen, Arne

2011-01-01

determined by the density and size of trading networks. In the empirical part of the paper we apply a two stage procedure to estimate the impact of social network structures on farm’s transaction costs observed for different input and output markets. At a first stage we estimate a multiple input......Based on the well-known fact that social networks can provide effective mechanisms that help to increase the trust level between two trade partners, we apply a simple game-theoretical framework to derive transaction costs as a high risk of opportunistic behavior in a repeated trade relation...... transaction cost functions for all traded farm inputs and outputs. Estimation results based on a sample of 315 Polish farms imply a significant influence of social network structures on farm’s transaction costs. Moreover, estimated transaction costs correspond to a reasonable amount of farm specific shadow...

Comparison of crisp and fuzzy character networks in handwritten word recognition

Science.gov (United States)

Gader, Paul; Mohamed, Magdi; Chiang, Jung-Hsien

1992-01-01

Experiments involving handwritten word recognition on words taken from images of handwritten address blocks from the United States Postal Service mailstream are described. The word recognition algorithm relies on the use of neural networks at the character level. The neural networks are trained using crisp and fuzzy desired outputs. The fuzzy outputs were defined using a fuzzy k-nearest neighbor algorithm. The crisp networks slightly outperformed the fuzzy networks at the character level but the fuzzy networks outperformed the crisp networks at the word level.

Two-terminal reliability analyses for a mobile ad hoc wireless network

International Nuclear Information System (INIS)

Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

2007-01-01

Reliability is one of the most important performance measures for emerging technologies. For these systems, shortcomings are often overlooked in early releases as the cutting edge technology overshadows a fragile design. Currently, the proliferation of the mobile ad hoc wireless networks (MAWN) is moving from cutting edge to commodity and thus, reliable performance will be expected. Generally, ad hoc networking is applied for the flexibility and mobility it provides. As a result, military and first responders employ this network scheme and the reliability of the network becomes paramount. To ensure reliability is achieved, one must first be able to analyze and calculate the reliability of the MAWN. This work describes the unique attributes of the MAWN and how the classical analysis of network reliability, where the network configuration is known a priori, can be adjusted to model and analyze this type of network. The methods developed acknowledge the dynamic and scalable nature of the MAWN along with its absence of infrastructure. Thus, the methods rely on a modeling approach that considers the probabilistic formation of different network configurations in a MAWN. Hence, this paper proposes reliability analysis methods that consider the effect of node mobility and the continuous changes in the network's connectivity

Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

Energy Technology Data Exchange (ETDEWEB)

Carta, Jose A. [Department of Mechanical Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Velazquez, Sergio [Department of Electronics and Automatics Engineering, University of Las Palmas de Gran Canaria, Campus de Tafira s/n, 35017 Las Palmas de Gran Canaria, Canary Islands (Spain); Matias, J.M. [Department of Statistics, University of Vigo, Lagoas Marcosende, 36200 Vigo (Spain)

2011-02-15

Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station. (author)

Use of Bayesian networks classifiers for long-term mean wind turbine energy output estimation at a potential wind energy conversion site

International Nuclear Information System (INIS)

Carta, Jose A.; Velazquez, Sergio; Matias, J.M.

2011-01-01

Due to the interannual variability of wind speed a feasibility analysis for the installation of a Wind Energy Conversion System at a particular site requires estimation of the long-term mean wind turbine energy output. A method is proposed in this paper which, based on probabilistic Bayesian networks (BNs), enables estimation of the long-term mean wind speed histogram for a site where few measurements of the wind resource are available. For this purpose, the proposed method allows the use of multiple reference stations with a long history of wind speed and wind direction measurements. That is to say, the model that is proposed in this paper is able to involve and make use of regional information about the wind resource. With the estimated long-term wind speed histogram and the power curve of a wind turbine it is possible to use the method of bins to determine the long-term mean energy output for that wind turbine. The intelligent system employed, the knowledgebase of which is a joint probability function of all the model variables, uses efficient calculation techniques for conditional probabilities to perform the reasoning. This enables automatic model learning and inference to be performed efficiently based on the available evidence. The proposed model is applied in this paper to wind speeds and wind directions recorded at four weather stations located in the Canary Islands (Spain). Ten years of mean hourly wind speed and direction data are available for these stations. One of the conclusions reached is that the BN with three reference stations gave fewer errors between the real and estimated long-term mean wind turbine energy output than when using two measure-correlate-predict algorithms which were evaluated and which use a linear regression between the candidate station and one reference station.

PowerFactory model for multi-terminal HVDC network with DC voltage droop control

DEFF Research Database (Denmark)

Korompili, Asimenia; Wu, Qiuwei

Nowadays, most of the installed HVDC systems are based on line commutated converters (LCC), since this technology offers a series of advantages, mainly low costs and losses. However, voltage source converters (VSCs) have recently drawn more and more attention, due to their high controllability....... Moreover, recent developments have improved efficiency and power quality. For multi-terminal HVDC grids, the advantages of VSCs become so large, that VSC-HVDC systems are the only viable solution. Nevertheless, no VSC-based multi-terminal HVDC grids exist to date. This is the reason for which many research...

Evaluating primary forest fuel rail terminals with discrete event simulation: A case study from Austria

OpenAIRE

Ulrich J. Wolfsmayr; Rossana Merenda; Peter Rauch; Francesco Longo; Manfred Gronalt

2016-01-01

Biomass rail transport is a useful alternative to unimodal truck transport for medium or long transport distances, if only a short road pre-haulage is required. Up to now primary forest fuels (PFF) are rarely transported on the rail network in Austria and rail terminals able to tranship notable volumes are not established yet. The objective of this study is to investigate the potentials of existing transhipment infrastructure for introducing and operating PFF terminals. Such PFF terminals ena...

Unit 16 - Output

OpenAIRE

Unit 16, CC in GIS; Star, Jeffrey L.

1990-01-01

This unit discusses issues related to GIS output, including the different types of output possible and the hardware for producing each. It describes text, graphic and digital data that can be generated by a GIS as well as line printers, dot matrix printers/plotters, pen plotters, optical scanners and cathode ray tubes (CRTs) as technologies for generating the output.

Computationally Efficient Transient Stability Modeling of multi-terminal VSC-HVDC

DEFF Research Database (Denmark)

van der Meer, Arjen A; Rueda-Torres, José; Silva, Filipe Miguel Faria da

2016-01-01

This paper studies the inclusion of averaged VSC-based grid interfaces and HVDC networks into stability type simulations, and compares the accuracy and speed of three multi-terminal DC dynamic models: 1) a state-space based model, 2) a multi-rate improved model, and 3) a reduced-order model...

Research into the Effect of Supercapacitor Terminal Voltage on Regenerative Suspension Energy-Regeneration and Dynamic Performance

Directory of Open Access Journals (Sweden)

Ruochen Wang

2017-01-01

Full Text Available To study the effect of supercapacitor initial terminal voltage on the regenerative and semiactive suspension energy-regeneration and dynamic performance, firstly, the relationship between supercapacitor terminal voltage and linear motor electromagnetic damping force and that between supercapacitor terminal voltage and recycled energy by the supercapacitor in one single switching period were both analyzed. The result shows that the linear motor electromagnetic damping force is irrelevant to the supercapacitor terminal voltage, and the recycled energy by the supercapacitor reaches the maximum when initial terminal voltage of the supercapacitor equals output terminal voltage of the linear motor. Then, performances of system dynamics and energy-regeneration were studied as the supercapacitor initial terminal voltage varied in situations of B level and C level road. The result showed that recycled energy by the supercapacitor increased at first and then decreased while the dynamic performance had no obvious change. On the basis of previous study, a mode-switching control strategy of supercapacitor for the regenerative and semiactive suspension system was proposed, and the mode-switching rule was built. According to simulation and experiment results, the system energy-regeneration efficiency can be increased by utilizing the control strategy without influencing suspension dynamic performance, which is highly valuable to practical engineering.

Ties that tear apart : the social embeddedness of strategic alliance termination

NARCIS (Netherlands)

Rooks, G.; Snijders, C.C.P.; Duysters, G.M.

2013-01-01

Strategic alliances between firms are inherently unstable, and many alliances fail before the planned termination date. Most studies of the instability of strategic alliances focus on internal factors, such as tensions between alliance partners. In the present study social networks, in particular

Ties that tear apart. The social embeddedness of strategic alliance termination

NARCIS (Netherlands)

Rook, G.; Snijders, C.; Duijsters, G.M.

2013-01-01

Strategic alliances between firms are inherently unstable, and many alliances fail before the planned termination date. Most studies of the instability of strategic alliances focus on internal factors, such as tensions between alliance partners. In the present study social networks, in particular

Porous Cross-Linked Polyimide-Urea Networks

Science.gov (United States)

Meador, Mary Ann B. (Inventor); Nguyen, Baochau N. (Inventor)

2015-01-01

Porous cross-linked polyimide-urea networks are provided. The networks comprise a subunit comprising two anhydride end-capped polyamic acid oligomers in direct connection via a urea linkage. The oligomers (a) each comprise a repeating unit of a dianhydride and a diamine and a terminal anhydride group and (b) are formulated with 2 to 15 of the repeating units. The subunit was formed by reaction of the diamine and a diisocyanate to form a diamine-urea linkage-diamine group, followed by reaction of the diamine-urea linkage-diamine group with the dianhydride and the diamine to form the subunit. The subunit has been cross-linked via a cross-linking agent, comprising three or more amine groups, at a balanced stoichiometry of the amine groups to the terminal anhydride groups. The subunit has been chemically imidized to yield the porous cross-linked polyimide-urea network. Also provided are wet gels, aerogels, and thin films comprising the networks, and methods of making the networks.

Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

Science.gov (United States)

Sadeh, Sadra; Rotter, Stefan

2015-01-01

The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are robust and do not

Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.

Directory of Open Access Journals (Sweden)

Sadra Sadeh

2015-01-01

Full Text Available The neuronal mechanisms underlying the emergence of orientation selectivity in the primary visual cortex of mammals are still elusive. In rodents, visual neurons show highly selective responses to oriented stimuli, but neighboring neurons do not necessarily have similar preferences. Instead of a smooth map, one observes a salt-and-pepper organization of orientation selectivity. Modeling studies have recently confirmed that balanced random networks are indeed capable of amplifying weakly tuned inputs and generating highly selective output responses, even in absence of feature-selective recurrent connectivity. Here we seek to elucidate the neuronal mechanisms underlying this phenomenon by resorting to networks of integrate-and-fire neurons, which are amenable to analytic treatment. Specifically, in networks of perfect integrate-and-fire neurons, we observe that highly selective and contrast invariant output responses emerge, very similar to networks of leaky integrate-and-fire neurons. We then demonstrate that a theory based on mean firing rates and the detailed network topology predicts the output responses, and explains the mechanisms underlying the suppression of the common-mode, amplification of modulation, and contrast invariance. Increasing inhibition dominance in our networks makes the rectifying nonlinearity more prominent, which in turn adds some distortions to the otherwise essentially linear prediction. An extension of the linear theory can account for all the distortions, enabling us to compute the exact shape of every individual tuning curve in our networks. We show that this simple form of nonlinearity adds two important properties to orientation selectivity in the network, namely sharpening of tuning curves and extra suppression of the modulation. The theory can be further extended to account for the nonlinearity of the leaky model by replacing the rectifier by the appropriate smooth input-output transfer function. These results are

A Squeezed Artificial Neural Network for the Symbolic Network Reliability Functions of Binary-State Networks.

Science.gov (United States)

Yeh, Wei-Chang

Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

Cellular Mechanisms Underlying Behavioral State-Dependent Bidirectional Modulation of Motor Cortex Output

Directory of Open Access Journals (Sweden)

Julia Schiemann

2015-05-01

Full Text Available Neuronal activity in primary motor cortex (M1 correlates with behavioral state, but the cellular mechanisms underpinning behavioral state-dependent modulation of M1 output remain largely unresolved. Here, we performed in vivo patch-clamp recordings from layer 5B (L5B pyramidal neurons in awake mice during quiet wakefulness and self-paced, voluntary movement. We show that L5B output neurons display bidirectional (i.e., enhanced or suppressed firing rate changes during movement, mediated via two opposing subthreshold mechanisms: (1 a global decrease in membrane potential variability that reduced L5B firing rates (L5Bsuppressed neurons, and (2 a coincident noradrenaline-mediated increase in excitatory drive to a subpopulation of L5B neurons (L5Benhanced neurons that elevated firing rates. Blocking noradrenergic receptors in forelimb M1 abolished the bidirectional modulation of M1 output during movement and selectively impaired contralateral forelimb motor coordination. Together, our results provide a mechanism for how noradrenergic neuromodulation and network-driven input changes bidirectionally modulate M1 output during motor behavior.

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

Science.gov (United States)

Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

47 CFR 68.354 - Numbering and labeling requirements for terminal equipment.

Science.gov (United States)

2010-10-01

... no competitive advantage for any entity or segment of the industry. (e) FCC numbering and labeling...) COMMON CARRIER SERVICES (CONTINUED) CONNECTION OF TERMINAL EQUIPMENT TO THE TELEPHONE NETWORK Conditions.... Customs Service to carry out their functions, and for consumers to easily identify the responsible party...

Forkhead Box C1 Regulates Human Primary Keratinocyte Terminal Differentiation.

Directory of Open Access Journals (Sweden)

Lianghua Bin

Full Text Available The epidermis serves as a critical protective barrier between the internal and external environment of the human body. Its remarkable barrier function is established through the keratinocyte (KC terminal differentiation program. The transcription factors specifically regulating terminal differentiation remain largely unknown. Using a RNA-sequencing (RNA-seq profiling approach, we found that forkhead box c 1 (FOXC1 was significantly up-regulated in human normal primary KC during the course of differentiation. This observation was validated in human normal primary KC from several different donors and human skin biopsies. Silencing FOXC1 in human normal primary KC undergoing differentiation led to significant down-regulation of late terminal differentiation genes markers including epidermal differentiation complex genes, keratinization genes, sphingolipid/ceramide metabolic process genes and epidermal specific cell-cell adhesion genes. We further demonstrated that FOXC1 works down-stream of ZNF750 and KLF4, and upstream of GRHL3. Thus, this study defines FOXC1 as a regulator specific for KC terminal differentiation and establishes its potential position in the genetic regulatory network.

Artificial Neural Network with Hardware Training and Hardware Refresh

Science.gov (United States)

Duong, Tuan A. (Inventor)

2003-01-01

A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

The use of output-dependent data scaling with artificial neural networks and multilinear regression for modeling of ciprofloxacin removal from aqueous solution

Directory of Open Access Journals (Sweden)

Ulaş Yurtsever

2017-03-01

Full Text Available In this study, an experimental system entailing ciprofloxacin hydrochloride (CIP removal from aqueous solution is modeled by using artificial neural networks (ANNs. For modeling of CIP removal from aqueous solution using bentonite and activated carbon, we utilized the combination of output-dependent data scaling (ODDS with ANN, and the combination of ODDS with multivariable linear regression model (MVLR. The ANN model normalized via ODDS performs better in comparison with the ANN model scaled via standard normalization. Four distinct hybrid models, ANN with standard normalization, ANN with ODDS, MVLR with standard normalization, and MVLR with ODDS, were also applied. We observed that ANN and MVLR estimations’ consistency, accuracy ratios and model performances increase as a result of pre-processing with ODDS.

Computing preimages of Boolean networks.

Science.gov (United States)

Klotz, Johannes; Bossert, Martin; Schober, Steffen

2013-01-01

In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.

Do Policy Networks lead to Network Governing?

DEFF Research Database (Denmark)

Damgaard, Bodil

This paper challenges the notion that creation of local policy networks necessarily leads to network governing. Through actor-centred case studies in the area of municipally implemented employment policy in Denmark it was found that the local governing mode is determined mainly by the municipality......’s approach to local co-governing as well as by the capacity and interest of key private actors. It is argued that national legislation requesting the creation of local policy networks was not enough to assure network governing and the case studies show that local policy networks may subsist also under...... hierarchical governing modes. Reasons why hierarchical governing modes prevail over network governing in some settings are identified pointing to both actor borne and structural factors. Output indicators of the four cases do not show that a particular governing mode is more efficient in its employment policy...

Autonomous Navigation Apparatus With Neural Network for a Mobile Vehicle

Science.gov (United States)

Quraishi, Naveed (Inventor)

1996-01-01

An autonomous navigation system for a mobile vehicle arranged to move within an environment includes a plurality of sensors arranged on the vehicle and at least one neural network including an input layer coupled to the sensors, a hidden layer coupled to the input layer, and an output layer coupled to the hidden layer. The neural network produces output signals representing respective positions of the vehicle, such as the X coordinate, the Y coordinate, and the angular orientation of the vehicle. A plurality of patch locations within the environment are used to train the neural networks to produce the correct outputs in response to the distances sensed.

The tariffs of use of liquefied natural gas transportation networks and facilities

International Nuclear Information System (INIS)

2005-01-01

The new tariff proposals for the use of natural gas transportation networks were transmitted to the French Ministry of economy, finances and industry on October 27, 2004 by the commission of energy regulation. These proposals have been adopted and are the object of three legislative texts: the decree no. 2005-607 from May 27 2005 relative to the tariffing rules, the by-law from May 27, 2005 relative to the definition of balancing areas, and the advice from May 27, 2005 relative to the tariffs of use of natural gas transportation networks. In application of article 7 of the law from January 3, 2003, the implementation of the first tariffs of use of natural gas transportation networks and of liquefied natural gas (LNG) facilities is defined in the decree no. 2004-994 from September 21, 2004. On the main transportation network, the tariffing is of 'input-output' type and does not depend on the distance, while at the regional network scale, the tariffing is linked with the distance. The tariff of use of LNG facilities is the sum of 4 terms: a fixed term applied to each batch unloaded at the methane terminal, a term proportional to the unloaded LNG quantities, a term depending on the duration of use of LNG storage facilities and a term covering the gas consumptions of LNG facilities. This document gathers these different legislative texts with their appendixes. (J.S.)

An improved algorithm for finding all minimal paths in a network

International Nuclear Information System (INIS)

Bai, Guanghan; Tian, Zhigang; Zuo, Ming J.

2016-01-01

Minimal paths (MPs) play an important role in network reliability evaluation. In this paper, we report an efficient recursive algorithm for finding all MPs in two-terminal networks, which consist of a source node and a sink node. A linked path structure indexed by nodes is introduced, which accepts both directed and undirected form of networks. The distance between each node and the sink node is defined, and a simple recursive algorithm is presented for labeling the distance for each node. Based on the distance between each node and the sink node, additional conditions for backtracking are incorporated to reduce the number of search branches. With the newly introduced linked node structure, the distances between each node and the sink node, and the additional backtracking conditions, an improved backtracking algorithm for searching for all MPs is developed. In addition, the proposed algorithm can be adapted to search for all minimal paths for each source–sink pair in networks consisting of multiple source nodes and/or multiple sink nodes. Through computational experiments, it is demonstrated that the proposed algorithm is more efficient than existing algorithms when the network size is not too small. The proposed algorithm becomes more advantageous as the size of the network grows. - Highlights: • A linked path structure indexed by nodes is introduced to represent networks. • Additional conditions for backtracking are proposed based on the distance of each node. • An efficient algorithm is developed to find all MPs for two-terminal networks. • The computational efficiency of the algorithm for two-terminal networks is investigated. • The computational efficiency of the algorithm for multi-terminal networks is investigated.

Input-output supervisor

International Nuclear Information System (INIS)

Dupuy, R.

1970-01-01

The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr

Evolution of the insect terminal patterning system--insights from the milkweed bug, Oncopeltus fasciatus.

Science.gov (United States)

Weisbrod, Anat; Cohen, Mira; Chipman, Ariel D

2013-08-01

The anterior and posterior ends of the insect embryo are patterned through the terminal patterning system, which is best known from the fruitfly Drosophila melanogaster. In Drosophila, the RTK receptor Torso and its presumed co-activator Torso-like initiate a signaling cascade, which activates two terminal gap genes, tailless and huckebein. These in turn interact with various patterning genes to define terminal structures. Work on other insect species has shown that this system is poorly conserved, and not all of its components have been found in all cases studied. We place the variability of the system within a broader phylogenetic framework. We describe the expression and knock-down phenotypes of the homologues of terminal patterning genes in the hemimetabolous Oncopeltus fasciatus. We have examined the interactions among these genes and between them and other patterning genes. We demonstrate that all of these genes have different roles in Oncopeltus relative to Drosophila; torso-like is expressed in follicle cells during oogenesis and is involved in the invagination of the blastoderm to form the germ band, and possibly also in defining the growth zone; tailless is regulated by orthodenticle and has a role only in anterior determination; huckebein is expressed only in the middle of the blastoderm; finally, torso was not found in Oncopeltus and its role in terminal patterning seems novel within holometabolous insects. We then use our data, together with published data on other insects, to reconstruct the evolution of the terminal patterning gene network in insects. We suggest that the Drosophila terminal patterning network evolved recently in the lineage leading to the Diptera, and represents an example of evolutionary "tinkering", where pre-existing pathways are co-opted for a new function. Copyright © 2013 Elsevier Inc. All rights reserved.

DESIGNING OF AN AUTOMOBILE FLEET NETWORK

Directory of Open Access Journals (Sweden)

R. B. Ivut

2016-01-01

Full Text Available Investment volume is considered as an important factor in regional development under current conditions. Logistical infrastructure which ensures a complex transport, distributive, information and other services exerts a significant influence on regional investment attractiveness. Lack of clear vision on development and execution of development strategy for logistics infrastructure from the side of regional authorities results in unwillingness of large federal and transnational companies to provide investments in infrastructure projects. Network of automotive transport terminals is one of the main elements in logistics infrastructure. The network allows to optimize a flow of material goods from the point of their origin to the point of their consumption with the lowest possible costs and the required level of service. Automobile transport is one of the main objects of transport infrastructure and it is characterized by rather high flexibility in comparison with other types of transport facilities that preconditions its widespread application. Network of automobile fleets (terminals has been formed for redistribution of goods traffic within the concerned regions. The purpose of the present research is to develop a mathematical model for formation of transport infrastructure on the territory of regions. The paper proposes an approach for formation of automobile fleet (terminal network on the territory of a large region with due account of the established network of distribution and sorting-out warehouse facilities. A model has been developed for solving the problem pertaining to minimization of aggregate costs related to maintenance of automobile fleets, delivery of goods to and from distribution and sorting-out warehouse facilities to consumers, ferry of empty trucks and goods handling. The model makes it possible to determine optimal number and location area of automobile fleets (terminals while accounting for their possible locations, capacity

Estimation of international output-energy relation. Effects of alternative output measures

International Nuclear Information System (INIS)

Shrestha, R.M.

2000-01-01

This paper analyzes the output-energy relationship with alternative measures of output and energy. Our analysis rejects the hypothesis of non-diminishing returns to energy consumption when GDP at purchasing power parities is used as the output measure unlike the case with GNP at market exchange rates. This finding also holds when energy input includes the usage of both commercial and traditional fuels. 13 refs

Coherent network detection of gravitational waves: the redundancy veto

International Nuclear Information System (INIS)

Wen Linqing; Schutz, Bernard F

2005-01-01

A network of gravitational wave detectors is called redundant if, given the direction to a source, the strain induced by a gravitational wave in one or more of the detectors can be fully expressed in terms of the strain induced in others in the network. Because gravitational waves have only two polarizations, any network of three or more differently oriented interferometers with similar observing bands is redundant. The three-armed LISA space interferometer has three outputs that are redundant at low frequencies. The two aligned LIGO interferometers at Hanford WA are redundant, and the LIGO detector at Livingston LA is nearly redundant with either of the Hanford detectors. Redundant networks have a powerful veto against spurious noise, a linear combination of the detector outputs that contains no gravitational wave signal. For LISA, this 'null' output is known as the Sagnac mode, and its use in discriminating between detector noise and a cosmological gravitational wave background is well understood. But the usefulness of the null veto for ground-based detector networks has been ignored until now. We show that it should make it possible to discriminate in a model-independent way between real gravitational waves and accidentally coincident non-Gaussian noise 'events' in redundant networks of two or more broadband detectors. It has been shown that with three detectors, the null output can even be used to locate the direction to the source, and then two other linear combinations of detector outputs give the optimal 'coherent' reconstruction of the two polarization components of the signal. We discuss briefly the implementation of such a detection strategy in realistic networks, where signals are weak, detector calibration is a significant uncertainty, and the various detectors may have different (but overlapping) observing bands

A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

Science.gov (United States)

Zhang, Liujie; Zhou, Yanquan; Duan, Xiuyu; Chen, Ruiqi

2018-03-01

Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing. In this paper, we propose a hierarchical multi-input and output model based bi-directional recurrent neural network, which both considers the semantic and lexical information of emotional expression. Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation. Then the lexical information is considered via attention over output of softmax activation on part of speech representation. In addition, we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels. The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.

Apprenticeship effect on a neural network

International Nuclear Information System (INIS)

Haddad, F.; Hagel, K.; Li, J.; Mdeiwayeh, N.; Natowitz, J.B.; Wada, R.; Xiao, B.; David, C.; Freslier, M.; Aichelin, J.

1997-01-01

Utilization of a neural network for determining the value of the impact parameter in heavy ion reactions is a two stage process: a apprenticeship stage followed by a utilization stage. During the first stage one determines the network parameters by means of a trial game for which the inputs and outputs are known. To realize the trial game a numerical simulation code was used. In order to estimate the biases of this procedure we generated trial games by resorting to two different models: a transport dynamical model (QMD) coupled to a deexcitation code (GEMINI) and a event generator based on a statistical approach (EUGENE). The procedure was applied to determine the impact parameter in 40 Ca + 40 Ca reactions. The effect of the model dependence of the apprenticeship procedure is studied thoroughly. In the two cases the outputs provided by the network are smaller then 7 fm which can be expected in case of complete events. The network trained with QMD gives outputs for input parameters within a larger range of values which is due to the fact that EUGENE does not contain 'Deep Inelastic'

Local Dynamics in Trained Recurrent Neural Networks.

Science.gov (United States)

Rivkind, Alexander; Barak, Omri

2017-06-23

Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

Local Dynamics in Trained Recurrent Neural Networks

Science.gov (United States)

Rivkind, Alexander; Barak, Omri

2017-06-01

Learning a task induces connectivity changes in neural circuits, thereby changing their dynamics. To elucidate task-related neural dynamics, we study trained recurrent neural networks. We develop a mean field theory for reservoir computing networks trained to have multiple fixed point attractors. Our main result is that the dynamics of the network's output in the vicinity of attractors is governed by a low-order linear ordinary differential equation. The stability of the resulting equation can be assessed, predicting training success or failure. As a consequence, networks of rectified linear units and of sigmoidal nonlinearities are shown to have diametrically different properties when it comes to learning attractors. Furthermore, a characteristic time constant, which remains finite at the edge of chaos, offers an explanation of the network's output robustness in the presence of variability of the internal neural dynamics. Finally, the proposed theory predicts state-dependent frequency selectivity in the network response.

Connecting Land-Based Networks to Ships

Science.gov (United States)

2013-06-01

multipoint wireless broadband systems, and WiMAX networks were initially deployed for fixed and nomadic (portable) applications. These standards...CAPABILITIES OF SHIP-TO-SHORE COMMUNICATIONS A. US Navy Automated Digital Network System (ADNS) The U.S. Navy’s Automated Digital Network System (ADNS...submit digitally any necessary documents to the terminal operators, contact their logistics providers, access tidal information and receive

Network Neutrality : A Survey of the Economic Literature

NARCIS (Netherlands)

Schuett, F.

2010-01-01

This paper reviews the small but growing economic literature on network neutrality. It considers a number of possible departures from network neutrality, in particular termination fees, second-degree price discrimination, and vertical foreclosure.

Super capacitor modeling with artificial neural network (ANN)

Energy Technology Data Exchange (ETDEWEB)

Marie-Francoise, J.N.; Gualous, H.; Berthon, A. [Universite de Franche-Comte, Lab. en Electronique, Electrotechnique et Systemes (L2ES), UTBM, INRETS (LRE T31) 90 - Belfort (France)

2004-07-01

This paper presents super-capacitors modeling using Artificial Neural Network (ANN). The principle consists on a black box nonlinear multiple inputs single output (MISO) model. The system inputs are temperature and current, the output is the super-capacitor voltage. The learning and the validation of the ANN model from experimental charge and discharge of super-capacitor establish the relationship between inputs and output. The learning and the validation of the ANN model use experimental results of 2700 F, 3700 F and a super-capacitor pack. Once the network is trained, the ANN model can predict the super-capacitor behaviour with temperature variations. The update parameters of the ANN model are performed thanks to Levenberg-Marquardt method in order to minimize the error between the output of the system and the predicted output. The obtained results with the ANN model of super-capacitor and experimental ones are in good agreement. (authors)

Estimation of continuous multi-DOF finger joint kinematics from surface EMG using a multi-output Gaussian Process.

Science.gov (United States)

Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro

2014-01-01

Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.

Analysis of neural networks through base functions

NARCIS (Netherlands)

van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

Improving the Robustness of Deep Neural Networks via Stability Training

OpenAIRE

Zheng, Stephan; Song, Yang; Leung, Thomas; Goodfellow, Ian

2016-01-01

In this paper we address the issue of output instability of deep neural networks: small perturbations in the visual input can significantly distort the feature embeddings and output of a neural network. Such instability affects many deep architectures with state-of-the-art performance on a wide range of computer vision tasks. We present a general stability training method to stabilize deep networks against small input distortions that result from various types of common image processing, such...

Nonlinear transfer function encodes synchronization in a neural network from the mammalian brain.

Science.gov (United States)

Menendez de la Prida, L; Sanchez-Andres, J V

1999-09-01

Synchronization is one of the mechanisms by which the brain encodes information. The observed synchronization of neuronal activity has, however, several levels of fluctuations, which presumably regulate local features of specific areas. This means that biological neural networks should have an intrinsic mechanism able to synchronize the neuronal activity but also to preserve the firing capability of individual cells. Here, we investigate the input-output relationship of a biological neural network from developing mammalian brain, i.e., the hippocampus. We show that the probability of occurrence of synchronous output activity (which consists in stereotyped population bursts recorded throughout the hippocampus) is encoded by a sigmoidal transfer function of the input frequency. Under this scope, low-frequency inputs will not produce any coherent output while high-frequency inputs will determine a synchronous pattern of output activity (population bursts). We analyze the effect of the network size (N) on the parameters of the transfer function (threshold and slope). We found that sigmoidal functions realistically simulate the synchronous output activity of hippocampal neural networks. This outcome is particularly important in the application of results from neural network models to neurobiology.

Distributed Extreme Learning Machine for Nonlinear Learning over Network

Directory of Open Access Journals (Sweden)

Songyan Huang

2015-02-01

Full Text Available Distributed data collection and analysis over a network are ubiquitous, especially over a wireless sensor network (WSN. To our knowledge, the data model used in most of the distributed algorithms is linear. However, in real applications, the linearity of systems is not always guaranteed. In nonlinear cases, the single hidden layer feedforward neural network (SLFN with radial basis function (RBF hidden neurons has the ability to approximate any continuous functions and, thus, may be used as the nonlinear learning system. However, confined by the communication cost, using the distributed version of the conventional algorithms to train the neural network directly is usually prohibited. Fortunately, based on the theorems provided in the extreme learning machine (ELM literature, we only need to compute the output weights of the SLFN. Computing the output weights itself is a linear learning problem, although the input-output mapping of the overall SLFN is still nonlinear. Using the distributed algorithmto cooperatively compute the output weights of the SLFN, we obtain a distributed extreme learning machine (dELM for nonlinear learning in this paper. This dELM is applied to the regression problem and classification problem to demonstrate its effectiveness and advantages.

Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

Directory of Open Access Journals (Sweden)

Rong Mei

2017-01-01

Full Text Available This paper presents an adaptive neural output feedback control scheme for uncertain robot manipulators with input saturation using the radial basis function neural network (RBFNN and disturbance observer. First, the RBFNN is used to approximate the system uncertainty, and the unknown approximation error of the RBFNN and the time-varying unknown external disturbance of robot manipulators are integrated as a compounded disturbance. Then, the state observer and the disturbance observer are proposed to estimate the unmeasured system state and the unknown compounded disturbance based on RBFNN. At the same time, the adaptation technique is employed to tackle the control input saturation problem. Utilizing the estimate outputs of the RBFNN, the state observer, and the disturbance observer, the adaptive neural output feedback control scheme is developed for robot manipulators using the backstepping technique. The convergence of all closed-loop signals is rigorously proved via Lyapunov analysis and the asymptotically convergent tracking error is obtained under the integrated effect of the system uncertainty, the unmeasured system state, the unknown external disturbance, and the input saturation. Finally, numerical simulation results are presented to illustrate the effectiveness of the proposed adaptive neural output feedback control scheme for uncertain robot manipulators.

Output hardcopy devices

CERN Document Server

Durbeck, Robert

1988-01-01

Output Hardcopy Devices provides a technical summary of computer output hardcopy devices such as plotters, computer output printers, and CRT generated hardcopy. Important related technical areas such as papers, ribbons and inks, color techniques, controllers, and character fonts are also covered. Emphasis is on techniques primarily associated with printing, as well as the plotting capabilities of printing devices that can be effectively used for computer graphics in addition to their various printing functions. Comprised of 19 chapters, this volume begins with an introduction to vector and ras

Neural node network and model, and method of teaching same

Science.gov (United States)

Parlos, Alexander G. (Inventor); Atiya, Amir F. (Inventor); Fernandez, Benito (Inventor); Tsai, Wei K. (Inventor); Chong, Kil T. (Inventor)

1995-01-01

The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk. Subsequent to the gradient propagation, the weights can be normalized, thereby preventing convergence to a local optimum. Education of the network can be incremental both on and off-line. An educated network is suitable for modeling and controlling dynamic nonlinear systems and time series systems and predicting the outputs as well as hidden states and parameters. The educated network can also be further educated during on-line processing.

A framework for visualization of battlefield network behavior

Science.gov (United States)

Perzov, Yury; Yurcik, William

2006-05-01

An extensible network simulation application was developed to study wireless battlefield communications. The application monitors node mobility and depicts broadcast and unicast traffic as expanding rings and directed links. The network simulation was specially designed to support fault injection to show the impact of air strikes on disabling nodes. The application takes standard ns-2 trace files as an input and provides for performance data output in different graphical forms (histograms and x/y plots). Network visualization via animation of simulation output can be saved in AVI format that may serve as a basis for a real-time battlefield awareness system.

Landslide Susceptibility Index Determination Using Aritificial Neural Network

Science.gov (United States)

Kawabata, D.; Bandibas, J.; Urai, M.

2004-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic features, rock types and geologic structure are especially important base factors of the landslide occurrence. Generating landslide susceptibility index by defining the relationship between landslide occurrence and that base factors using conventional mathematical and statistical methods is very difficult and inaccurate. This study focuses on generating landslide susceptibility index using artificial neural networks in Southern Japanese Alps. The training data are geomorphic (e.g. altitude, slope and aspect) and geologic parameters (e.g. rock type, distance from geologic boundary and geologic dip-strike angle) and landslides. Artificial neural network structure and training scheme are formulated to generate the index. Data from areas with and without landslide occurrences are used to train the network. The network is trained to output 1 when the input data are from areas with landslides and 0 when no landslide occurred. The trained network generates an output ranging from 0 to 1 reflecting the possibility of landslide occurrence based on the inputted data. Output values nearer to 1 means higher possibility of landslide occurrence. The artificial neural network model is incorporated into the GIS software to generate a landslide susceptibility map.

From Static Output Feedback to Structured Robust Static Output Feedback: A Survey

OpenAIRE

Sadabadi , Mahdieh ,; Peaucelle , Dimitri

2016-01-01

This paper reviews the vast literature on static output feedback design for linear time-invariant systems including classical results and recent developments. In particular, we focus on static output feedback synthesis with performance specifications, structured static output feedback, and robustness. The paper provides a comprehensive review on existing design approaches including iterative linear matrix inequalities heuristics, linear matrix inequalities with rank constraints, methods with ...

Development of Data Envelopment Analysis for the Performance Evaluation of Green Supply Chain with Undesirable Outputs

Directory of Open Access Journals (Sweden)

Alireza Alinezhad

2016-08-01

Full Text Available A fundamental problem is the use of DEA in multistep or multilevel processes such as supply chain, lack of attention to processes’ internal communications in a way that the recent studies on DEA in the context of serial processes have focused on closed systems that the outputs of one level become the inputs of the next level and none of the inputs enter the mediator process. The present study aimed to examine the general dimensions of an open multilevel process. Here, some of the data such as inputs and outputs are supposed to leave the system while other outputs turn into the inputs of the next level. The new inputs can enter the next level as well. We expand this mode for network structures. The overall performance of such a structure is considered as a weighted average of sectors’ performance or distinct steps. Therefore, this suggested model in this study, not only provides the possibility to evaluate the performance of the entire network, but creates the performance analysis for each of the sub-processes. On the other hand, considering the data with undesirable structure leads to more correct performance estimation. In the real world, all productive processes do not comprise desirable factors. Therefore, presenting a structure that is capable of taking into account the undesirable structure is of crucial importance. In this study, a new model in the DEA by network structure is offered that can analyze the performance considering undesirable factors.

Research on optical access network remote management technology

Science.gov (United States)

Wang, Wayne; Zou, Chen; Luo, Wenyi

2008-11-01

This paper goal is to provide a framework for the remote configuration and management of services for PON (Passive Optical Network) access and fiber access. Also it defines how Auto-Configuration Servers (ACS) in the network can remotely configure, troubleshoot and manage a Passive Optical Network (PON) optical network termination (ONT) with layer 3 capabilities using the CPE WAN management protocol, TR-069.

CERN's common Unix and X terminal environment

International Nuclear Information System (INIS)

Cass, Tony

1996-01-01

The Desktop Infrastructure Group of CERN's Computing and Networks Division has developed a Common Unix and X Terminal Environment to case the migration to Unix based Interactive Computing. The CUTE architecture relies on a distributed flesystem - currently Transarc's AFS - to enable essentially interchangeable client workstation to access both home directory and program files transparently. Additionally, we provide a suite of programs to configure workstations for CUTE and to ensure continued compatibility. This paper describes the different components and the development of the CUTE architecture. (author)

Traffic sharing algorithms for hybrid mobile networks

Science.gov (United States)

Arcand, S.; Murthy, K. M. S.; Hafez, R.

1995-01-01

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

Evolution of the Research Libraries Information Network.

Science.gov (United States)

Richards, David; Lerche, Carol

1989-01-01

Discusses current RLIN (Research Libraries Information Network) communications technology and motivations for change. Goals, topology, hardware, software, and protocol, terminal wiring, and deployment are considered. Sidebars provide a diagram of the current RLIN communications technology and describe the integrated RLIN network. (one reference)…

Remote Earth Terminals in the Health, Education, Telecommunications Network. Satellite Technology Demonstration, Technical Report No. 0423.

Science.gov (United States)

Braunstein, Jean; And Others

The major purpose of the Health, Education, Telecommunications experiment was to demonstrate the feasibility of distributing video materials to a large number of low-cost earth terminals located in rural areas. The receivers are of two types: one-way video receivers for the reception of video programs, and two-way voice/data terminals which permit…

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Science.gov (United States)

Al-Anzi, Bader; Arpp, Patrick; Gerges, Sherif; Ormerod, Christopher; Olsman, Noah; Zinn, Kai

2015-05-01

An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae). A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Body-insensitive Multi-Mode MIMO Terminal Antenna of Double-Ring Structure

DEFF Research Database (Denmark)

Zhao, Kun; Zhang, Shuai; Ishimiya, Katsunori

2015-01-01

of mobile terminals. With the multimode excitation, the MIMO cellular antenna can operate at 830-900 MHz, 1700-2200 MHz, and 2400-2700 MHz, for 2G, 3G, and LTE bands, respectively. The MIMO Wi-Fi antenna can cover two Wi-Fi bands from 2.4 to 2.5 GHz and from 5.2 to 5.8 GHz. The effect of a user's body......In this paper, we propose a novel multimode multi-input multi-output (MIMO) antenna system composed of a dual-element MIMO cellular antenna and dual-element MIMO Wi-Fi antenna for mobile terminal applications. The antenna system has a double-ring structure and can be integrated with the metal frame...... on the MIMO cellular antenna is investigated on CTIA standard phantoms and a real user. Since our antenna mainly operates in the loop mode, it has a much lower efficiency loss than conventional mobile antennas in both talking and data modes. Our theoretical analysis and experiments have shown that our design...

System convergence in transport models: algorithms efficiency and output uncertainty

DEFF Research Database (Denmark)

Rich, Jeppe; Nielsen, Otto Anker

2015-01-01

of this paper is to analyse convergence performance for the external loop and to illustrate how an improper linkage between the converging parts can lead to substantial uncertainty in the final output. Although this loop is crucial for the performance of large-scale transport models it has not been analysed...... much in the literature. The paper first investigates several variants of the Method of Successive Averages (MSA) by simulation experiments on a toy-network. It is found that the simulation experiments produce support for a weighted MSA approach. The weighted MSA approach is then analysed on large......-scale in the Danish National Transport Model (DNTM). It is revealed that system convergence requires that either demand or supply is without random noise but not both. In that case, if MSA is applied to the model output with random noise, it will converge effectively as the random effects are gradually dampened...

Possible factors determining the non-linearity in the VO2-power output relationship in humans: theoretical studies.

Science.gov (United States)

Korzeniewski, Bernard; Zoladz, Jerzy A

2003-08-01

At low power output exercise (below lactate threshold), the oxygen uptake increases linearly with power output, but at high power output exercise (above lactate threshold) some additional oxygen consumption causes a non-linearity in the overall VO(2) (oxygen uptake rate)-power output relationship. The functional significance of this phenomenon for human exercise tolerance is very important, but the mechanisms underlying it remain unknown. In the present work, a computer model of oxidative phosphorylation in intact skeletal muscle developed previously is used to examine the background of this relationship in different modes of exercise. Our simulations demonstrate that the non-linearity in the VO(2)-power output relationship and the difference in the magnitude of this non-linearity between incremental exercise mode and square-wave exercise mode (constant power output exercise) can be generated by introducing into the model some hypothetical factor F (group of associated factors) that accumulate(s) in time during exercise. The performed computer simulations, based on this assumption, give proper time courses of changes in VO(2) and [PCr] after an onset of work of different intensities, including the slow component in VO(2), well matching the experimental results. Moreover, if it is assumed that the exercise terminates because of fatigue when the amount/intensity of F exceed some threshold value, the model allows the generation of a proper shape of the well-known power-duration curve. This fact suggests that the phenomenon of the non-linearity of the VO(2)-power output relationship and the magnitude of this non-linearity in different modes of exercise is determined by some factor(s) responsible for muscle fatigue.

Performance Analysis of a Power Limited Spectrum Sharing System with TAS/MRC

KAUST Repository

Khan, Fahd Ahmed; Tourki, Kamel; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

2014-01-01

multiple antennas on the secondary network terminals and performing antenna selection. In this paper, the performance of a multiple-input multiple-output (MIMO) secondary link with transmit antenna selection (TAS) at the transmitter and maximum ratio

Gene Circuit Analysis of the Terminal Gap Gene huckebein

Science.gov (United States)

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-01-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network. PMID:19876378

GDP Growth, Potential Output, and Output Gaps in Mexico

OpenAIRE

Ebrima A Faal

2005-01-01

This paper analyzes the sources of Mexico's economic growth since the 1960s and compares various decompositions of historical growth into its trend and cyclical components. The role of the implied output gaps in the inflationary process is then assessed. Looking ahead, the paper presents medium-term paths for GDP based on alternative assumptions for productivity growth rates. The results indicate that the most important factor underlying the slowdown in output growth was a decline in trend to...

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

Directory of Open Access Journals (Sweden)

Sungyoung Lee

2011-12-01

Full Text Available 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.

Enhancement to the Tektronix PLOT-10 Terminal Control System for creation of graphics metafiles

International Nuclear Information System (INIS)

Gray, W.H.

1983-01-01

Many data handling and analysis codes at the Oak Ridge National Laboratory (ORNL) use the Tektronix PLOT-10 Terminal Control System to graphically display data upon Tektronix or Tektronix-emulating graphics devices. Prior to the development of the software libraries and postprocessors discussed within this report, ORNL users were limited to the type of hardcopy output obtainable from the Tektronix PLOT-10 software library. Only Tektronix graphics devices are supported by the PLOT-10 library. The graphics library presented here eliminates this restriction by implementing a suite of software that optionally creates a graphics metafile within the user's disk area while simultaneously drawing a display image on the screen of a user's Tektronix terminal. This graphics metafile can then be postprocessed onto any of the graphics devices at ORNL via the ORNL PLOT command

Probabilistic Coexistence and Throughput of Cognitive Dual-Polarized Networks

Directory of Open Access Journals (Sweden)

J.-M. Dricot

2010-01-01

Full Text Available Diversity techniques for cognitive radio networks are important since they enable the primary and secondary terminals to efficiently share the spectral resources in the same location simultaneously. In this paper, we investigate a simple, yet powerful, diversity scheme by exploiting the polarimetric dimension. More precisely, we evaluate a scenario where the cognitive terminals use cross-polarized communications with respect to the primary users. Our approach is network-centric, that is, the performance of the proposed dual-polarized system is investigated in terms of link throughput in the primary and the secondary networks. In order to carry out this analysis, we impose a probabilistic coexistence constraint derived from an information-theoretic approach, that is, we enforce a guaranteed capacity for a primary terminal for a high fraction of time. Improvements brought about by the use of our scheme are demonstrated analytically and through simulations. In particular, the main simulation parameters are extracted from a measurement campaign dedicated to the characterization of indoor-to-indoor and outdoor-to-indoor polarization behaviors. Our results suggest that the polarimetric dimension represents a remarkable opportunity, yet easily implementable, in the context of cognitive radio networks.

Smooth function approximation using neural networks.

Science.gov (United States)

Ferrari, Silvia; Stengel, Robert F

2005-01-01

An algebraic approach for representing multidimensional nonlinear functions by feedforward neural networks is presented. In this paper, the approach is implemented for the approximation of smooth batch data containing the function's input, output, and possibly, gradient information. The training set is associated to the network adjustable parameters by nonlinear weight equations. The cascade structure of these equations reveals that they can be treated as sets of linear systems. Hence, the training process and the network approximation properties can be investigated via linear algebra. Four algorithms are developed to achieve exact or approximate matching of input-output and/or gradient-based training sets. Their application to the design of forward and feedback neurocontrollers shows that algebraic training is characterized by faster execution speeds and better generalization properties than contemporary optimization techniques.

Polarity-specific high-level information propagation in neural networks.

Science.gov (United States)

Lin, Yen-Nan; Chang, Po-Yen; Hsiao, Pao-Yueh; Lo, Chung-Chuan

2014-01-01

Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neural networks: the somatic nervous system of Caenorhabditis elegans (C. elegans) and the partial central complex network of Drosophila, in light of these properties. Specifically, we quantified high-level propagation in the vertical and horizontal directions: the former characterizes how signals propagate from specific input nodes to specific output nodes and the latter characterizes how a signal from a specific input node is shared by all output nodes. We found that the two neural networks are characterized by very efficient vertical and horizontal propagation. In comparison, classic small-world networks show a trade-off between vertical and horizontal propagation; increasing the rewiring probability improves the efficiency of horizontal propagation but worsens the efficiency of vertical propagation. Our result provides insights into how the complex functions of natural neural networks may arise from a design that allows them to efficiently transform and combine input signals.

Mobility management for SIP sessions in a heterogeneous network environment

NARCIS (Netherlands)

Romijn, Willem A.; Plas, Dirk-Jaap; Bijwaard, D.; Meeuwissen, Erik; van Ooijen, Gijs

2004-01-01

The next generation of communication networks is expected to create a heterogeneous network environment encompassing an ever-increasing number of different access networks and end-user terminals that will enable the introduction of and provide access to numerous feature-rich end-user services. It is

Harvesting full-duplex rate gains in cellular networks with half-duplex user terminals

KAUST Repository

Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim

2016-01-01

Full-Duplex (FD) transceivers may be expensive in terms of complexity, power consumption, and price to be implemented in all user terminals. Therefore, techniques to exploit in-band full-duplex communication with FD base stations (BSs) and half

Network resiliency through memory health monitoring and proactive management

Science.gov (United States)

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

Directory of Open Access Journals (Sweden)

Christopher E Hart

2006-12-01

Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

Osteogenic cell differentiation on H-terminated and O-terminated nanocrystalline diamond films

Directory of Open Access Journals (Sweden)

Liskova J

2015-01-01

Full Text Available Jana Liskova,1 Oleg Babchenko,2 Marian Varga,2 Alexander Kromka,2 Daniel Hadraba,1 Zdenek Svindrych,1 Zuzana Burdikova,1 Lucie Bacakova1 1Institute of Physiology, Academy of Sciences of the Czech Republic, Prague, Czech Republic; 2Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic Abstract: Nanocrystalline diamond (NCD films are promising materials for bone implant coatings because of their biocompatibility, chemical resistance, and mechanical hardness. Moreover, NCD wettability can be tailored by grafting specific atoms. The NCD films used in this study were grown on silicon substrates by microwave plasma-enhanced chemical vapor deposition and grafted by hydrogen atoms (H-termination or oxygen atoms (O-termination. Human osteoblast-like Saos-2 cells were used for biological studies on H-terminated and O-terminated NCD films. The adhesion, growth, and subsequent differentiation of the osteoblasts on NCD films were examined, and the extracellular matrix production and composition were quantified. The osteoblasts that had been cultivated on the O-terminated NCD films exhibited a higher growth rate than those grown on the H-terminated NCD films. The mature collagen fibers were detected in Saos-2 cells on both the H-terminated and O-terminated NCD films; however, the quantity of total collagen in the extracellular matrix was higher on the O-terminated NCD films, as were the amounts of calcium deposition and alkaline phosphatase activity. Nevertheless, the expression of genes for osteogenic markers – type I collagen, alkaline phosphatase, and osteocalcin – was either comparable on the H-terminated and O-terminated films or even lower on the O-terminated films. In conclusion, the higher wettability of the O-terminated NCD films is promising for adhesion and growth of osteoblasts. In addition, the O-terminated surface also seems to support the deposition of extracellular matrix proteins and extracellular matrix

Accuracy assessment of the scalar network analyzer using sliding termination techniques

DEFF Research Database (Denmark)

Knudsen, Bent; Engen, Glenn F.; Guldbrandsen, Birthe

1989-01-01

In the absence of phase response the major, if not the primary, sources of error in the scalar network analyzer are the imperfect directivity, etc., associated with its internal and frequently inaccessible test set or measurement network. An explicit expression is obtained for this error in terms...

Organizational Relationship Termination Competence

DEFF Research Database (Denmark)

Ritter, Thomas; Geersbro, Jens

2011-01-01

termination are found to significantly affect a firm's relationship termination competence. The findings suggest that managers should regard termination as a legitimate option in customer relationship management. In order to decrease the number of unwanted customers, managers must accept termination......Most firms are involved in a number of customer relationships that drain the firm's resources. However, many firms are hesitant to address this problem. This paper investigates customer relationship termination at the organizational level. We develop and analyze the organizational dimensions...... of organizational termination in order to improve our understanding of the management of termination. The impact of these termination dimensions on the percentage of unwanted customers is developed and tested using PLS on data gathered from a cross-sectional survey of more than 800 sales representatives. We find...

Development and aminergic neuromodulation of a spinal locomotor network controlling swimming in Xenopus larvae.

Science.gov (United States)

Sillar, K T; Reith, C A; McDearmid, J R

1998-11-16

In this article we review our research on the development and intrinsic neuromodulation of a spinal network controlling locomotion in a simple vertebrate. Swimming in hatchling Xenopus embryos is generated by a restricted network of well-characterized spinal neurons. This network produces a stereotyped motor pattern which, like real swimming, involves rhythmic activity that alternates across the body and progresses rostrocaudally with a brief delay between muscle segments. The stereotypy results from motoneurons discharging a single impulse in each cycle; because all motoneurons appear to behave similarly there is little scope for altering the output to the myotomes from one cycle to the next. Just one day later, however, Xenopus larvae generate a more complex and flexible motor pattern in which motoneurons can discharge a variable number of impulses which contribute to ventral root bursts in each cycle. This maturation of swimming is due, in part, to the influence of serotonin released from brain-stem raphespinal interneurons whose axonal projections innervate the cord early in larval life. Larval swimming is differentially modulated by both serotonin and by noradrenaline: serotonin leads to relatively fast, intense swimming whereas noradrenaline favors slower, weaker activity. Thus, these two biogenic amines select opposite extremes from the spectrum of possible output patterns that the swimming network can produce. Our studies on the cellular and synaptic effects of the amines indicate that they can control the strength of reciprocal glycinergic inhibition in the spinal cord. Serotonin and noradrenaline act presynaptically on the terminals of glycinergic commissural interneurons to weaken and strengthen, respectively, crossed glycinergic inhibition during swimming. As a result, serotonin reduces and noradrenaline increases interburst intervals. The membrane properties of spinal neurons are also affected by the amines. In particular, serotonin can induce

Kitimat LNG terminal

International Nuclear Information System (INIS)

Schmaltz, I.; Boulton, R.

2007-01-01

Kitimat Liquefied Natural Gas (LNG) terminal is a terminal development company owned by Galveston LNG, a privately owned Canadian energy development company. This presentation provided information on Kitimat LNG with particular reference to its terminal located in Bish Cove on the Douglas Channel in British Columbia. This LNG terminal is reported to be the only fully permitted regasification terminal on the west coast of Canada and the United States. The presentation addressed market fundamentals including several graphs, such as world natural gas proved reserves in 2006; LNG supplements to Canadian gas supplies; global LNG demand for 2005-2020; average annual United States LNG imports; and global LNG liquefaction projects. Other market fundamentals were described, including that Kitimat is the only other approved terminal aside from the Costa Azul terminal in Mexico; Kitimat is the only west coast LNG import terminal that connects to midwest and eastern North American markets through existing gas pipelines; LNG producers are looking for destination diversification; and markets and marketers are looking for supply diversification. The authors noted that by 2010, western Canadian gas demand will exceed Californian demand. Other topics that were discussed in the presentation included Canadian natural gas field receipts; unadjusted bitumen production outlook; oil sands gas demand; forward basis fundamentals; and the commercial drivers of the Kitimat LNG terminal. The presentation also discussed the pacific trail pipelines, a partnership between Galveston LNG and Pacific Northern Gas to develop the natural gas transmission line from Kitimat to Summit. The presentation concluded with a discussion of the benefits of Kitimat LNG terminal such as providing access to the largest natural gas markets in the world via major gas transmission lines with spare capacity. figs

Neutron spectrum unfolding using neural networks

International Nuclear Information System (INIS)

Vega C, H.R.; Hernandez D, V.M.; Manzanares A, E.

2004-01-01

An artificial neural network has been designed to obtain the neutron spectra from the Bonner spheres spectrometer's count rates. The neural network was trained using a large set of neutron spectra compiled by the International Atomic Energy Agency. These include spectra from iso- topic neutron sources, reference and operational neutron spectra obtained from accelerators and nuclear reactors. The spectra were transformed from lethargy to energy distribution and were re-binned to 31 energy groups using the MCNP 4C code. Re-binned spectra and UTA4 matrix were used to calculate the expected count rates in Bonner spheres spectrometer. These count rates were used as input and correspondent spectrum was used as output during neural network training. The network has 7 input nodes, 56 neurons as hidden layer and 31 neurons in the output layer. After training the network was tested with the Bonner spheres count rates produced by twelve neutron spectra. The network allows unfolding the neutron spectrum from count rates measured with Bonner spheres. Good results are obtained when testing count rates belong to neutron spectra used during training, acceptable results are obtained for count rates obtained from actual neutron fields; however the network fails when count rates belong to monoenergetic neutron sources. (Author)

Early-Transition Output Decline Revisited

Directory of Open Access Journals (Sweden)

Crt Kostevc

2016-05-01

Full Text Available In this paper we revisit the issue of aggregate output decline that took place in the early transition period. We propose an alternative explanation of output decline that is applicable to Central- and Eastern-European countries. In the first part of the paper we develop a simple dynamic general equilibrium model that builds on work by Gomulka and Lane (2001. In particular, we consider price liberalization, interpreted as elimination of distortionary taxation, as a trigger of the output decline. We show that price liberalization in interaction with heterogeneous adjustment costs and non-employment benefits lead to aggregate output decline and surge in wage inequality. While these patterns are consistent with actual dynamics in CEE countries, this model cannot generate output decline in all sectors. Instead sectors that were initially taxed even exhibit output growth. Thus, in the second part we consider an alternative general equilibrium model with only one production sector and two types of labor and distortion in a form of wage compression during the socialist era. The trigger for labor mobility and consequently output decline is wage liberalization. Assuming heterogeneity of workers in terms of adjustment costs and non-employment benefits can explain output decline in all industries.

Organization for the input and output of the environmental managment system in the Austrian network; Aufbau- und Ablauforganisation des Umweltmanagementsystems im Verbund

Energy Technology Data Exchange (ETDEWEB)

Neumann, G. [Oesterreichische Elektrizitaetswirtschaft-AG (Verbund), Vienna (Austria)

1998-12-01

The Austrian network has pledged itself in all areas of activity to a responsible, enduring relationship with the environment and, consequently, has introduced an environmental management system which embraces all undertakings. The input and output organization is described in relation to the new companies` structure. The establishment of an environmental information system, as well as documentation (required by EMAS) and communications with the public in the form of an annual environmental report may be cited as some of the concrete results. (orig.) [Deutsch] Der oesterreichische Verbund hat sich in allen Taetigkeitsbereichen zu einem verantwortungsvollen, an Nachhaltigkeit orientierten Umgang mit der Umwelt verpflichtet und daher ein - das gesamte Unternehmen umfassendes - Umweltmanagementsystem eingefuehrt. Beschrieben wird die Aufbau- und Ablauforganisation in Verbindung mit der neuen Firmenstruktur. Als konkrete Ergebnisse seien der Aufbau eines Umweltinformationssystems sowie die (vom EMAS geforderte) Dokumentation und Kommunikation mit der Oeffentlichkeit in Form eines jaehrlichen Umweltberichtes erwaehnt. (orig.)

Experimental and computational analysis of a large protein network that controls fat storage reveals the design principles of a signaling network.

Directory of Open Access Journals (Sweden)

Bader Al-Anzi

2015-05-01

Full Text Available An approach combining genetic, proteomic, computational, and physiological analysis was used to define a protein network that regulates fat storage in budding yeast (Saccharomyces cerevisiae. A computational analysis of this network shows that it is not scale-free, and is best approximated by the Watts-Strogatz model, which generates "small-world" networks with high clustering and short path lengths. The network is also modular, containing energy level sensing proteins that connect to four output processes: autophagy, fatty acid synthesis, mRNA processing, and MAP kinase signaling. The importance of each protein to network function is dependent on its Katz centrality score, which is related both to the protein's position within a module and to the module's relationship to the network as a whole. The network is also divisible into subnetworks that span modular boundaries and regulate different aspects of fat metabolism. We used a combination of genetics and pharmacology to simultaneously block output from multiple network nodes. The phenotypic results of this blockage define patterns of communication among distant network nodes, and these patterns are consistent with the Watts-Strogatz model.

Using an Artificial Neural Network Approach for Supplier Evaluation Process and a Sectoral Application

Directory of Open Access Journals (Sweden)

A. Yeşim Yayla

2011-02-01

Full Text Available In this study, a-three layered feed-forward backpropagation Artificial Neural Network (ANN model is developed for the supplier firms in ceramic sector on the bases of user effectiveness for using concurrent engineering method. The developed model is also questioned for its usability in the supplier evaluation process. The network's independent variables of the developed model are considered as input variables of the network and dependent variables are used as output variables. The values of these variables are determined with factor analysis. For obtaining the date set to be used in the analysis, a questionnaire form with 34 questions explaining the network's input and output variables are prepared and sent out to 52 firms active in related sector. For obtaining more accurate results from the network, the questions having factor load below 0,6 are eliminated from the analysis. With the elimination of the questions from the analysis, the answers given for 22 questions explaining 8 input variables are used for the evaluation the network's inputs, the answers given for 3 questions explaining output variables are used for the evaluation the network's outputs. The data set of the network's are divided into four equal groups with k-fold method in order to get four different alternative network structures. As a conclusion, the forecasted firm scores giving the minimum error from the network test simulation and real firm scores are found to be very close to each other, thus, it is concluded that the developed artificial neural network model can be used effectively in the supplier evaluation process.

MODELS OF AIR TRAFFIC CONTROLLERS ERRORS PREVENTION IN TERMINAL CONTROL AREAS UNDER UNCERTAINTY CONDITIONS

Directory of Open Access Journals (Sweden)

Volodymyr Kharchenko

2017-03-01

Full Text Available Purpose: the aim of this study is to research applied models of air traffic controllers’ errors prevention in terminal control areas (TMA under uncertainty conditions. In this work the theoretical framework descripting safety events and errors of air traffic controllers connected with the operations in TMA is proposed. Methods: optimisation of terminal control area formal description based on the Threat and Error management model and the TMA network model of air traffic flows. Results: the human factors variables associated with safety events in work of air traffic controllers under uncertainty conditions were obtained. The Threat and Error management model application principles to air traffic controller operations and the TMA network model of air traffic flows were proposed. Discussion: Information processing context for preventing air traffic controller errors, examples of threats in work of air traffic controllers, which are relevant for TMA operations under uncertainty conditions.

Analysis of neural networks in terms of domain functions

NARCIS (Netherlands)

van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, Lambert

Despite their success-story, artificial neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more as a

Approximate solutions of dual fuzzy polynomials by feed-back neural networks

Directory of Open Access Journals (Sweden)

Ahmad Jafarian

2012-11-01

Full Text Available Recently, artificial neural networks (ANNs have been extensively studied and used in different areas such as pattern recognition, associative memory, combinatorial optimization, etc. In this paper, we investigate the ability of fuzzy neural networks to approximate solution of a dual fuzzy polynomial of the form $a_{1}x+ ...+a_{n}x^n =b_{1}x+ ...+b_{n}x^n+d,$ where $a_{j},b_{j},d epsilon E^1 (for j=1,...,n.$ Since the operation of fuzzy neural networks is based on Zadeh's extension principle. For this scope we train a fuzzified neural network by back-propagation-type learning algorithm which has five layer where connection weights are crisp numbers. This neural network can get a crisp input signal and then calculates its corresponding fuzzy output. Presented method can give a real approximate solution for given polynomial by using a cost function which is defined for the level sets of fuzzy output and target output. The simulation results are presented to demonstrate the efficiency and effectiveness of the proposed approach.

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models.

Directory of Open Access Journals (Sweden)

Ryan C Williamson

2016-12-01

Full Text Available Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction-shared dimensionality and percent shared variance-with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.

A performance analysis of DS-CDMA and SCPC VSAT networks

Science.gov (United States)

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.

Application of neural network technology to nuclear plant thermal efficiency improvement

International Nuclear Information System (INIS)

Doremus, Rick; Allen Ho, S.; Bailey, James V.; Roman, Harry

2004-01-01

Due to the tremendous cost of building new nuclear power plants, it has become increasingly attractive to increase the power output from the existing operating power plants. There are two options that may be available to accomplish this goal. One option is to uprate the plant through licensing modification for a comfortably achievable goal of 4% to 6%. However, the licensing efforts required are no small task, vary from plant to plant, and may take years to accomplish. Some nuclear power plants may not have this option because of design, environmental, political, or geographical limitations. A second option exists that is simpler and more immediate. It focuses on improving the plant operating conditions using adaptive software that could increase the total plant output by approximately one-half percent by adjusting certain key operating parameters. No design basis analyses, hardware modifications, or licensing changes are required. In fact, this technique can be used on a plant that has already obtained licensing modification to obtain an additional one-half percent on top of the 4% to 6% increase. Public Service Electric and Gas and ARD Corporation are jointly investigating the creation of a Plant Optimization System, called POSITIVE. POSITIVE is an adaptive software tool that enables a user to analyze current plant data to identify potential problem areas and to obtain recommendations for increasing the plant's electric output. POSITIVE uses a combination of expert systems and adaptive software to analyze the thermal performance of a nuclear power plant. Historical data, obtained while the plant was above 93% power, is used to train neural networks to determine the current electric output of the plant. Once sufficiently trained, new data can be processed through the neural network. The neural network first determines the electric output associated with the current data. If the actual power matches the power predicted by the network, the neural network can be used

Interacting neural networks

Science.gov (United States)

Metzler, R.; Kinzel, W.; Kanter, I.

2000-08-01

Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random.

Understanding the tariff. Access to the public power transportation network

International Nuclear Information System (INIS)

2002-01-01

Since the European directive of December 19, 1996 about the common rules of the European power market, the eligible companies can chose their power supplier anywhere in Europe. The manager of the French power transportation network (RTE) supplies a network access to these companies according to a tariff fixed by the decree no. 2002-1014 from July 19, 2002. The aim of this document is to explain this tariff: tariffing principles ('mail-stamp' principle, voltage domain, subscribed output power tariffs, input power tariffs), tariffing elements (access to the grid, elements of output tariffs (subscribed power, overload, emergency tariffs, modifications etc..)), invoicing modalities, output tariffs, definitions. (J.S.)

Enhanced performance CCD output amplifier

Science.gov (United States)

Dunham, Mark E.; Morley, David W.

1996-01-01

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Increasing cellular coverage within integrated terrestrial/satellite mobile networks

Science.gov (United States)

Castro, Jonathan P.

1995-01-01

When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

Clean sailing. LNG terminals. Maritime infrastructure for liquefied natural gas; Sauber auf See. LNG-Terminals. Maritime Infrastruktur fuer fluessiges Erdgas

Energy Technology Data Exchange (ETDEWEB)

Anon.

2013-09-01

Ports act as essential hubs in the global economy. But the rise in maritime traffic is taking a toll on the quality of air in ports and out at sea. From 2015 onwards, threshold governing harmful emissions are being tightened in a bid to clear the air. All of which is driving interest in more environmentally sound fuels. Liquefied natural gas (LNG) is the perfect fit, more than complying with the upcoming regulations. To enable its widespread adoption, Linde is working full steam ahead to create a network of LNG terminals in Europe. (orig.)

Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS

Directory of Open Access Journals (Sweden)

Christopher Bergmeir

2012-01-01

Full Text Available Neural networks are important standard machine learning procedures for classification and regression. We describe the R package RSNNS that provides a convenient interface to the popular Stuttgart Neural Network Simulator SNNS. The main features are (a encapsulation of the relevant SNNS parts in a C++ class, for sequential and parallel usage of different networks, (b accessibility of all of the SNNSalgorithmic functionality from R using a low-level interface, and (c a high-level interface for convenient, R-style usage of many standard neural network procedures. The package also includes functions for visualization and analysis of the models and the training procedures, as well as functions for data input/output from/to the original SNNSfile formats.

Control of 12-Cylinder Camless Engine with Neural Networks

OpenAIRE

Ashhab Moh’d Sami

2017-01-01

The 12-cyliner camless engine breathing process is modeled with artificial neural networks (ANN’s). The inputs to the net are the intake valve lift (IVL) and intake valve closing timing (IVC) whereas the output of the net is the cylinder air charge (CAC). The ANN is trained with data collected from an engine simulation model which is based on thermodynamics principles and calibrated against real engine data. A method for adapting single-output feed-forward neural networks is proposed and appl...

A new backpropagation learning algorithm for layered neural networks with nondifferentiable units.

Science.gov (United States)

Oohori, Takahumi; Naganuma, Hidenori; Watanabe, Kazuhisa

2007-05-01

We propose a digital version of the backpropagation algorithm (DBP) for three-layered neural networks with nondifferentiable binary units. This approach feeds teacher signals to both the middle and output layers, whereas with a simple perceptron, they are given only to the output layer. The additional teacher signals enable the DBP to update the coupling weights not only between the middle and output layers but also between the input and middle layers. A neural network based on DBP learning is fast and easy to implement in hardware. Simulation results for several linearly nonseparable problems such as XOR demonstrate that the DBP performs favorably when compared to the conventional approaches. Furthermore, in large-scale networks, simulation results indicate that the DBP provides high performance.

Drift chamber tracking with neural networks

International Nuclear Information System (INIS)

Lindsey, C.S.; Denby, B.; Haggerty, H.

1992-10-01

We discuss drift chamber tracking with a commercial log VLSI neural network chip. Voltages proportional to the drift times in a 4-layer drift chamber were presented to the Intel ETANN chip. The network was trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs were recorded and later compared off line to conventional track fits. Two types of network architectures were studied. Applications of neural network tracking to high energy physics detector triggers is discussed

An artificial neural network model for periodic trajectory generation

Science.gov (United States)

Shankar, S.; Gander, R. E.; Wood, H. C.

A neural network model based on biological systems was developed for potential robotic application. The model consists of three interconnected layers of artificial neurons or units: an input layer subdivided into state and plan units, an output layer, and a hidden layer between the two outer layers which serves to implement nonlinear mappings between the input and output activation vectors. Weighted connections are created between the three layers, and learning is effected by modifying these weights. Feedback connections between the output and the input state serve to make the network operate as a finite state machine. The activation vector of the plan units of the input layer emulates the supraspinal commands in biological central pattern generators in that different plan activation vectors correspond to different sequences or trajectories being recalled, even with different frequencies. Three trajectories were chosen for implementation, and learning was accomplished in 10,000 trials. The fault tolerant behavior, adaptiveness, and phase maintenance of the implemented network are discussed.

Particle identification using artificial neural networks at BESIII

International Nuclear Information System (INIS)

Qin Gang; Lv Junguang; Bian Jianming; Chinese Academy of Sciences, Beijing

2008-01-01

A multilayered perceptrons' neural network technique has been applied in the particle identification at BESIII. The networks are trained in each sub-detector level. The NN output of sub-detectors can be sent to a sequential network or be constructed as PDFs for a likelihood. Good muon-ID, electron-ID and hadron-ID are obtained from the networks by using the simulated Monte Carlo samples. (authors)

High-Speed Optical Wide-Area Data-Communication Network

Science.gov (United States)

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.

Governmentally amplified output volatility

Science.gov (United States)

Funashima, Yoshito

2016-11-01

Predominant government behavior is decomposed by frequency into several periodic components: updating cycles of infrastructure, Kuznets cycles, fiscal policy over business cycles, and election cycles. Little is known, however, about the theoretical impact of such cyclical behavior in public finance on output fluctuations. Based on a standard neoclassical growth model, this study intends to examine the frequency at which public investment cycles are relevant to output fluctuations. We find an inverted U-shaped relationship between output volatility and length of cycle in public investment. This implies that periodic behavior in public investment at a certain frequency range can cause aggravated output resonance. Moreover, we present an empirical analysis to test the theoretical implication, using the U.S. data in the period from 1968 to 2015. The empirical results suggest that such resonance phenomena change from low to high frequency.

BAKNET - Communication network for radiation monitoring devices

International Nuclear Information System (INIS)

Cohen, Y.; Wengrowicz, U.; Tirosh, D.; Barak, D.

1997-01-01

A system, based on a new concept of controlling and monitoring distributed radiation monitors, has been developed and approved at the NRCN. The system, named B AKNET Network , consists of a series of communication adapters connected to a main PC via an RS-485 communication network (see Fig. 1). The network's maximal length is 1200 meters and it enables connection of up to 128 adapters. The BAKNET adapters are designed to interface output signals of different types of stationary radiation monitors to a main PC. The BAKNET adapters' interface type includes: digital, analog, RS-232, and mixed output signals. This allows versatile interfacing of different stationary radiation monitors to the main computer. The connection to the main computer is via an RS-485 network, utilizing an identical communication protocol. The PC software, written in C ++ under MS-Windows, consists of two main programs. The first is the data collection program and the second is the Human Machine Interface (HMI). (authors)

Antenna analysis using neural networks

Science.gov (United States)

Smith, William T.

1992-01-01

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

Directory of Open Access Journals (Sweden)

Xiaohong Li

2018-03-01

Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

The Malaysian Intermodal Terminal System: The Implication on the Malaysian Maritime Cluster

Directory of Open Access Journals (Sweden)

Mohamad Rosni Othman

2016-06-01

Full Text Available The maritime sector in Malaysia is best known globally due to the Straits of Malacca and being a nation surrounded by sea. Malaysia also has a substantial maritime industry consisting of numerous shipyards, ports and terminal faculties, ship services and a plethora of other companies and institutions with maritime oriented activities and become essential components of the Malaysia's maritime clusters. Issues such as underutilised intermodal terminals, uneven proportions in the freight transport infrastructure and road and seaport congestions prevent Malaysian seaports from achieving their full potential in serving their respective hinterlands. The key factors to improve Malaysian dry port or intermodal terminals are transport network; container planning; competition; location and, externalities. The paper does not only present the critical challenges faced by Malaysian intermodal terminals especially dry ports and the implications for seaport competency but it also provides strategies to utilise the Malaysian freight multimodal system to amplify seaports
tm performance in serving their hinterlands. As such, this may warrant policy makers to devise a comprehensive national master plan for the maritime sector in order for Malaysia to further develop her maritime industry and economies.

Cooperative networking in a heterogeneous wireless medium

CERN Document Server

Ismail, Muhammad

2013-01-01

This brief focuses on radio resource allocation in a heterogeneous wireless medium. It presents radio resource allocation algorithms with decentralized implementation, which support both single-network and multi-homing services. The brief provides a set of cooperative networking algorithms, which rely on the concepts of short-term call traffic load prediction, network cooperation, convex optimization, and decomposition theory. In the proposed solutions, mobile terminals play an active role in the resource allocation operation, instead of their traditional role as passive service recipients in the networking environment.

Quantum networks: where should we be heading?

Science.gov (United States)

Sasaki, Masahide

2017-06-01

Quantum key distribution network has become a reality in practical environment. Quantum repeaters have been explored in various physical systems and their combinations. For practical use of them, these new paradigms must be combined with existing or emerging infrastructures of communication and security systems. In this article, we discussed how quantum network can be combined with modern cryptographic technologies in fibre network and with emerging mobile terminals in wireless network, creating new solutions for the future cryptographic and communication systems. Our discussions are summarised in a roadmap.

Advanced evacuation model managed through fuzzy logic during an accident in LNG terminal

Energy Technology Data Exchange (ETDEWEB)

Stankovicj, Goran; Petelin, Stojan [Faculty for Maritime Studies and Transport, University of Ljubljana, Portorozh (Sierra Leone); others, and

2014-07-01

Evacuation of people located inside the enclosed area of an LNG terminal is a complex problem, especially considering that accidents involving LNG are potentially very hazardous. In order to create an evacuation model managed through fuzzy logic, extensive influence must be generated from safety analyses. A very important moment in the optimal functioning of an evacuation model is the creation of a database which incorporates all input indicators. The output result is the creation of a safety evacuation route which is active at the moment of the accident. (Author)

A TLD dose algorithm using artificial neural networks

International Nuclear Information System (INIS)

Moscovitch, M.; Rotunda, J.E.; Tawil, R.A.; Rathbone, B.A.

1995-01-01

An artificial neural network was designed and used to develop a dose algorithm for a multi-element thermoluminescence dosimeter (TLD). The neural network architecture is based on the concept of functional links network (FLN). Neural network is an information processing method inspired by the biological nervous system. A dose algorithm based on neural networks is fundamentally different as compared to conventional algorithms, as it has the capability to learn from its own experience. The neural network algorithm is shown the expected dose values (output) associated with given responses of a multi-element dosimeter (input) many times. The algorithm, being trained that way, eventually is capable to produce its own unique solution to similar (but not exactly the same) dose calculation problems. For personal dosimetry, the output consists of the desired dose components: deep dose, shallow dose and eye dose. The input consists of the TL data obtained from the readout of a multi-element dosimeter. The neural network approach was applied to the Harshaw Type 8825 TLD, and was shown to significantly improve the performance of this dosimeter, well within the U.S. accreditation requirements for personnel dosimeters

A Novel Cache Invalidation Scheme for Mobile Networks

Institute of Scientific and Technical Information of China (English)

无

2006-01-01

In this paper, we propose a strategy of maintaining cache consistency in wireless mobile environments, which adds a validation server (VS) into the GPRS network, utilizes the location information of mobile terminal in SGSN located at GPRS backbone, just sends invalidation information to mobile terminal which is online in accordance with the cached data, and reduces the information amount in asynchronous transmission. This strategy enables mobile terminal to access cached data with very little computing amount, little delay and arbitrary disconnection intervals, and excels the synchronous IR and asynchronous state (AS) in the total performances.

Effects of social network on production output of maize farmers in ...

African Journals Online (AJOL)

Social is as a veritable factor for getting access to resources. Thus, the effect of social network on productivity of maize farmers in Kwara State, Nigeria was investigated. Primary data were collected from one hundred and fifty maize farmers using a multistage random sampling procedure. Data were analysed using ...

An Asynchronous Recurrent Network of Cellular Automaton-Based Neurons and Its Reproduction of Spiking Neural Network Activities.

Science.gov (United States)

Matsubara, Takashi; Torikai, Hiroyuki

2016-04-01

Modeling and implementation approaches for the reproduction of input-output relationships in biological nervous tissues contribute to the development of engineering and clinical applications. However, because of high nonlinearity, the traditional modeling and implementation approaches encounter difficulties in terms of generalization ability (i.e., performance when reproducing an unknown data set) and computational resources (i.e., computation time and circuit elements). To overcome these difficulties, asynchronous cellular automaton-based neuron (ACAN) models, which are described as special kinds of cellular automata that can be implemented as small asynchronous sequential logic circuits have been proposed. This paper presents a novel type of such ACAN and a theoretical analysis of its excitability. This paper also presents a novel network of such neurons, which can mimic input-output relationships of biological and nonlinear ordinary differential equation model neural networks. Numerical analyses confirm that the presented network has a higher generalization ability than other major modeling and implementation approaches. In addition, Field-Programmable Gate Array-implementations confirm that the presented network requires lower computational resources.

Protocol for multiple node network

Science.gov (United States)

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.

multi scale analysis of a function by neural networks elementary derivatives functions

International Nuclear Information System (INIS)

Chikhi, A.; Gougam, A.; Chafa, F.

2006-01-01

Recently, the wavelet network has been introduced as a special neural network supported by the wavelet theory . Such networks constitute a tool for function approximation problems as it has been already proved in reference . Our present work deals with this model, treating a multi scale analysis of a function. We have then used a linear expansion of a given function in wavelets, neglecting the usual translation parameters. We investigate two training operations. The first one consists on an optimization of the output synaptic layer, the second one, optimizing the output function with respect to scale parameters. We notice a temporary merging of the scale parameters leading to some interesting results : new elementary derivatives units emerge, representing a new elementary task, which is the derivative of the output task

Disorder generated by interacting neural networks: application to econophysics and cryptography

International Nuclear Information System (INIS)

Kinzel, Wolfgang; Kanter, Ido

2003-01-01

When neural networks are trained on their own output signals they generate disordered time series. In particular, when two neural networks are trained on their mutual output they can synchronize; they relax to a time-dependent state with identical synaptic weights. Two applications of this phenomenon are discussed for (a) econophysics and (b) cryptography. (a) When agents competing in a closed market (minority game) are using neural networks to make their decisions, the total system relaxes to a state of good performance. (b) Two partners communicating over a public channel can find a common secret key

Reconstructing the population activity of olfactory output neurons that innervate identifiable processing units

Directory of Open Access Journals (Sweden)

Shigehiro Namiki

2008-06-01

Full Text Available We investigated the functional organization of the moth antennal lobe (AL, the primary olfactory network, using in vivo electrophysiological recordings and anatomical identification. The moth AL contains about 60 processing units called glomeruli that are identifiable from one animal to another. We were able to monitor the output information of the AL by recording the activity of a population of output neurons, each of which innervated a single glomerulus. Using compiled intracellular recordings and staining data from different animals, we mapped the odor-evoked dynamics on a digital atlas of the AL and geometrically reconstructed the population activity. We examined the quantitative relationship between the similarity of olfactory responses and the anatomical distance between glomeruli. Globally, the olfactory response profile was independent of the anatomical distance, although some local features were present.

An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

Directory of Open Access Journals (Sweden)

Zhe Dong

2014-02-01

Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

Prediction of drug terminal half-life and terminal volume of distribution after intravenous dosing based on drug clearance, steady-state volume of distribution, and physiological parameters of the body.

Science.gov (United States)

Berezhkovskiy, Leonid M

2013-02-01

The steady state, V(ss), terminal volume of distribution, V(β), and the terminal half-life, t(1/2), are commonly obtained from the drug plasma concentration-time profile, C(p)(t), following intravenous dosing. Unlike V(ss) that can be calculated based on the physicochemical properties of drugs considering the equilibrium partitioning between plasma and organ tissues, t(1/2) and V(β) cannot be calculated that way because they depend on the rates of drug transfer between blood and tissues. Considering the physiological pharmacokinetic model pertinent to the terminal phase of drug elimination, a novel equation that calculates t(1/2) (and consequently V(β)) was derived. It turns out that V(ss), the total body clearance, Cl, equilibrium blood-plasma concentration ratio, r; and the physiological parameters of the body such as cardiac output, and blood and tissue volumes are sufficient for determination of terminal kinetics. Calculation of t(1/2) by the obtained equation appears to be in good agreement with the experimentally observed vales of this parameter in pharmacokinetic studies in rat, monkey, dog, and human. The equation for the determination of the pre-exponent of the terminal phase of C(p)(t) is also found. The obtained equation allows to predict t(1/2) in human assuming that V(ss) and Cl were either obtained by allometric scaling or, respectively, calculated in silico or based on in vitro drug stability measurements. For compounds that have high clearance, the derived equation may be applied to calculate r just using the routine data on Cl, V(ss), and t(1/2), rather than doing the in vitro assay to measure this parameter. Copyright © 2012 Wiley Periodicals, Inc.

Hidden neural networks

DEFF Research Database (Denmark)

Krogh, Anders Stærmose; Riis, Søren Kamaric

1999-01-01

A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

Science.gov (United States)

Ye, Qiang

2010-01-01

Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

Outputs of paired Gabor filters summed across the background frame of reference predict the direction of movement

Science.gov (United States)

Lawton, Teri B.

1989-01-01

A cortical neural network that computes the visibility of shifts in the direction of movement is proposed. The network computes: (1) the magnitude of the position difference between the test and background patterns, (2) localized contrast differences at different spatial scales analyzed by computing temporal gradients of the difference and sum of the outputs of paired even- and odd-symmetric bandpass filters convolved with the input pattern, and (3) using global processes that pool the output from paired even- and odd-symmetric simple and complex cells across the spatial extent of the background frame of reference the direction a test pattern moved relative to a textured background. Evidence that magnocellular pathways are used to discriminate the direction of movement is presented. Since magnocellular pathways are used to discriminate the direction of movement, this task is not affected by small pattern changes such as jitter, short presentations, blurring, and different background contrasts that result when the veiling illumination in a scene changes.

Music Signal Processing Using Vector Product Neural Networks

Science.gov (United States)

Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

2017-05-01

We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

CONTAINER TERMINALS IN EUROPE

Directory of Open Access Journals (Sweden)

Bart W. WIEGMANS

2001-01-01

Full Text Available This paper aims to address the linkage between logistics (in particular, the management of marketing channel flows and transport markets, while also the interaction between these two markets and intermodal container terminals is analysed. The marketing channel theory is used to describe all relevant actors and flows that run through marketing channels, starting with customer needs and ending with customer satisfaction. Porter's theory of competitive advantages is used to review competitive forces in both markets. Finally, a competitor analysis is performed for the logistics and transport market. These theories are applied so as to be able to determine the competitive position of intermodal container terminals with a view to the management of marketing channel flows and the physical transport of freight flows. Hence, the central question of this paper is: Which markets are served by intermodal container terminals and with whom are they competing? At present, neither the maritime container terminals nor the continental container terminals appear to have a significant influence in the logistics service market; they concentrate mainly on the physical movement of containers (transshipment. Furthermore, maritime container terminals and continental container terminals are not dominant players in the transport service market. Our conclusion is that continental terminals are predominantly competing with unimodal road transport, with neighbouring continental terminals and with barge transport companies.

Scalable Optical-Fiber Communication Networks

Science.gov (United States)

Chow, Edward T.; Peterson, John C.

1993-01-01

Scalable arbitrary fiber extension network (SAFEnet) is conceptual fiber-optic communication network passing digital signals among variety of computers and input/output devices at rates from 200 Mb/s to more than 100 Gb/s. Intended for use with very-high-speed computers and other data-processing and communication systems in which message-passing delays must be kept short. Inherent flexibility makes it possible to match performance of network to computers by optimizing configuration of interconnections. In addition, interconnections made redundant to provide tolerance to faults.

[Design and implementation of mobile terminal data acquisition for Chinese materia medica resources survey].

Science.gov (United States)

Qi, Yuan-Hua; Wang, Hui; Zhang, Xiao-Bo; Jin, Yan; Ge, Xiao-Guang; Jing, Zhi-Xian; Wang, Ling; Zhao, Yu-Ping; Guo, Lan-Ping; Huang, Lu-Qi

2017-11-01

In this paper, a data acquisition system based on mobile terminal combining GPS, offset correction, automatic speech recognition and database networking technology was designed implemented with the function of locating the latitude and elevation information fast, taking conveniently various types of Chinese herbal plant photos, photos, samples habitat photos and so on. The mobile system realizes automatic association with Chinese medicine source information, through the voice recognition function it records the information of plant characteristics and environmental characteristics, and record relevant plant specimen information. The data processing platform based on Chinese medicine resources survey data reporting client can effectively assists in indoor data processing, derives the mobile terminal data to computer terminal. The established data acquisition system provides strong technical support for the fourth national survey of the Chinese materia medica resources (CMMR). Copyright© by the Chinese Pharmaceutical Association.

CRYSNET manual. Informal report. [Hardware and software of crystallographic computing network

Energy Technology Data Exchange (ETDEWEB)

None,

1976-07-01

This manual describes the hardware and software which together make up the crystallographic computing network (CRYSNET). The manual is intended as a users' guide and also provides general information for persons without any experience with the system. CRYSNET is a network of intelligent remote graphics terminals that are used to communicate with the CDC Cyber 70/76 computing system at the Brookhaven National Laboratory (BNL) Central Scientific Computing Facility. Terminals are in active use by four research groups in the field of crystallography. A protein data bank has been established at BNL to store in machine-readable form atomic coordinates and other crystallographic data for macromolecules. The bank currently includes data for more than 20 proteins. This structural information can be accessed at BNL directly by the CRYSNET graphics terminals. More than two years of experience has been accumulated with CRYSNET. During this period, it has been demonstrated that the terminals, which provide access to a large, fast third-generation computer, plus stand-alone interactive graphics capability, are useful for computations in crystallography, and in a variety of other applications as well. The terminal hardware, the actual operations of the terminals, and the operations of the BNL Central Facility are described in some detail, and documentation of the terminal and central-site software is given. (RWR)

Adaptive model predictive process control using neural networks

Science.gov (United States)

Buescher, K.L.; Baum, C.C.; Jones, R.D.

1997-08-19

A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

Network Edge Intelligence for the Emerging Next-Generation Internet

Directory of Open Access Journals (Sweden)

Salekul Islam

2010-11-01

Full Text Available The success of the Content Delivery Networks (CDN in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP many opportunities to become directly involved in content and service delivery.

Input/output plugin architecture for MDSplus

International Nuclear Information System (INIS)

Stillerman, Joshua; Fredian, Thomas; Manduchi, Gabriele

2014-01-01

The first version of MDSplus was released in 1991 for VAX/VMS. Since that time the underlying file formats have remained constant. The software however has evolved, it was ported to unix, linux, Windows, and Macintosh. In 1997 a TCP based protocol, mdsip, was added to provide network access to MDSplus data. In 2011 a mechanism was added to allow protocol plugins to permit the use of other transport mechanisms such as ssh to access data users. This paper describes a similar design which permits the insertion of plugins to handle the reading and writing of MDSplus data at the data storage level. Tree paths become URIs which specify the protocol, host, and protocol specific information. The protocol is provided by a dynamically activated shared library that can provide any consistent subset of the data store access API, treeshr. The existing low level network protocol called mdsip, is activated by defining tree paths like “host::/directory”. Using the new plugin mechanism this is re-implemented as an instance of the general plugin that replaces the low level treeshr input/output routines. It is specified by using a path like “mdsip://host/directory”. This architecture will make it possible to adapt the MDSplus data organization and analysis tools to other underlying data storage. The first new application of this, after the existing network protocol is implemented, will be a plugin based on a key value store. Key value stores, can provide inexpensive scalable, redundant data storage. An example of this might be an Amazon G3 plugin which would let you specify a tree path such as “AG3://container” to access MDSplus data stored in the cloud

Input/output plugin architecture for MDSplus

Energy Technology Data Exchange (ETDEWEB)

Stillerman, Joshua, E-mail: jas@psfc.mit.edu [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Fredian, Thomas, E-mail: twf@psfc.mit.edu [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Manduchi, Gabriele, E-mail: gabriele.manduchi@igi.cnr.it [Consorzio RFX, Euratom-ENEA Association, Corso Stati Uniti 4, Padova 35127 (Italy)

2014-05-15

The first version of MDSplus was released in 1991 for VAX/VMS. Since that time the underlying file formats have remained constant. The software however has evolved, it was ported to unix, linux, Windows, and Macintosh. In 1997 a TCP based protocol, mdsip, was added to provide network access to MDSplus data. In 2011 a mechanism was added to allow protocol plugins to permit the use of other transport mechanisms such as ssh to access data users. This paper describes a similar design which permits the insertion of plugins to handle the reading and writing of MDSplus data at the data storage level. Tree paths become URIs which specify the protocol, host, and protocol specific information. The protocol is provided by a dynamically activated shared library that can provide any consistent subset of the data store access API, treeshr. The existing low level network protocol called mdsip, is activated by defining tree paths like “host::/directory”. Using the new plugin mechanism this is re-implemented as an instance of the general plugin that replaces the low level treeshr input/output routines. It is specified by using a path like “mdsip://host/directory”. This architecture will make it possible to adapt the MDSplus data organization and analysis tools to other underlying data storage. The first new application of this, after the existing network protocol is implemented, will be a plugin based on a key value store. Key value stores, can provide inexpensive scalable, redundant data storage. An example of this might be an Amazon G3 plugin which would let you specify a tree path such as “AG3://container” to access MDSplus data stored in the cloud.

Discovery of new molecular entities able to strongly interfere with Hsp90 C-terminal domain.

Science.gov (United States)

Terracciano, Stefania; Russo, Alessandra; Chini, Maria G; Vaccaro, Maria C; Potenza, Marianna; Vassallo, Antonio; Riccio, Raffaele; Bifulco, Giuseppe; Bruno, Ines

2018-01-26

Heat shock protein 90 (Hsp90) is an ATP dependent molecular chaperone deeply involved in the complex network of cellular signaling governing some key functions, such as cell proliferation and survival, invasion and angiogenesis. Over the past years the N-terminal protein domain has been fully investigated as attractive strategy against cancer, but despite the many efforts lavished in the field, none of the N-terminal binders (termed "classical inhibitors"), currently in clinical trials, have yet successfully reached the market, because of the detrimental heat shock response (HSR) that showed to induce; thus, recently, the selective inhibition of Hsp90 C-terminal domain has powerfully emerged as a more promising alternative strategy for anti-cancer therapy, not eliciting this cell rescue cascade. However, the structural complexity of the target protein and, mostly, the lack of a co-crystal structure of C-terminal domain-ligand, essential to drive the identification of new hits, represent the largest hurdles in the development of new selective C-terminal inhibitors. Continuing our investigations on the identification of new anticancer drug candidates, by using an orthogonal screening approach, here we describe two new potent C-terminal inhibitors able to induce cancer cell death and a considerable down-regulation of Hsp90 client oncoproteins, without triggering the undesired heat shock response.

Short term memory in echo state networks

OpenAIRE

Jaeger, H.

2001-01-01

The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

UNMANNED AIR VEHICLE STABILIZATION BASED ON NEURAL NETWORK REGULATOR

Directory of Open Access Journals (Sweden)

S. S. Andropov

2016-09-01

Full Text Available A problem of stabilizing for the multirotor unmanned aerial vehicle in an environment with external disturbances is researched. A classic proportional-integral-derivative controller is analyzed, its flaws are outlined: inability to respond to changing of external conditions and the need for manual adjustment of coefficients. The paper presents an adaptive adjustment method for coefficients of the proportional-integral-derivative controller based on neural networks. A neural network structure, its input and output data are described. Neural networks with three layers are used to create an adaptive stabilization system for the multirotor unmanned aerial vehicle. Training of the networks is done with the back propagation method. Each neural network produces regulator coefficients for each angle of stabilization as its output. A method for network training is explained. Several graphs of transition process on different stages of learning, including processes with external disturbances, are presented. It is shown that the system meets stabilization requirements with sufficient number of iterations. Described adjustment method for coefficients can be used in remote control of unmanned aerial vehicles, operating in the changing environment.

Energy and output dynamics in Bangladesh

International Nuclear Information System (INIS)

Paul, Biru Paksha; Uddin, Gazi Salah

2011-01-01

The relationship between energy consumption and output is still ambiguous in the existing literature. The economy of Bangladesh, having spectacular output growth and rising energy demand as well as energy efficiency in recent decades, can be an ideal case for examining energy-output dynamics. We find that while fluctuations in energy consumption do not affect output fluctuations, movements in output inversely affect movements in energy use. The results of Granger causality tests in this respect are consistent with those of innovative accounting that includes variance decompositions and impulse responses. Autoregressive distributed lag models also suggest a role of output in Bangladesh's energy use. Hence, the findings of this study have policy implications for other developing nations where measures for energy conservation and efficiency can be relevant in policymaking.

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

Science.gov (United States)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

Research and Mass Deployment of Non-cognitive Authentication Strategy Based on Campus Wireless Network

Directory of Open Access Journals (Sweden)

Huangfu Dapeng

2018-01-01

Full Text Available With the rapid development of Internet +, the dependence on wireless networks and wireless terminals are increasing. Campus wireless network has become the main network of teachers and students in campus on the internet. As there are uneven clients and a wide variety of intelligent terminals now. Simplified authentication and network security become the most urgent problem for wireless network. This paper used the Portal + Mac authentication method to realize the non-cognitive authentication of teachers and students on basis of the analysis of the advantages and disadvantages of mainstream authentication of campus wireless network, such as 802.1X authentication, Portal authentication, Mac authentication and DHCP authentication. Teachers and students only need portal certification at the first time, then surf the internet with non-perceived authentication at the second time and later. This method increases network security, and is better to meet the needs of teachers and students.

Active Center Control of Termination by RNA Polymerase III and tRNA Gene Transcription Levels In Vivo.

Directory of Open Access Journals (Sweden)

Keshab Rijal

2016-08-01

Full Text Available The ability of RNA polymerase (RNAP III to efficiently recycle from termination to reinitiation is critical for abundant tRNA production during cellular proliferation, development and cancer. Yet understanding of the unique termination mechanisms used by RNAP III is incomplete, as is its link to high transcription output. We used two tRNA-mediated suppression systems to screen for Rpc1 mutants with gain- and loss- of termination phenotypes in S. pombe. 122 point mutation mutants were mapped to a recently solved 3.9 Å structure of yeast RNAP III elongation complex (EC; they cluster in the active center bridge helix and trigger loop, as well as the pore and funnel, the latter of which indicate involvement of the RNA cleavage domain of the C11 subunit in termination. Purified RNAP III from a readthrough (RT mutant exhibits increased elongation rate. The data strongly support a kinetic coupling model in which elongation rate is inversely related to termination efficiency. The mutants exhibit good correlations of terminator RT in vitro and in vivo, and surprisingly, amounts of transcription in vivo. Because assessing in vivo transcription can be confounded by various parameters, we used a tRNA reporter with a processing defect and a strong terminator. By ruling out differences in RNA decay rates, the data indicate that mutants with the RT phenotype synthesize more RNA than wild type cells, and than can be accounted for by their increased elongation rate. Finally, increased activity by the mutants appears unrelated to the RNAP III repressor, Maf1. The results show that the mobile elements of the RNAP III active center, including C11, are key determinants of termination, and that some of the mutations activate RNAP III for overall transcription. Similar mutations in spontaneous cancer suggest this as an unforeseen mechanism of RNAP III activation in disease.

Transient Processes in Electric Power Supply System for Oil Terminal with Own Gas-Turbine Power Station

Directory of Open Access Journals (Sweden)

A. M. Hаshimov

2009-01-01

Full Text Available The paper contains results of the investigations concerning influence of symmetrical and non-symmetrical short circuits at main power network on electric power supply system of a huge oil terminal which is powered by own gas-turbine power station. Calculations have been made in accordance with the IEC and IEEЕ requirements. Estimations for voltage level and distribution of short circuit current in the electric power supply system of the Sangachal oil terminal being operated in parallel with the AzerEnerji grid are presented in the paper

Optimal design of cluster-based ad-hoc networks using probabilistic solution discovery

International Nuclear Information System (INIS)

Cook, Jason L.; Ramirez-Marquez, Jose Emmanuel

2009-01-01

The reliability of ad-hoc networks is gaining popularity in two areas: as a topic of academic interest and as a key performance parameter for defense systems employing this type of network. The ad-hoc network is dynamic and scalable and these descriptions are what attract its users. However, these descriptions are also synonymous for undefined and unpredictable when considering the impacts to the reliability of the system. The configuration of an ad-hoc network changes continuously and this fact implies that no single mathematical expression or graphical depiction can describe the system reliability-wise. Previous research has used mobility and stochastic models to address this challenge successfully. In this paper, the authors leverage the stochastic approach and build upon it a probabilistic solution discovery (PSD) algorithm to optimize the topology for a cluster-based mobile ad-hoc wireless network (MAWN). Specifically, the membership of nodes within the back-bone network or networks will be assigned in such as way as to maximize reliability subject to a constraint on cost. The constraint may also be considered as a non-monetary cost, such as weight, volume, power, or the like. When a cost is assigned to each component, a maximum cost threshold is assigned to the network, and the method is run; the result is an optimized allocation of the radios enabling back-bone network(s) to provide the most reliable network possible without exceeding the allowable cost. The method is intended for use directly as part of the architectural design process of a cluster-based MAWN to efficiently determine an optimal or near-optimal design solution. It is capable of optimizing the topology based upon all-terminal reliability (ATR), all-operating terminal reliability (AoTR), or two-terminal reliability (2TR)

VAX Professional Workstation goes graphic

International Nuclear Information System (INIS)

Downward, J.G.

1984-01-01

The VAX Professional Workstation (VPW) is a collection of programs and procedures designed to provide an integrated work-station environment for the staff at KMS Fusion's research laboratories. During the past year numerous capabilities have been added to VPW, including support for VT125/VT240/4014 graphic workstations, editing windows, and additional desk utilities. Graphics workstation support allows users to create, edit, and modify graph data files, enter the data via a graphic tablet, create simple plots with DATATRIEVE or DECgraph on ReGIS terminals, or elaborate plots with TEKGRAPH on ReGIS or Tektronix terminals. Users may assign display error bars to the data and interactively plot it in a variety of ways. Users also can create and display viewgraphs. Hard copy output for a large network of office terminals is obtained by multiplexing each terminal's video output into a recently developed video multiplexer front ending a single channel video hard copy unit

Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Kim LaeYoung

2009-01-01

Full Text Available Abstract Next generation wireless communications are expected to rely on integrated networks consisting of multiple wireless technologies. Heterogeneous networks based on Wireless Local Area Networks (WLANs and Wireless Wide Area Networks (WWANs can combine their respective advantages on coverage and data rates, offering a high Quality of Service (QoS to mobile users. In such environment, multi-interface terminals should seamlessly switch from one network to another in order to obtain improved performance or at least to maintain a continuous wireless connection. Therefore, network selection algorithm is important in providing better performance to the multi-interface terminals in the integrated networks. In this paper, we propose a cost-based vertical handover decision algorithm that triggers the Vertical Handover (VHO based on a cost function for WWAN/WLAN integrated networks. For the cost function, we focus on developing an analytical model of the expected cost of WLAN for the mobile users that enter the double-coverage area while having a connection in the WWAN. Our simulation results show that the proposed scheme achieves better performance in terms of power consumption and throughput than typical approach where WLANs are always preferred whenever the WLAN access is available.

Coordinated frequency control from offshore wind power plants connected to multi terminal DC system considering wind speed variation

DEFF Research Database (Denmark)

Sakamuri, Jayachandra N.; Altin, Müfit; Hansen, Anca Daniela

2017-01-01

A coordinated fast primary frequency control scheme from offshore wind power plants (OWPPs) integrated to a three terminal high voltage DC (HVDC) system is proposed in this study. The impact of wind speed variation on the OWPP active power output and thus on the AC grid frequency and DC grid...... the active power support from OWPP with a ramp rate limiter and (iii) An alternative method for the wind turbine overloading considering rotor speed. The effectiveness of the proposed control scheme is demonstrated on a wind power plant integrated into a three terminal HVDC system developed in DIg......SILIENT PowerFactory. The results show that the proposed coordinated frequency control method performs effectively at different wind speeds and minimises the secondary effects on frequency and DC voltage....

Self-tuning control of a nuclear reactor using a Gaussian function neural network

International Nuclear Information System (INIS)

Park, M.G.; Cho, N.Z.

1995-01-01

A self-tuning control method is described for a nuclear reactor system that requires only a set of input-output measurements. The use of an artificial neural network in nonlinear model-based adaptive control, both as a plant model and a controller, is investigated. A neural network called a Gaussian function network is used for one-step-ahead predictive control to track the desired plant output. The effectiveness of the controller is demonstrated by the application of the method to the power tracking control of the Korea Multipurpose Research Reactor

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems.

Science.gov (United States)

Sakhre, Vandana; Jain, Sanjeev; Sapkal, Vilas S; Agarwal, Dev P

2015-01-01

Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furnace Box-Jenkins time series data.

Fuzzy Counter Propagation Neural Network Control for a Class of Nonlinear Dynamical Systems

Directory of Open Access Journals (Sweden)

Vandana Sakhre

2015-01-01

Full Text Available Fuzzy Counter Propagation Neural Network (FCPN controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL. FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN and Back Propagation Network (BPN on the basis of Mean Absolute Error (MAE, Mean Square Error (MSE, Best Fit Rate (BFR, and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO and a single input and single output (SISO gas furnace Box-Jenkins time series data.

From cognitive networks to seizures: Stimulus evoked dynamics in a coupled cortical network

Science.gov (United States)

Lee, Jaejin; Ermentrout, Bard; Bodner, Mark

2013-12-01

Epilepsy is one of the most common neuropathologies worldwide. Seizures arising in epilepsy or in seizure disorders are characterized generally by uncontrolled spread of excitation and electrical activity to a limited region or even over the entire cortex. While it is generally accepted that abnormal excessive firing and synchronization of neuron populations lead to seizures, little is known about the precise mechanisms underlying human epileptic seizures, the mechanisms of transitions from normal to paroxysmal activity, or about how seizures spread. Further complication arises in that seizures do not occur with a single type of dynamics but as many different phenotypes and genotypes with a range of patterns, synchronous oscillations, and time courses. The concept of preventing, terminating, or modulating seizures and/or paroxysmal activity through stimulation of brain has also received considerable attention. The ability of such stimulation to prevent or modulate such pathological activity may depend on identifiable parameters. In this work, firing rate networks with inhibitory and excitatory populations were modeled. Network parameters were chosen to model normal working memory behaviors. Two different models of cognitive activity were developed. The first model consists of a single network corresponding to a local area of the brain. The second incorporates two networks connected through sparser recurrent excitatory connectivity with transmission delays ranging from approximately 3 ms within local populations to 15 ms between populations residing in different cortical areas. The effect of excitatory stimulation to activate working memory behavior through selective persistent activation of populations is examined in the models, and the conditions and transition mechanisms through which that selective activation breaks down producing spreading paroxysmal activity and seizure states are characterized. Specifically, we determine critical parameters and architectural

Neuroadaptive Fault-Tolerant Control of Nonlinear Systems Under Output Constraints and Actuation Faults.

Science.gov (United States)

Zhao, Kai; Song, Yongduan; Shen, Zhixi

2018-02-01

In this paper, a neuroadaptive fault-tolerant tracking control method is proposed for a class of time-delay pure-feedback systems in the presence of external disturbances and actuation faults. The proposed controller can achieve prescribed transient and steady-state performance, despite uncertain time delays and output constraints as well as actuation faults. By combining a tangent barrier Lyapunov-Krasovskii function with the dynamic surface control technique, the neural network unit in the developed control scheme is able to take its action from the very beginning and play its learning/approximating role safely during the entire system operational envelope, leading to enhanced control performance without the danger of violating compact set precondition. Furthermore, prescribed transient performance and output constraints are strictly ensured in the presence of nonaffine uncertainties, external disturbances, and undetectable actuation faults. The control strategy is also validated by numerical simulation.

Relay Precoder Optimization in MIMO-Relay Networks With Imperfect CSI

KAUST Repository

Pandarakkottilil, Ubaidulla; Chockalingam, A.

2011-01-01

In this paper, we consider robust joint designs of relay precoder and destination receive filters in a nonregenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a

Cardiac output measurement

Directory of Open Access Journals (Sweden)

Andreja Möller Petrun

2014-02-01

Full Text Available In recent years, developments in the measuring of cardiac output and other haemodynamic variables are focused on the so-called minimally invasive methods. The aim of these methods is to simplify the management of high-risk and haemodynamically unstable patients. Due to the need of invasive approach and the possibility of serious complications the use of pulmonary artery catheter has decreased. This article describes the methods for measuring cardiac output, which are based on volume measurement (Fick method, indicator dilution method, pulse wave analysis, Doppler effect, and electrical bioimpedance.

Facebook use during relationship termination: uncertainty reduction and surveillance.

Science.gov (United States)

Tong, Stephanie Tom

2013-11-01

Many studies document how individuals use Facebook to meet partners or develop and maintain relationships. Less is known about information-seeking behaviors during the stages of relationship termination. Relational dissolution is a socially embedded activity, and affordances of social network sites offer many advantages in reducing uncertainty after a breakup. A survey collected responses from 110 individuals who use Facebook to gather information about their romantic ex-partners. Results indicated that after breakup, partners may take advantage of the system's information visibility and the relative invisibility of movement depending on relational factors (initiator role and breakup uncertainty), social factors (perceived network approval of Facebook surveillance), and individual privacy concerns. This investigation addresses questions such as what type of information-seeking foci do individuals employ and how do individuals use Facebook as a form of surveillance? What factors motivate surveillance behavior?

Antecedents of Customer Relationship Termination

DEFF Research Database (Denmark)

Geersbro, Jens; Ritter, Thomas

To end business relationships, or to more actively terminate relationships, has long been acknowledged as part of customer relationship management. However, compared to other elements such as initiation and maintenance of relationships, little is known about the termination of business...... relationships as a managerial task. This paper contributes by (1) developing a conceptualization of relationship termination competence and (2) analyzing its antecedents. The empirical results identify termination acceptance, definition non-customers, organizational relationship termination routines......, and motivation as significant antecedents. Because of this, managers need to develop their organizations in order to use relationship termination as a vital strategy....

Multi-power-level Energy Saving Management for Passive Optical Networks

OpenAIRE

Taheri, Mina; Ansari, Nirwan

2014-01-01

Environmental concerns have motivated network designers to further reduce energy consumption of access networks. This paper focuses on reducing energy consumption of Ethernet passive optical network (EPON) as one of the most efficient transmission technologies for broadband access. In EPON, the downstream traffic is sent from the optical line terminal (OLT) located at the central office to all optical network units (ONUs). Each ONU checks all arrival downstream packets and selects the downstr...

Probabilistic Output Analysis by Program Manipulation

DEFF Research Database (Denmark)

Rosendahl, Mads; Kirkeby, Maja Hanne

2015-01-01

The aim of a probabilistic output analysis is to derive a probability distribution of possible output values for a program from a probability distribution of its input. We present a method for performing static output analysis, based on program transformation techniques. It generates a probability...

Study on networking issues of medium earth orbit satellite communications systems

Science.gov (United States)

Araki, Noriyuki; Shinonaga, Hideyuki; Ito, Yasuhiko

1993-01-01

Two networking issues of communications systems with medium earth orbit (MEO) satellites, namely network architectures and location determination and registration methods for hand-held terminals, are investigated in this paper. For network architecture, five candidate architectures are considered and evaluated in terms of signaling traffic. For location determination and registration, two methods are discussed and evaluated.

Power feeding to terminal devices in optical subscriber network; Hikari fuaiba tsushin ni okeru tanmatsu kiki eno kyuden

Energy Technology Data Exchange (ETDEWEB)

Yamasaki, M

1998-09-01

This paper outlines present state of the feeding system in the light access system in consideration of backup in case of home power failure. In the optical communication, equipment with bilateral conversion function for light and electricity has to be installed both on communication service side and home side. Outline of the light access system and equipment requiring backup are shown. The following items are explained: main types of the light access system, such as FTTC (fiber to the curb), FTTP (fiber to the pole), FTTH (fiber to the home) and HFC (hybrid fiber coax), and the feeding system; problems on feeding system for the light access system. Key elements of ONU (optical network unit) for FTTH and construction of the ONU power source are illustrated. The ONU power source is composed of a backup power supply unit and main body supply unit. Backup power is indispensable to the ONU and analog telephones: output is supplied by the backup batteries in power failure. For miniaturization of the backup power source, power supply circuits and backup batteries have to be miniaturized simultaneously. History of miniaturization is explained on the experimental models. 6 refs., 7 figs., 1 tab.

Reliability Analysis Techniques for Communication Networks in Nuclear Power Plant

International Nuclear Information System (INIS)

Lim, T. J.; Jang, S. C.; Kang, H. G.; Kim, M. C.; Eom, H. S.; Lee, H. J.

2006-09-01

The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for nuclear power plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of this study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks

Internal measuring models in trained neural networks for parameter estimation from images

NARCIS (Netherlands)

Feng, Tian-Jin; Feng, T.J.; Houkes, Z.; Korsten, Maarten J.; Spreeuwers, Lieuwe Jan

1992-01-01

The internal representations of 'learned' knowledge in neural networks are still poorly understood, even for backpropagation networks. The paper discusses a possible interpretation of learned knowledge of a network trained for parameter estimation from images. The outputs of the hidden layer are the

Endogenous network of firms and systemic risk

Science.gov (United States)

Ma, Qianting; He, Jianmin; Li, Shouwei

2018-02-01

We construct an endogenous network characterized by commercial credit relationships connecting the upstream and downstream firms. Simulation results indicate that the endogenous network model displays a scale-free property which exists in real-world firm systems. In terms of the network structure, with the expansion of the scale of network nodes, the systemic risk increases significantly, while the heterogeneities of network nodes have no effect on systemic risk. As for firm micro-behaviors, including the selection range of trading partners, actual output, labor requirement, price of intermediate products and employee salaries, increase of all these parameters will lead to higher systemic risk.

Inverter communications using output signal

Science.gov (United States)

Chapman, Patrick L.

2017-02-07

Technologies for communicating information from an inverter configured for the conversion of direct current (DC) power generated from an alternative source to alternating current (AC) power are disclosed. The technologies include determining information to be transmitted from the inverter over a power line cable connected to the inverter and controlling the operation of an output converter of the inverter as a function of the information to be transmitted to cause the output converter to generate an output waveform having the information modulated thereon.

High serotonin levels during brain development alter the structural input-output connectivity of neural networks in the rat somatosensory layer IV

Directory of Open Access Journals (Sweden)

Stéphanie eMiceli

2013-06-01

Full Text Available Homeostatic regulation of serotonin (5-HT concentration is critical for normal topographical organization and development of thalamocortical (TC afferent circuits. Down-regulation of the serotonin transporter (SERT and the consequent impaired reuptake of 5-HT at the synapse, results in a reduced terminal branching of developing TC afferents within the primary somatosensory cortex (S1. Despite the presence of multiple genetic models, the effect of high extracellular 5-HT levels on the structure and function of developing intracortical neural networks is far from being understood. Here, using juvenile SERT knockout (SERT-/- rats we investigated, in vitro, the effect of increased 5-HT levels on the structural organization of (i the thalamocortical projections of the ventroposteromedial thalamic nucleus towards S1, (ii the general barrel-field pattern and (iii the electrophysiological and morphological properties of the excitatory cell population in layer IV of S1 (spiny stellate and pyramidal cells. Our results confirmed previous findings that high levels of 5-HT during development lead to a reduction of the topographical precision of TCA projections towards the barrel cortex. Also, the barrel pattern was altered but not abolished in SERT-/- rats. In layer IV, both excitatory spiny stellate and pyramidal cells showed a significantly reduced intracolumnar organization of their axonal projections. In addition, the layer IV spiny stellate cells gave rise to a prominent projection towards the infragranular layer Vb. Our findings point to a structural and functional reorganization, of TCAs, as well as early stage intracortical microcircuitry, following the disruption of 5-HT reuptake during critical developmental periods. The increased projection pattern of the layer IV neurons suggests that the intracortical network changes are not limited to the main entry layer IV but may also affect the subsequent stages of the canonical circuits of the barrel

[Remote results of plastic operations on the tricuspid valve in patients with cardiac insufficiency at terminal stage].

Science.gov (United States)

Habriielian, A V; Smorzhevs'kyĭ, V I; Onishchenko, V F; Beleĭovych, V V; Topchu, Ie I; Domans'kyĭ, T M; Myroniuk, O I

2011-07-01

Comparative analysis of the results of plastic operations performance on a tricuspid valve (TV) in patients, suffering cardiac insufficiency in terminal stage, was conducted. In late postoperative period the indices of intracardial hemodynamics (cardiac output fraction, regurgitation on TV) and clinical features (severity of symptoms, quality of life) after plastic operations, using a support ring, have differed significantly from those after performance of a sutured plasty. The valve function during five years was secured in 91.1% of patients.

Cascade of links in complex networks

Energy Technology Data Exchange (ETDEWEB)

Feng, Yeqian; Sun, Bihui [Department of Management Science, School of Government, Beijing Normal University, 100875 Beijing (China); Zeng, An, E-mail: anzeng@bnu.edu.cn [School of Systems Science, Beijing Normal University, 100875 Beijing (China)

2017-01-30

Cascading failure is an important process which has been widely used to model catastrophic events such as blackouts and financial crisis in real systems. However, so far most of the studies in the literature focus on the cascading process on nodes, leaving the possibility of link cascade overlooked. In many real cases, the catastrophic events are actually formed by the successive disappearance of links. Examples exist in the financial systems where the firms and banks (i.e. nodes) still exist but many financial trades (i.e. links) are gone during the crisis, and the air transportation systems where the airports (i.e. nodes) are still functional but many airlines (i.e. links) stop operating during bad weather. In this letter, we develop a link cascade model in complex networks. With this model, we find that both artificial and real networks tend to collapse even if a few links are initially attacked. However, the link cascading process can be effectively terminated by setting a few strong nodes in the network which do not respond to any link reduction. Finally, a simulated annealing algorithm is used to optimize the location of these strong nodes, which significantly improves the robustness of the networks against the link cascade. - Highlights: • We propose a link cascade model in complex networks. • Both artificial and real networks tend to collapse even if a few links are initially attacked. • The link cascading process can be effectively terminated by setting a few strong nodes. • A simulated annealing algorithm is used to optimize the location of these strong nodes.

Cascade of links in complex networks

International Nuclear Information System (INIS)

Feng, Yeqian; Sun, Bihui; Zeng, An

2017-01-01

Cascading failure is an important process which has been widely used to model catastrophic events such as blackouts and financial crisis in real systems. However, so far most of the studies in the literature focus on the cascading process on nodes, leaving the possibility of link cascade overlooked. In many real cases, the catastrophic events are actually formed by the successive disappearance of links. Examples exist in the financial systems where the firms and banks (i.e. nodes) still exist but many financial trades (i.e. links) are gone during the crisis, and the air transportation systems where the airports (i.e. nodes) are still functional but many airlines (i.e. links) stop operating during bad weather. In this letter, we develop a link cascade model in complex networks. With this model, we find that both artificial and real networks tend to collapse even if a few links are initially attacked. However, the link cascading process can be effectively terminated by setting a few strong nodes in the network which do not respond to any link reduction. Finally, a simulated annealing algorithm is used to optimize the location of these strong nodes, which significantly improves the robustness of the networks against the link cascade. - Highlights: • We propose a link cascade model in complex networks. • Both artificial and real networks tend to collapse even if a few links are initially attacked. • The link cascading process can be effectively terminated by setting a few strong nodes. • A simulated annealing algorithm is used to optimize the location of these strong nodes.

Near-optimal power allocation with PSO algorithm for MIMO cognitive networks using multiple AF two-way relays

KAUST Repository

Alsharoa, Ahmad M.

2014-06-01

In this paper, the problem of power allocation for a multiple-input multiple-output two-way system is investigated in underlay Cognitive Radio (CR) set-up. In the CR underlay mode, secondary users are allowed to exploit the spectrum allocated to primary users in an opportunistic manner by respecting a tolerated temperature limit. The secondary networks employ an amplify-and-forward two-way relaying technique in order to maximize the sum rate under power budget and interference constraints. In this context, we formulate an optimization problem that is solved in two steps. First, we derive a closed-form expression of the optimal power allocated to terminals. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the power allocated to secondary relays. Simulation results demonstrate the efficiency of the proposed solution and analyze the impact of some system parameters on the achieved performance. © 2014 IEEE.

Implementing controlled-unitary operations over the butterfly network

Energy Technology Data Exchange (ETDEWEB)

Soeda, Akihito; Kinjo, Yoshiyuki; Turner, Peter S. [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo (Japan); Murao, Mio [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan and NanoQuine, The University of Tokyo, Tokyo (Japan)

2014-12-04

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

Mobile location services over the next generation IP core network

DEFF Research Database (Denmark)

Thongthammachart, Saowanee; Olesen, Henning

2003-01-01

network is changing from circuit-switched to packet-switched technology and evolving to an IP core network based on IPv6. The IP core network will allow all IP devices to be connected seamlessly. Due to the movement detection mechanism of Mobile IPv6, mobile terminals will periodically update....... The concept of mobile location services over the next generation IP networks is described. We also discuss the effectiveness of the short-range wireless network regarding a mobile user's position inside buildings and hotspot areas....

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-03-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA.cm-2, and average power density of ~4.44 mW.cm-2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-01-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA·cm−2, and average power density of ~4.44 mW·cm−2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics. PMID:25791299

Instrument surveillance and calibration verification through plant wide monitoring using autoassociative neural networks

International Nuclear Information System (INIS)

Wrest, D.J.; Hines, J.W.; Uhrig, R.E.

1996-01-01

The approach to instrument surveillance and calibration verification (ISCV) through plant wide monitoring proposed in this paper is an autoassociative neural network (AANN) which will utilize digitized data presently available in the Safety Parameter Display computer system from Florida Power Corporations Crystal River number 3 nuclear power plant. An autoassociative neural network is one in which the outputs are trained to emulate the inputs over an appropriate dynamic range. The relationships between the different variables are embedded in the weights by the training process. As a result, the output can be a correct version of an input pattern that has been distorted by noise, missing data, or non-linearities. Plant variables that have some degree of coherence with each other constitute the inputs to the network. Once the network has been trained with normal operational data it has been shown to successfully monitor the selected plant variables to detect sensor drift or failure by simply comparing the network inputs with the outputs. The AANN method of monitoring many variables not only indicates that there is a sensor failure, it clearly indicates the signal channel in which the signal error has occurred. (author). 11 refs, 8 figs, 2 tabs

Instrument surveillance and calibration verification through plant wide monitoring using autoassociative neural networks

Energy Technology Data Exchange (ETDEWEB)

Wrest, D J; Hines, J W; Uhrig, R E [Tennessee Univ., Knoxville, TN (United States). Dept. of Nuclear Engineering

1997-12-31

The approach to instrument surveillance and calibration verification (ISCV) through plant wide monitoring proposed in this paper is an autoassociative neural network (AANN) which will utilize digitized data presently available in the Safety Parameter Display computer system from Florida Power Corporations Crystal River number 3 nuclear power plant. An autoassociative neural network is one in which the outputs are trained to emulate the inputs over an appropriate dynamic range. The relationships between the different variables are embedded in the weights by the training process. As a result, the output can be a correct version of an input pattern that has been distorted by noise, missing data, or non-linearities. Plant variables that have some degree of coherence with each other constitute the inputs to the network. Once the network has been trained with normal operational data it has been shown to successfully monitor the selected plant variables to detect sensor drift or failure by simply comparing the network inputs with the outputs. The AANN method of monitoring many variables not only indicates that there is a sensor failure, it clearly indicates the signal channel in which the signal error has occurred. (author). 11 refs, 8 figs, 2 tabs.

Information transmission and signal permutation in active flow networks

Science.gov (United States)

Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn

2018-03-01

Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

Improvement of the ID model for quantitative network data

DEFF Research Database (Denmark)

Sørensen, Peter Borgen; Damgaard, Christian Frølund; Dupont, Yoko Luise

2015-01-01

Many interactions are often poorly registered or even unobserved in empirical quantitative networks. Hence, the output of the statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. Such artefa......Many interactions are often poorly registered or even unobserved in empirical quantitative networks. Hence, the output of the statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks......)1. This presentation will illustrate the application of the ID method based on a data set which consists of counts of visits by 152 pollinator species to 16 plant species. The method is based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1), pi...... reproduce the high number of zero valued cells in the data set and mimic the sampling distribution. 1 Sørensen et al, Journal of Pollination Ecology, 6(18), 2011, pp129-139...

Modelling computer networks

International Nuclear Information System (INIS)

Max, G

2011-01-01

Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

Application of neural network to CT

International Nuclear Information System (INIS)

Ma, Xiao-Feng; Takeda, Tatsuoki

1999-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multilayer neural network. Multilayer neural networks are extensively investigated and practically applied to solution of various problems such as inverse problems or time series prediction problems. From learning an input-output mapping from a set of examples, neural networks can be regarded as synthesizing an approximation of multidimensional function (that is, solving the problem of hypersurface reconstruction, including smoothing and interpolation). From this viewpoint, neural networks are well suited to the solution of CT image reconstruction. Though a conventionally used object function of a neural network is composed of a sum of squared errors of the output data, we can define an object function composed of a sum of residue of an integral equation. By employing an appropriate line integral for this integral equation, we can construct a neural network that can be used for CT. We applied this method to some model problems and obtained satisfactory results. As it is not necessary to discretized the integral equation using this reconstruction method, therefore it is application to the problem of complicated geometrical shapes is also feasible. Moreover, in neural networks, interpolation is performed quite smoothly, as a result, inverse mapping can be achieved smoothly even in case of including experimental and numerical errors, However, use of conventional back propagation technique for optimization leads to an expensive computation cost. To overcome this drawback, 2nd order optimization methods or parallel computing will be applied in future. (J.P.N.)

Structural factoring approach for analyzing stochastic networks

Science.gov (United States)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

LNG TERMINAL SAFE OPERATION MANAGEMENT

Directory of Open Access Journals (Sweden)

Andrzej ADAMKIEWICZ

2012-07-01

Full Text Available This article presents the significance of LNG terminal safety issues in natural gas sea transport. It shows particular requirements for LNG transmission installations resulting from the specific properties of LNG. Out of the multi‐layer critical safety areas comprising structural elements of the terminal safety system, possibilities to decrease the risk of emergency occurrence on LNG terminals have been selected. Tasks performed by the LNG terminal, together with its own personnel and the outside one, have been defined. General theses for LNG terminal safety have been formulated.

Self-deception in terminal patients: belief system at stake

Directory of Open Access Journals (Sweden)

Luis E Echarte

2016-02-01

Full Text Available A substantial minority of patients with terminal illness hold unrealistically hopeful beliefs about the severity of their disease or the nature of its treatment, considering therapy as curative rather than palliative. We propose that this attitude may be understood as self-deception, following the current psychological theories about this topic. In this article we suggest that the reason these patients deceive themselves is to preserve their belief systems. According to some philosophical accounts, the human belief system (HBS is constituted as a web with a few stable central nodes –deep seated beliefs– intimately related with the self. We hypothesize that the mind may possess defensive mechanisms, mostly non-conscious, that reject certain sensory inputs (e.g., a fatal diagnosis that may undermine deep-seated beliefs. This interpretation is in line with the theory of cognitive dissonance. Following this reasoning, we also propose that HBS-related self-deception would entail a lower cognitive load than that associated with confronting the truth: whereas the latter would engage a myriad of high cognitive functions to re-configure crucial aspects of the self, including the setting of plans, goals, or even a behavioral output, the former would be mostly non-conscious. Overall, we believe that our research supports the hypothesis that in cases of terminal illness, (self-deceiving requires less effort than accepting the truth.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Nonleaking battery terminals.

Science.gov (United States)

Snider, W. E.; Nagle, W. J.

1972-01-01

Three different terminals were designed for usage in a 40 ampere/hour silver zinc battery which has a 45% KOH by weight electrolyte in a plastic battery case. Life tests, including thermal cycling, electrical charge and discharge for up to three years duration, were conducted on these three different terminal designs. Tests for creep rate and tensile strength were conducted on the polyphenylene oxide plastic battery cases. Some cases were unused and others containing KOH electrolyte were placed on life tests. The design and testing of nonleaking battery terminals for use with a KOH electrolyte in a plastic case are considered.

A network-base analysis of CMIP5 "historical" experiments

Science.gov (United States)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

DESAIN ALGORITMA DAN SIMULASI ROUTING UNTUK GATEWAY AD HOC WIRELESS NETWORKS

Directory of Open Access Journals (Sweden)

Nixson Meok

2009-12-01

Full Text Available   Routing protocol to the wireless ad hoc networks is very needed in the communication process between some terminals, to send the data packet through one or several node(s to the destination address where the network typology is always changing. Many previous works that discussed about routing ad hoc both for manet (mobile ad hoc networks and wireless networks, but the emphasis have more focus on comparing the performance of several routing ad hoc. While in this work, there is a bulding of routing algorithm model to gateway in land to the nodes that analogized as a boat that move on the sea. With the assumption that the communication inter terminals to radio band of Very High Frequency, thus algorithm that built in the simulation based on the range gap of the HF frequency. The result of this simulation will be developed as the platform to implement the service development of multiuser communication

water demand prediction using artificial neural network

African Journals Online (AJOL)

user

2017-01-01

Jan 1, 2017 ... Interface for activation and deactivation of valves. •. Interface demand ... process could be done and monitored at the computer terminal as expected of a .... [15] Arbib, M. A.The Handbook of Brain Theory and Neural. Networks.

Downlink power distributions for 2G and 3G mobile communication networks.

Science.gov (United States)

Colombi, Davide; Thors, Björn; Persson, Tomas; Wirén, Niklas; Larsson, Lars-Eric; Jonsson, Mikael; Törnevik, Christer

2013-12-01

Knowledge of realistic power levels is key when conducting accurate EMF exposure assessments. In this study, downlink output power distributions for radio base stations in 2G and 3G mobile communication networks have been assessed. The distributions were obtained from network measurement data collected from the Operations Support System, which normally is used for network monitoring and management. Significant amounts of data were gathered simultaneously for large sets of radio base stations covering wide geographical areas and different environments. The method was validated with in situ measurements. For the 3G network, the 90th percentile of the averaged output power during high traffic hours was found to be 43 % of the maximum available power. The corresponding number for 2G, with two or more transceivers installed, was 65 % or below.

Alternatif Lokasi Terminal Sebagai Pusat Pertumbuhan Ekonomi di Doloksanggul Kabupaten Humbang Hasundutan

Directory of Open Access Journals (Sweden)

Jusmar Effendi Simamora

2014-08-01

Full Text Available Doloksanggul as the Capital District of Humbang Hasundutan also as the center economic growth until now has not had a terminal infrastructure. The result appears terminal shadows that make the city crowded and poor quality of public transport services, so that the internal and external connectivity hub disrupted economic growth. While the terminal as one element of ground transportation can lead to multiple economic effects (multiplier effect to the local and regional economy, so it has a very strategic role in supporting economic growth centers. This study aims to determine the location of the terminal is capable of supporting Doloksanggul as the center of economic growth in the District Humbang Hasundutan through assessment criteria used. To achieve the research objectives used a qualitative-descriptive and quantitative-descriptive approach which is using purposive sampling techniques, by restricting the respondent only directly related to the problem, namely regulators, operators and users (passengers. The analytical method used is the method of Analytic Hierarchy Process (AHP, because it is a flexible method of decision-making by combining a variety of considerations to obtain multi-criteria problem solving. The formulated criteria are the easies of accessibility to enter and from the terminal location, the availability of transportation networks, the ultimate destination of public transport track AKAP/AKDP, adjacent to the central market, located in the city center. The alternatives terminal location are located in the Bonanionan village, the Pasaribu village and the Simangaronsang village. Based on the results of the analysis found that the best location is the Bonanionan village with value of 0.6022 (60.22% followed the Pasaribu village with value of 0.3073 (30.73% and the last is the Simangaronsang village with value of 0.0905 (9.05%.

Cascaded Subpatch Networks for Effective CNNs.

Science.gov (United States)

Jiang, Xiaoheng; Pang, Yanwei; Sun, Manli; Li, Xuelong

2017-05-12

Conventional convolutional neural networks use either a linear or a nonlinear filter to extract features from an image patch (region) of spatial size Hx W (typically, H is small and is equal to W, e.g., H is 5 or 7 ). Generally, the size of the filter is equal to the size Hx W of the input patch. We argue that the representational ability of equal-size strategy is not strong enough. To overcome the drawback, we propose to use subpatch filter whose spatial size hx w is smaller than Hx W . The proposed subpatch filter consists of two subsequent filters. The first one is a linear filter of spatial size hx w and is aimed at extracting features from spatial domain. The second one is of spatial size 1x 1 and is used for strengthening the connection between different input feature channels and for reducing the number of parameters. The subpatch filter convolves with the input patch and the resulting network is called a subpatch network. Taking the output of one subpatch network as input, we further repeat constructing subpatch networks until the output contains only one neuron in spatial domain. These subpatch networks form a new network called the cascaded subpatch network (CSNet). The feature layer generated by CSNet is called the csconv layer. For the whole input image, we construct a deep neural network by stacking a sequence of csconv layers. Experimental results on five benchmark data sets demonstrate the effectiveness and compactness of the proposed CSNet. For example, our CSNet reaches a test error of 5.68% on the CIFAR10 data set without model averaging. To the best of our knowledge, this is the best result ever obtained on the CIFAR10 data set.

Use of medium-range numerical weather prediction model output to produce forecasts of streamflow

Science.gov (United States)

Clark, M.P.; Hay, L.E.

2004-01-01

This paper examines an archive containing over 40 years of 8-day atmospheric forecasts over the contiguous United States from the NCEP reanalysis project to assess the possibilities for using medium-range numerical weather prediction model output for predictions of streamflow. This analysis shows the biases in the NCEP forecasts to be quite extreme. In many regions, systematic precipitation biases exceed 100% of the mean, with temperature biases exceeding 3??C. In some locations, biases are even higher. The accuracy of NCEP precipitation and 2-m maximum temperature forecasts is computed by interpolating the NCEP model output for each forecast day to the location of each station in the NWS cooperative network and computing the correlation with station observations. Results show that the accuracy of the NCEP forecasts is rather low in many areas of the country. Most apparent is the generally low skill in precipitation forecasts (particularly in July) and low skill in temperature forecasts in the western United States, the eastern seaboard, and the southern tier of states. These results outline a clear need for additional processing of the NCEP Medium-Range Forecast Model (MRF) output before it is used for hydrologic predictions. Techniques of model output statistics (MOS) are used in this paper to downscale the NCEP forecasts to station locations. Forecasted atmospheric variables (e.g., total column precipitable water, 2-m air temperature) are used as predictors in a forward screening multiple linear regression model to improve forecasts of precipitation and temperature for stations in the National Weather Service cooperative network. This procedure effectively removes all systematic biases in the raw NCEP precipitation and temperature forecasts. MOS guidance also results in substantial improvements in the accuracy of maximum and minimum temperature forecasts throughout the country. For precipitation, forecast improvements were less impressive. MOS guidance increases

Salient Feature Selection Using Feed-Forward Neural Networks and Signal-to-Noise Ratios with a Focus Toward Network Threat Detection and Classification

Science.gov (United States)

2014-03-27

0.8.0. The virtual machine’s network adapter was set to internal network only to keep any outside traffic from interfering. A MySQL -based query...primary output of Fullstats is the ARFF file format, intended for use with the WEKA Java -based data mining software developed at the University of Waikato

Secure Media Independent Handover Message Transport in Heterogeneous Networks

Directory of Open Access Journals (Sweden)

Cho Choong-Ho

2009-01-01

Full Text Available The IEEE 802.21 framework for Media Independent Handover (MIH provides seamless vertical handover support for multimode mobile terminals. MIH messages are exchanged over various wireless media between mobile terminals and access networks to facilitate seamless handover. This calls for the need to secure MIH messages against network security threats in the wireless medium. In this paper, we first analyze IPSec/IKEv2 and DTLS security solution for secure MIH message transport. We show that handover latency can be an impediment to the use of IPSec and DTLS solutions. To overcome the handover overhead and hence minimize authentication time, a new secure MIH message transport solution, referred as MIHSec in this paper, is proposed. Experimental results are obtained for MIH between WLAN and Ethernet networks and the impacts of MIH message security on the handover latency are evaluated for IPSec, DTLS, and MIHSec security solutions. The effectiveness of MIHSec is demonstrated.

Management and optimization of the CPCU network working

Energy Technology Data Exchange (ETDEWEB)

Silvain, D. (Compagnie Parisienne de Chauffage Urbain, 75 - Paris (FR))

1991-10-01

The CPCU steam distribution network is supplemented by a return network for the condensation water. The data system installed in 1988 provides, for the real time, management of the function of the two networks and a reduction in production costs. For the steam, data required in the network, the boiler houses and from external sources are processed by local network of five microprocessors and permit: - with time delay: technical and economic production optimizing calculations, or forecasts, for the following day, of the total required output and the procedure necessary for supplying this at the lowest cost; - in real time: on the basis of the forecasts for the previous day, creating the production instructions for the boiler houses and the instructions for the network remote control elements; - in case of an unexpected occurrence: immediate creation of new operating forecasts for the boiler houses for the establishing management data in real time. For the water, the system forecasts the volume to be returned to the boiler depending on the quantity of steam to be produced. Subsequently, an analysis is carried out in real time of pressures and outputs measured in the network for deriving valve movements and the pump stop/start procedure for guaranteeing the return of the water. The architecture, basic principles and software developed for this application can be used in other steam or water networks and, in a general manner, are adaptable for the management of any complex multi-supplier or multicustomer systems.

Nuclear networking.

Science.gov (United States)

Xie, Wei; Burke, Brian

2017-07-04

Nuclear lamins are intermediate filament proteins that represent important structural components of metazoan nuclear envelopes (NEs). By combining proteomics and superresolution microscopy, we recently reported that both A- and B-type nuclear lamins form spatially distinct filament networks at the nuclear periphery of mouse fibroblasts. In particular, A-type lamins exhibit differential association with nuclear pore complexes (NPCs). Our studies reveal that the nuclear lamina network in mammalian somatic cells is less ordered and more complex than that of amphibian oocytes, the only other system in which the lamina has been visualized at high resolution. In addition, the NPC component Tpr likely links NPCs to the A-type lamin network, an association that appears to be regulated by C-terminal modification of various A-type lamin isoforms. Many questions remain, however, concerning the structure and assembly of lamin filaments, as well as with their mode of association with other nuclear components such as peripheral chromatin.

PID Neural Network Based Speed Control of Asynchronous Motor Using Programmable Logic Controller

Directory of Open Access Journals (Sweden)

MARABA, V. A.

2011-11-01

Full Text Available This paper deals with the structure and characteristics of PID Neural Network controller for single input and single output systems. PID Neural Network is a new kind of controller that includes the advantages of artificial neural networks and classic PID controller. Functioning of this controller is based on the update of controller parameters according to the value extracted from system output pursuant to the rules of back propagation algorithm used in artificial neural networks. Parameters obtained from the application of PID Neural Network training algorithm on the speed model of the asynchronous motor exhibiting second order linear behavior were used in the real time speed control of the motor. Programmable logic controller (PLC was used as real time controller. The real time control results show that reference speed successfully maintained under various load conditions.

Effort levels of the partners in networked manufacturing

Science.gov (United States)

Chai, G. R.; Cai, Z.; Su, Y. N.; Zong, S. L.; Zhai, G. Y.; Jia, J. H.

2017-08-01

Compared with traditional manufacturing mode, could networked manufacturing improve effort levels of the partners? What factors will affect effort level of the partners? How to encourage the partners to improve their effort levels? To answer these questions, we introduce network effect coefficient to build effort level model of the partners in networked manufacturing. The results show that (1) with the increase of the network effect in networked manufacturing, the actual effort level can go beyond the ideal level of traditional manufacturing. (2) Profit allocation based on marginal contribution rate would help improve effort levels of the partners in networked manufacturing. (3) The partners in networked manufacturing who wishes to have a larger distribution ratio must make a higher effort level, and enterprises with insufficient effort should be terminated in networked manufacturing.

Intrinsic terminators in Mycoplasma hyopneumoniae transcription.

Science.gov (United States)

Fritsch, Tiago Ebert; Siqueira, Franciele Maboni; Schrank, Irene Silveira

2015-04-08

Mycoplasma hyopneumoniae, an important pathogen of swine, exhibits a low guanine and cytosine (GC) content genome. M. hyopneumoniae genome is organised in long transcriptional units and promoter sequences have been mapped upstream of all transcription units. These analysis provided insights into the gene organisation and transcription initiation at the genome scale. However, the presence of transcriptional terminator sequences in the M. hyopneumoniae genome is poorly understood. In silico analyses demonstrated the presence of putative terminators in 82% of the 33 monocistronic units (mCs) and in 74% of the 116 polycistronic units (pCs) considering different classes of terminators. The functional activity of 23 intrinsic terminators was confirmed by RT-PCR and qPCR. Analysis of all terminators found by three software algorithms, combined with experimental results, allowed us to propose a pattern of RNA hairpin formation during the termination process and to predict the location of terminators in the M. hyopneumoniae genome sequence. The stem-loop structures of intrinsic terminators of mycoplasma diverge from the pattern of terminators found in other bacteria due the low content of guanine and cytosine. In M. hyopneumoniae, transcription can end after a transcriptional unit and before its terminator sequence and can also continue past the terminator sequence with RNA polymerases gradually releasing the RNA.

A network architecture for International Business Satellite communications

Science.gov (United States)

Takahata, Fumio; Nohara, Mitsuo; Takeuchi, Yoshio

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

Optical-Correlator Neural Network Based On Neocognitron

Science.gov (United States)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Determining optimal stations for HVDC terminals; Ermittlung vorteilhafter HGUe-Anschluss knoten

Energy Technology Data Exchange (ETDEWEB)

Linnemann, C.; Echternacht, D.; Breuer, C.; Heuberger, D.; Moser, A. [RWTH Aachen (Germany). Inst. fuer Elektrische Anlagen und Energiewirtschaft (IAEW)

2012-07-01

Due to a massiv increase in renewable generation capacity the need for grid reinforcements in the European transmission grid is rising significantly. The nuclear phase out in Germany enlarges this effect furthermore. The required transmission capacity can be provided using conventional AC equipment but also the usage of HVDC technology is currently discussed. This paper presents an approach for identifying suitable locations for HVDc terminals. Subsequently the approach is applied to a model of the German transmission network in the year 2022. (orig.)

Interior point algorithm-based power flow optimisation of a combined AC and DC multi-terminal grid

Directory of Open Access Journals (Sweden)

Farhan Beg

2015-01-01

Full Text Available The high cost of power electronic equipment, lower reliability and poor power handling capacity of the semiconductor devices had stalled the deployment of systems based on DC (multi-terminal direct current system (MTDC networks. The introduction of voltage source converters (VSCs for transmission has renewed the interest in the development of large interconnected grids based on both alternate current (AC and DC transmission networks. Such a grid platform also realises the added advantage of integrating the renewable energy sources into the grid. Thus a grid based on DC MTDC network is a possible solution to improve energy security and check the increasing supply demand gap. An optimal power solution for combined AC and DC grids obtained by the solution of the interior point algorithm is proposed in this study. Multi-terminal HVDC grids lie at the heart of various suggested transmission capacity increases. A significant difference is observed when MTDC grids are solved for power flows in place of conventional AC grids. This study deals with the power flow problem of a combined MTDC and an AC grid. The AC side is modelled with the full power flow equations and the VSCs are modelled using a connecting line, two generators and an AC node. The VSC and the DC losses are also considered. The optimisation focuses on several different goals. Three different scenarios are presented in an arbitrary grid network with ten AC nodes and five converter stations.

Impact of small-world network topology on the conventional artificial neural network for the diagnosis of diabetes

International Nuclear Information System (INIS)

Erkaymaz, Okan; Ozer, Mahmut

2016-01-01

Artificial intelligent systems have been widely used for diagnosis of diseases. Due to their importance, new approaches are attempted consistently to increase the performance of these systems. In this study, we introduce a new approach for diagnosis of diabetes based on the Small-World Feed Forward Artificial Neural Network (SW- FFANN). We construct the small-world network by following the Watts–Strogatz approach, and use this architecture for classifying the diabetes, and compare its performance with that of the regular or the conventional FFANN. We show that the classification performance of the SW-FFANN is better than that of the conventional FFANN. The SW-FFANN approach also results in both the highest output correlation and the best output error parameters. We also perform the accuracy analysis and show that SW-FFANN approach exhibits the highest classifier performance.

LNG TERMINAL SAFE OPERATION MANAGEMENT

OpenAIRE

Andrzej ADAMKIEWICZ; Włodzimierz KAMIŃSKI

2012-01-01

This article presents the significance of LNG terminal safety issues in natural gas sea transport. It shows particular requirements for LNG transmission installations resulting from the specific properties of LNG. Out of the multi‐layer critical safety areas comprising structural elements of the terminal safety system, possibilities to decrease the risk of emergency occurrence on LNG terminals have been selected. Tasks performed by the LNG terminal, together with its own personnel and the out...

Networks of Cells and Petri Nets

OpenAIRE

Bernardini, Francesco; Gheorgue, Marian; Margenstern, Maurice; Verlan, Sergey

2007-01-01

We introduce a new class of P systems, called networks of cells, with rules allowing several cells to simultaneously interact with each other in order to produce some new objects inside some other output cells. We define different types of behavior for networks of cells by considering alternative strategies for the application of the rules: sequential application, free parallelism, maximal parallelism, locally-maximal parallelism and minimal parallelism. We devise a way for tra...

Optimal Output of Distributed Generation Based On Complex Power Increment

Science.gov (United States)

Wu, D.; Bao, H.

2017-12-01

In order to meet the growing demand for electricity and improve the cleanliness of power generation, new energy generation, represented by wind power generation, photovoltaic power generation, etc has been widely used. The new energy power generation access to distribution network in the form of distributed generation, consumed by local load. However, with the increase of the scale of distribution generation access to the network, the optimization of its power output is becoming more and more prominent, which needs further study. Classical optimization methods often use extended sensitivity method to obtain the relationship between different power generators, but ignore the coupling parameter between nodes makes the results are not accurate; heuristic algorithm also has defects such as slow calculation speed, uncertain outcomes. This article proposes a method called complex power increment, the essence of this method is the analysis of the power grid under steady power flow. After analyzing the results we can obtain the complex scaling function equation between the power supplies, the coefficient of the equation is based on the impedance parameter of the network, so the description of the relation of variables to the coefficients is more precise Thus, the method can accurately describe the power increment relationship, and can obtain the power optimization scheme more accurately and quickly than the extended sensitivity method and heuristic method.

Multi input single output model predictive control of non-linear bio-polymerization process

Energy Technology Data Exchange (ETDEWEB)

Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)

2015-05-15

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

Termination unit

Energy Technology Data Exchange (ETDEWEB)

Traeholt, Chresten; Willen, Dag; Roden, Mark; Tolbert, Jerry C.; Lindsay, David; Fisher, Paul W.; Nielsen, Carsten Thidemann

2016-05-03

Cable end section comprises end-parts of N electrical phases/neutral, and a thermally-insulation envelope comprising cooling fluid. The end-parts each comprises a conductor and are arranged with phase 1 innermost, N outermost surrounded by the neutral, electrical insulation being between phases and N and neutral. The end-parts comprise contacting surfaces located sequentially along the longitudinal extension of the end-section. A termination unit has an insulating envelope connected to a cryostat, special parts at both ends comprising an adapter piece at the cable interface and a closing end-piece terminating the envelope in the end-section. The special parts houses an inlet and/or outlet for cooling fluid. The space between an inner wall of the envelope and a central opening of the cable is filled with cooling fluid. The special part at the end connecting to the cryostat houses an inlet or outlet, splitting cooling flow into cable annular flow and termination annular flow.

MIMO Communication for Cellular Networks

CERN Document Server

Huang, Howard; Venkatesan, Sivarama

2012-01-01

As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

NARCIS (Netherlands)

Bolzoni, D.; Crispo, Bruno; Etalle, Sandro

2007-01-01

We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

Discriminating lysosomal membrane protein types using dynamic neural network.

Science.gov (United States)

Tripathi, Vijay; Gupta, Dwijendra Kumar

2014-01-01

This work presents a dynamic artificial neural network methodology, which classifies the proteins into their classes from their sequences alone: the lysosomal membrane protein classes and the various other membranes protein classes. In this paper, neural networks-based lysosomal-associated membrane protein type prediction system is proposed. Different protein sequence representations are fused to extract the features of a protein sequence, which includes seven feature sets; amino acid (AA) composition, sequence length, hydrophobic group, electronic group, sum of hydrophobicity, R-group, and dipeptide composition. To reduce the dimensionality of the large feature vector, we applied the principal component analysis. The probabilistic neural network, generalized regression neural network, and Elman regression neural network (RNN) are used as classifiers and compared with layer recurrent network (LRN), a dynamic network. The dynamic networks have memory, i.e. its output depends not only on the input but the previous outputs also. Thus, the accuracy of LRN classifier among all other artificial neural networks comes out to be the highest. The overall accuracy of jackknife cross-validation is 93.2% for the data-set. These predicted results suggest that the method can be effectively applied to discriminate lysosomal associated membrane proteins from other membrane proteins (Type-I, Outer membrane proteins, GPI-Anchored) and Globular proteins, and it also indicates that the protein sequence representation can better reflect the core feature of membrane proteins than the classical AA composition.

Oil output's changing fortunes

International Nuclear Information System (INIS)

Eldridge, D.

1994-01-01

The Petroleum Economist, previously the Petroleum Press Service, has been making annual surveys of output levels of petroleum in all the oil-producing countries since its founding in 1934. This article documents trends and changes in the major oil-producing countries output from 1934 until the present. This analysis is linked with the political and historical events accompanying these changes, notably the growth of Middle Eastern oil production, the North Sea finds and most recently, Iraq's invasion of Kuwait in 1990. (UK)

Optimal transmit power allocation for MIMO two-way cognitive relay networks with multiple relays using AF strategy

KAUST Repository

Alsharoa, Ahmad M.; Ghazzai, Hakim; Alouini, Mohamed-Slim

2014-01-01

In this letter, we consider a multiple-input multiple-output two-way cognitive radio system under a spectrum sharing scenario, where primary and secondary users operate on the same frequency band. The secondary terminals aims to exchange different

DIST/AVC Out-Put Definition.

Science.gov (United States)

Wilkinson, Gene L.

The first stage of development of a management information system for DIST/AVC (Division of Instructional Technology/Audio-Visual Center) is the definition of out-put units. Some constraints on the definition of output units are: 1) they should reflect goals of the organization, 2) they should reflect organizational structure and procedures, and…

DCS-Neural-Network Program for Aircraft Control and Testing

Science.gov (United States)

Jorgensen, Charles C.

2006-01-01

A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from wind-tunnel test data and computing real-time stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

A neural network model of the relativistic electron flux at geosynchronous orbit

International Nuclear Information System (INIS)

Koons, H.C.; Gorney, D.J.

1991-01-01

A neural network has been developed to model the temporal variations of relativistic (>3 MeV) electrons at geosynchronous orbit based on model inputs consisting of 10 consecutive days of the daily sum of the planetary magnetic index ΣKp. The neural network consists of three layers of neurons, containing 10 neurons in the input layer, 6 neurons in a hidden layer, and 1 output neuron. The output is a prediction of the daily-averaged electron flux for the tenth day. The neural network was trained using 62 days of data from July 1, 1984, through August 31, 1984, from the SEE spectrometer on the geosynchronous spacecraft 1982-019. The performance of the model was measured by comparing model outputs with measured fluxes over a 6-year period from April 19, 1982, to June 4, 1988. For the entire data set the rms logarithmic error of the neural network is 0.76, and the average logarithmic error is 0.58. The neural network is essentially zero biased, and for accumulation intervals of 3 days or longer the average logarithmic error is less than 0.1. The neural network provides results that are significantly more accurate than those from linear prediction filters. The model has been used to simulate conditions which are rarely observed in nature, such as long periods of quiet (ΣKp = 0) and ideal impulses. It has also been used to make reasonably accurate day-ahead forecasts of the relativistic electron flux at geosynchronous orbit

Modelling a variable valve timing spark ignition engine using different neural networks

Energy Technology Data Exchange (ETDEWEB)

Beham, M. [BMW AG, Munich (Germany); Yu, D.L. [John Moores University, Liverpool (United Kingdom). Control Systems Research Group

2004-10-01

In this paper different neural networks (NN) are compared for modelling a variable valve timing spark-ignition (VVT SI) engine. The overall system is divided for each output into five neural multi-input single output (MISO) subsystems. Three kinds of NN, multilayer Perceptron (MLP), pseudo-linear radial basis function (PLRBF), and local linear model tree (LOLIMOT) networks, are used to model each subsystem. Real data were collected when the engine was under different operating conditions and these data are used in training and validation of the developed neural models. The obtained models are finally tested in a real-time online model configuration on the test bench. The neural models run independently of the engine in parallel mode. The model outputs are compared with process output and compared among different models. These models performed well and can be used in the model-based engine control and optimization, and for hardware in the loop systems. (author)

Learning text representation using recurrent convolutional neural network with highway layers

OpenAIRE

Wen, Ying; Zhang, Weinan; Luo, Rui; Wang, Jun

2016-01-01

Recently, the rapid development of word embedding and neural networks has brought new inspiration to various NLP and IR tasks. In this paper, we describe a staged hybrid model combining Recurrent Convolutional Neural Networks (RCNN) with highway layers. The highway network module is incorporated in the middle takes the output of the bi-directional Recurrent Neural Network (Bi-RNN) module in the first stage and provides the Convolutional Neural Network (CNN) module in the last stage with the i...

Nuclear power plant monitoring method by neural network and its application to actual nuclear reactor

International Nuclear Information System (INIS)

Nabeshima, Kunihiko; Suzuki, Katsuo; Shinohara, Yoshikuni; Tuerkcan, E.

1995-11-01

In this paper, the anomaly detection method for nuclear power plant monitoring and its program are described by using a neural network approach, which is based on the deviation between measured signals and output signals of neural network model. The neural network used in this study has three layered auto-associative network with 12 input/output, and backpropagation algorithm is adopted for learning. Furthermore, to obtain better dynamical model of the reactor plant, a new learning technique was developed in which the learning process of the present neural network is divided into initial and adaptive learning modes. The test results at the actual nuclear reactor shows that the neural network plant monitoring system is successfull in detecting in real-time the symptom of small anomaly over a wide power range including reactor start-up, shut-down and stationary operation. (author)

Physical Sequestration of Bacillus anthracis in the Pulmonary Capillaries in Terminal Infection.

Science.gov (United States)

Jouvion, Gregory; Corre, Jean-Philippe; Khun, Huot; Moya-Nilges, Marie; Roux, Pascal; Latroche, Claire; Tournier, Jean-Nicolas; Huerre, Michel; Chrétien, Fabrice; Goossens, Pierre L

2016-07-15

The lung is the terminal target of Bacillus anthracis before death, whatever the route of infection (cutaneous, inhalational, or digestive). During a cutaneous infection in absence of toxins, we observed encapsulated bacteria colonizing the alveolar capillary network, bacteria and hemorrhages in alveolar and bronchiolar spaces, and hypoxic foci in the lung (endothelial cells) and brain (neurons and neuropil). Circulating encapsulated bacteria were as chains of approximately 13 µm in length. Bacteria of such size were immediately trapped within the lung capillary network, but bacteria of shorter length were not. Controlling lung-targeted pathology would be beneficial for anthrax treatment. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Theoretical analysis of magnetic sensor output voltage

International Nuclear Information System (INIS)

Liu Haishun; Dun Chaochao; Dou Linming; Yang Weiming

2011-01-01

The output voltage is an important parameter to determine the stress state in magnetic stress measurement, the relationship between the output voltage and the difference in the principal stresses was investigated by a comprehensive application of magnetic circuit theory, magnetization theory, stress analysis as well as the law of electromagnetic induction, and a corresponding quantitative equation was derived. It is drawn that the output voltage is proportional to the difference in the principal stresses, and related to the angle between the principal stress and the direction of the sensor. This investigation provides a theoretical basis for the principle stresses measurement by output voltage. - Research highlights: → A comprehensive investigation of magnetic stress signal. → Derived a quantitative equation about output voltage and the principal stresses. → The output voltage is proportional to the difference of the principal stresses. → Provide a theoretical basis for the principle stresses measurement.

Simulation and Evaluation of Ethernet Passive Optical Network

Directory of Open Access Journals (Sweden)

Salah A. Jaro Alabady

2013-05-01

Full Text Available      This paper studies simulation and evaluation of Ethernet Passive Optical Network (EPON system, IEEE802.3ah based OPTISM 3.6 simulation program. The simulation program is used in this paper to build a typical ethernet passive optical network, and to evaluate the network performance when using the (1580, 1625 nm wavelength instead of (1310, 1490 nm that used in Optical Line Terminal (OLT and Optical Network Units (ONU's in system architecture of Ethernet passive optical network at different bit rate and different fiber optic length. The results showed enhancement in network performance by increase the number of nodes (subscribers connected to the network, increase the transmission distance, reduces the received power and reduces the Bit Error Rate (BER.   

Down-link power distributions for 2G and 3G mobile communication networks

International Nuclear Information System (INIS)

Colombi, D.; Thors, B.; Persson, T.; Wiren, N.; Larsson, L. E.; Jonsson, M.; Toernevik, C.

2013-01-01

Knowledge of realistic power levels is key when conducting accurate EMF exposure assessments. In this study, down-link output power distributions for radio base stations in 2G and 3G mobile communication networks have been assessed. The distributions were obtained from network measurement data collected from the Operations Support System, which normally is used for network monitoring and management. Significant amounts of data were gathered simultaneously for large sets of radio base stations covering wide geographical areas and different environments. The method was validated with in situ measurements. For the 3G network, the 90. percentile of the averaged output power during high traffic hours was found to be 43 % of the maximum available power. The corresponding number for 2G, with two or more transceivers installed, was 65 % or below. (authors)

Internal-state analysis in layered artificial neural network trained to categorize lung sounds

NARCIS (Netherlands)

Oud, M

2002-01-01

In regular use of artificial neural networks, only input and output states of the network are known to the user. Weight and bias values can be extracted but are difficult to interpret. We analyzed internal states of networks trained to map asthmatic lung sound spectra onto lung function parameters.

Output, renewable energy consumption and trade in Africa

International Nuclear Information System (INIS)

Ben Aïssa, Mohamed Safouane; Ben Jebli, Mehdi; Ben Youssef, Slim

2014-01-01

We use panel cointegration techniques to examine the relationship between renewable energy consumption, trade and output in a sample of 11 African countries covering the period 1980–2008. The results from panel error correction model reveal that there is evidence of a bidirectional causality between output and exports and between output and imports in both the short and long-run. However, in the short-run, there is no evidence of causality between output and renewable energy consumption and between trade (exports or imports) and renewable energy consumption. Also, in the long-run, there is no causality running from output or trade to renewable energy. In the long-run, our estimations show that renewable energy consumption and trade have a statistically significant and positive impact on output. Our energy policy recommendations are that national authorities should design appropriate fiscal incentives to encourage the use of renewable energies, create more regional economic integration for renewable energy technologies, and encourage trade openness because of its positive impact on technology transfer and on output. - Highlights: • We examine the relationship between renewable energy consumption, trade and output in African countries. • There is a bidirectional causality between output and trade in both the short and long-run. • In the short-run, there is no causality between renewable energy consumption and trade or output. • In the long-run, renewable energy consumption and trade have a statistically significant positive impact on output. • African authorities should encourage trade openness because of its positive impact on technology transfer and on output

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar

2018-01-01

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

KAUST Repository

Alfadly, Modar M.

2018-04-12

Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.

GSFC network operations with Tracking and Data Relay Satellites

Science.gov (United States)

Spearing, R.; Perreten, D. E.

The Tracking and Data Relay Satellite System (TDRSS) Network (TN) has been developed to provide services to all NASA User spacecraft in near-earth orbits. Three inter-relating entities will provide these services. The TN has been transformed from a network continuously changing to meet User specific requirements to a network which is flexible to meet future needs without significant changes in operational concepts. Attention is given to the evolution of the TN network, the TN capabilities-space segment, forward link services, tracking services, return link services, the three basic capabilities, single access services, multiple access services, simulation services, the White Sands Ground Terminal, the NASA communications network, and the network control center.

MIMO Techniques for Jamming Threat Suppression in Vehicular Networks

Directory of Open Access Journals (Sweden)

Dimitrios Kosmanos

2016-01-01

Full Text Available Vehicular ad hoc networks have emerged as a promising field of research and development, since they will be able to accommodate a variety of applications, ranging from infotainment to traffic management and road safety. A specific security-related concern that vehicular ad hoc networks face is how to keep communication alive in the presence of radio frequency jamming, especially during emergency situations. Multiple Input Multiple Output techniques are proven to be able to improve some crucial parameters of vehicular communications such as communication range and throughput. In this article, we investigate how Multiple Input Multiple Output techniques can be used in vehicular ad hoc networks as active defense mechanisms in order to avoid jamming threats. For this reason, a variation of spatial multiplexing is proposed, namely, vSP4, which achieves not only high throughput but also a stable diversity gain upon the interference of a malicious jammer.

Real-time compression of analog-to-digital converter outputs

International Nuclear Information System (INIS)

Okumura, Haruhiko

1997-01-01

We describe a fast lossless data compression algorithm suitable for digitized data taken at regular time intervals, such as outputs from analog-to-digital converters (ADCs). It is designed on the assumptions that the present value can be predicted approximately from the past values, and that the distribution of the prediction error is approximately Gaussian with zero mean and small and slowly changing standard deviation. Unlike many offline compression tools such as LHA and gzip, our algorithm does not need future values to encode the present value. This property is important for real-time transmission of compressed data on the network. The algorithm is to be integrated into our data acquisition system for the Large Helical Device (LHD) experiments at the National Institute for Fusion Science (NIFS). (author)

Scintillation camera with improved output means

International Nuclear Information System (INIS)

Lange, K.; Wiesen, E.J.; Woronowicz, E.M.

1978-01-01

In a scintillation camera system, the output pulse signals from an array of photomultiplier tubes are coupled to the inputs of individual preamplifiers. The preamplifier output signals are coupled to circuitry for computing the x and y coordinates of the scintillations. A cathode ray oscilloscope is used to form an image corresponding with the pattern in which radiation is emitted by a body. Means for improving the uniformity and resolution of the scintillations are provided. The means comprise biasing means coupled to the outputs of selected preamplifiers so that output signals below a predetermined amplitude are not suppressed and signals falling within increasing ranges of amplitudes are increasingly suppressed. In effect, the biasing means make the preamplifiers non-linear for selected signal levels