Distributed reconfigurable control strategies for switching topology networked multi-agent systems.

Science.gov (United States)

Gallehdari, Z; Meskin, N; Khorasani, K

2017-11-01

In this paper, distributed control reconfiguration strategies for directed switching topology networked multi-agent systems are developed and investigated. The proposed control strategies are invoked when the agents are subject to actuator faults and while the available fault detection and isolation (FDI) modules provide inaccurate and unreliable information on the estimation of faults severities. Our proposed strategies will ensure that the agents reach a consensus while an upper bound on the team performance index is ensured and satisfied. Three types of actuator faults are considered, namely: the loss of effectiveness fault, the outage fault, and the stuck fault. By utilizing quadratic and convex hull (composite) Lyapunov functions, two cooperative and distributed recovery strategies are designed and provided to select the gains of the proposed control laws such that the team objectives are guaranteed. Our proposed reconfigurable control laws are applied to a team of autonomous underwater vehicles (AUVs) under directed switching topologies and subject to simultaneous actuator faults. Simulation results demonstrate the effectiveness of our proposed distributed reconfiguration control laws in compensating for the effects of sudden actuator faults and subject to fault diagnosis module uncertainties and unreliabilities. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Pilot Integration of HIV Screening and Healthcare Settings with Multi- Component Social Network and Partner Testing for HIV Detection.

Science.gov (United States)

Rentz, Michael F; Ruffner, Andrew H; Ancona, Rachel M; Hart, Kimberly W; Kues, John R; Barczak, Christopher M; Lindsell, Christopher J; Fichtenbaum, Carl J; Lyons, Michael S

2017-11-23

Healthcare settings screen broadly for HIV. Public health settings use social network and partner testing ("Transmission Network Targeting (TNT)") to select high-risk individuals based on their contacts. HIV screening and TNT systems are not integrated, and healthcare settings have not implemented TNT. The study aimed to evaluate pilot implementation of multi-component, multi-venue TNT in conjunction with HIV screening by a healthcare setting. Our urban, academic health center implemented a TNT program in collaboration with the local health department for five months during 2011. High-risk or HIV positive patients of the infectious diseases clinic and emergency department HIV screening program were recruited to access social and partner networks via compensated peer-referral, testing of companions present with them, and partner notification services. Contacts became the next-generation index cases in a snowball recruitment strategy. The pilot TNT program yielded 485 HIV tests for 482 individuals through eight generations of recruitment with five (1.0%; 95% CI = 0.4%, 2.3%) new diagnoses. Of these, 246 (51.0%; 95% CI = 46.6%, 55.5%) reported that they had not been tested for HIV within the last 12 months and 383 (79.5%; 95% CI = 75.7%, 82.9%) had not been tested by the existing ED screening program within the last five years. TNT complements population screening by more directly targeting high-risk individuals and by expanding the population receiving testing. Information from existing healthcare services could be used to seed TNT programs, or TNT could be implemented within healthcare settings. Research evaluating multi-component, multi-venue HIV detection is necessary to maximize complementary approaches while minimizing redundancy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

The design of multi-lead-compensators for stabilization and pole placement in double-integrator networks under saturation

NARCIS (Netherlands)

Wan, Yan; Roy, Sandip; Saberi, Ali; Stoorvogel, Antonie Arij

2009-01-01

We study decentralized controller design for stabilization and pole-placement, in a network of autonomous agents with double-integrator internal dynamics and arbitrary observation topology. We show that a simple multi-lead-compensator architecture, in particular one in which each agent uses a

Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

Science.gov (United States)

Gill, Joel C.; Malamud, Bruce D.

2016-08-01

This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability

Design considerations for energy efficient, resilient, multi-layer networks

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Hansen, Line Pyndt; Ruepp, Sarah Renée

2016-01-01

measures. In this complex problem, considerations such as client traffic granularity, applied grooming policies and multi-layer resiliency add even more complexity. A commercially available network planning tool is used to investigate the interplay between different methods for resilient capacity planning......This work investigates different network design considerations with respect to energy-efficiency, under green-field resilient multi-layer network deployment. The problem of energy efficient, reliable multi-layer network design is known to result in different trade-offs between key performance....... Switching off low-utilized transport links has been investigated via a pro-active re-routing applied during the network planning. Our analysis shows that design factors such as the applied survivability strategy and the applied planning method have higher impact on the key performance indicators compared...

Integrating pro-environmental behavior with transportation network modeling: User and system level strategies, implementation, and evaluation

Science.gov (United States)

Aziz, H. M. Abdul

compared with other groups. Next, we propose personal mobility carbon allowance (PMCA) scheme to reduce emissions from personal travel. PMCA is a market-based scheme that allocates carbon credits to users at no cost based on the emissions reduction goal of the system. Users can spend carbon credits for travel and a market place exists where users can buy or sell credits. This dissertation addresses two primary dimensions: the change in travel behavior of the users and the impact at network level in terms of travel time and emissions when PMCA is implemented. To understand this process, a real-time experimental game tool is developed where players are asked to make travel decisions within the carbon budget set by PMCA and they are allowed to trade carbon credits in a market modeled as a double auction game. Random parameter models are estimated to examine the impact of PMCA on short-term travel decisions. Further, to assess the impact at system level, a multi-class dynamic user equilibrium model is formulated that captures the travel behavior under PMCA scheme. The equivalent variational inequality problem is solved using projection method. Results indicate that PMCA scheme is able to reduce GHG emissions from transportation networks. Individuals with high value of travel time (VOTT) are less sensitive to PMCA scheme in context of work trips. High and medium income users are more likely to have non-work trips with lower carbon cost (higher travel time) to save carbon credits for work trips. Next, we focus on the strategies from the perspectives of system operators in transportation networks. Learning based signal control schemes are developed that can reduce emissions from signalized urban networks. The algorithms are implemented and tested in VISSIM micro simulator. Finally, an integrated emissions-traffic simulator framework is outlined that can be used to evaluate the effectiveness of the strategies. The integrated framework uses MOVES2010b as the emissions simulator. To

Multi-mode energy management strategy for fuel cell electric vehicles based on driving pattern identification using learning vector quantization neural network algorithm

Science.gov (United States)

Song, Ke; Li, Feiqiang; Hu, Xiao; He, Lin; Niu, Wenxu; Lu, Sihao; Zhang, Tong

2018-06-01

The development of fuel cell electric vehicles can to a certain extent alleviate worldwide energy and environmental issues. While a single energy management strategy cannot meet the complex road conditions of an actual vehicle, this article proposes a multi-mode energy management strategy for electric vehicles with a fuel cell range extender based on driving condition recognition technology, which contains a patterns recognizer and a multi-mode energy management controller. This paper introduces a learning vector quantization (LVQ) neural network to design the driving patterns recognizer according to a vehicle's driving information. This multi-mode strategy can automatically switch to the genetic algorithm optimized thermostat strategy under specific driving conditions in the light of the differences in condition recognition results. Simulation experiments were carried out based on the model's validity verification using a dynamometer test bench. Simulation results show that the proposed strategy can obtain better economic performance than the single-mode thermostat strategy under dynamic driving conditions.

Droop Control Design of Multi-VSC Systems for Offshore Networks to Integrate Wind Energy

Directory of Open Access Journals (Sweden)

Muhammad Raza

2016-10-01

Full Text Available This research envisages the droop control design of multi voltage source converter systems for offshore networks to integrate wind power plant with the grids. An offshore AC network is formulated by connecting several nearby wind power plants together with AC cables. The net energy in the network is transferred to onshore using voltage source high voltage direct current (VSC-HVDC transmissionsystems. In the proposed configuration, an offshore network is energized by more than one VSC-HVDC system, hereby providing redundancy to continue operation in case of failure in one of the HVDC transmission lines. The power distribution between VSC-HVDC systems is done using a droop control scheme. Frequency droop is implemented to share active power, and voltage droop is implemented to share reactive power. Furthermore, a method of calculating droop gains according to the contribution factor of each converter is presented. The system has been analyzed to evaluate the voltage profile of the network affected by the droop control. Nonlinear dynamic simulation has been performed for the verification of the control principle.

Collaborative-Hybrid Multi-Layer Network Control for Emerging Cyber-Infrastructures

Energy Technology Data Exchange (ETDEWEB)

Lehman, Tom [USC; Ghani, Nasir [UNM; Boyd, Eric [UCAID

2010-08-31

At a high level, there were four basic task areas identified for the Hybrid-MLN project. They are: o Multi-Layer, Multi-Domain, Control Plane Architecture and Implementation, including OSCARS layer2 and InterDomain Adaptation, Integration of LambdaStation and Terapaths with Layer2 dynamic provisioning, Control plane software release, Scheduling, AAA, security architecture, Network Virtualization architecture, Multi-Layer Network Architecture Framework Definition; o Heterogeneous DataPlane Testing; o Simulation; o Project Publications, Reports, and Presentations.

Principles and strategies for monitoring data collection integrity in a multi-site randomized clinical trial of a behavioral intervention.

Science.gov (United States)

Phillips-Salimi, Celeste R; Donovan Stickler, Molly A; Stegenga, Kristin; Lee, Melissa; Haase, Joan E

2011-08-01

Although treatment fidelity strategies for enhancing the integrity of behavioral interventions have been well described, little has been written about monitoring data collection integrity. This article describes the principles and strategies developed to monitor data collection integrity of the "Stories and Music for Adolescent/Young Adult Resilience During Transplant" study (R01NR008583, U10CA098543, and U10CA095861)-a multi-site Children's Oncology Group randomized clinical trial of a music therapy intervention for adolescents and young adults undergoing stem cell transplant. The principles and strategies outlined in this article provide one model for development and evaluation of a data collection integrity monitoring plan for behavioral interventions that may be adapted by investigators and may be useful to funding agencies and grant application reviewers in evaluating proposals. Copyright © 2011 Wiley Periodicals, Inc.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Multi-attribute integrated measurement of node importance in complex networks.

Science.gov (United States)

Wang, Shibo; Zhao, Jinlou

2015-11-01

The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

Content-Based Multi-Channel Network Coding Algorithm in the Millimeter-Wave Sensor Network

Directory of Open Access Journals (Sweden)

Kai Lin

2016-07-01

Full Text Available With the development of wireless technology, the widespread use of 5G is already an irreversible trend, and millimeter-wave sensor networks are becoming more and more common. However, due to the high degree of complexity and bandwidth bottlenecks, the millimeter-wave sensor network still faces numerous problems. In this paper, we propose a novel content-based multi-channel network coding algorithm, which uses the functions of data fusion, multi-channel and network coding to improve the data transmission; the algorithm is referred to as content-based multi-channel network coding (CMNC. The CMNC algorithm provides a fusion-driven model based on the Dempster-Shafer (D-S evidence theory to classify the sensor nodes into different classes according to the data content. By using the result of the classification, the CMNC algorithm also provides the channel assignment strategy and uses network coding to further improve the quality of data transmission in the millimeter-wave sensor network. Extensive simulations are carried out and compared to other methods. Our simulation results show that the proposed CMNC algorithm can effectively improve the quality of data transmission and has better performance than the compared methods.

Combating Forest Corruption: the Forest Integrity Network

NARCIS (Netherlands)

Gupta, A.; Siebert, U.

2004-01-01

This article describes the strategies and activities of the Forest Integrity Network. One of the most important underlying causes of forest degradation is corruption and related illegal logging. The Forest Integrity Network is a timely new initiative to combat forest corruption. Its approach is to

Distributed optimization-based control of multi-agent networks in complex environments

CERN Document Server

Zhu, Minghui

2015-01-01

This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Resea...

Optical network control plane for multi-domain networking

DEFF Research Database (Denmark)

Manolova, Anna Vasileva

This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic...... process are not enough for efficient TE in mesh multi-domain networks. Enhancing the protocol with multi-path dissemination capability, combined with the employment of an end-to-end TE metric proves to be a highly efficient solution. Simulation results show good performance characteristics of the proposed...... is not as essential for improved network performance as the length of the provided paths. Second, the issue of multi-domain survivability support is analyzed. An AS-disjoint paths is beneficial not only for resilience support, but also for facilitating adequate network reactions to changes in the network, which...

Load balancing in integrated optical wireless networks

DEFF Research Database (Denmark)

Yan, Ying; Dittmann, Lars; Wong, S-W.

2010-01-01

In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

Science.gov (United States)

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

Adaptive multi-resolution Modularity for detecting communities in networks

Science.gov (United States)

Chen, Shi; Wang, Zhi-Zhong; Bao, Mei-Hua; Tang, Liang; Zhou, Ji; Xiang, Ju; Li, Jian-Ming; Yi, Chen-He

2018-02-01

Community structure is a common topological property of complex networks, which attracted much attention from various fields. Optimizing quality functions for community structures is a kind of popular strategy for community detection, such as Modularity optimization. Here, we introduce a general definition of Modularity, by which several classical (multi-resolution) Modularity can be derived, and then propose a kind of adaptive (multi-resolution) Modularity that can combine the advantages of different Modularity. By applying the Modularity to various synthetic and real-world networks, we study the behaviors of the methods, showing the validity and advantages of the multi-resolution Modularity in community detection. The adaptive Modularity, as a kind of multi-resolution method, can naturally solve the first-type limit of Modularity and detect communities at different scales; it can quicken the disconnecting of communities and delay the breakup of communities in heterogeneous networks; and thus it is expected to generate the stable community structures in networks more effectively and have stronger tolerance against the second-type limit of Modularity.

Multi-granularity immunization strategy based on SIRS model in scale-free network

Science.gov (United States)

Nian, Fuzhong; Wang, Ke

2015-04-01

In this paper, a new immunization strategy was established to prevent the epidemic spreading based on the principle of "Multi-granularity" and "Pre-warning Mechanism", which send different pre-warning signal with the risk rank of the susceptible node to be infected. The pre-warning means there is a higher risk that the susceptible node is more likely to be infected. The multi-granularity means the susceptible node is linked with multi-infected nodes. In our model, the effect of the different situation of the multi-granularity immunizations is compared and different spreading rates are adopted to describe the epidemic behavior of nodes. In addition the threshold value of epidemic outbreak is investigated, which makes the result more convincing. The theoretical analysis and the simulations indicate that the proposed immunization strategy is effective and it is also economic and feasible.

Quantitative learning strategies based on word networks

Science.gov (United States)

Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

2018-02-01

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

OpenAIRE

Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

2014-01-01

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between t...

Using a multi-state Learning Community as an implementation strategy for immediate postpartum long-acting reversible contraception.

Science.gov (United States)

DeSisto, Carla L; Estrich, Cameron; Kroelinger, Charlan D; Goodman, David A; Pliska, Ellen; Mackie, Christine N; Waddell, Lisa F; Rankin, Kristin M

2017-11-21

educational meetings, facilitation, promote network weaving, provide ongoing consultation, and distribute educational materials. Convening a multi-state learning collaborative is a promising approach for facilitating the implementation of new reimbursement policies for evidence-based practices complicated by systems challenges. By integrating several implementation strategies, the Learning Community serves as a meta-strategy for supporting implementation.

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.

Layered Multi-mode Optimal Control Strategy for Multi-MW Wind Turbine

Institute of Scientific and Technical Information of China (English)

KONG Yi-gang; WANG Zhi-xin

2008-01-01

The control strategy is one of the most important renewable technology, and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch (VS-VP) technology. The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy. But the power generated by wind turbine changes rapidly because of the centinuous fluctuation of wind speed and direction. At the same time, wind energy conversion systems are of high order, time delays and strong nonlinear characteristics because of many uncertain factors. Based on analyzing the all dynamic processes of wind turbine, a kind of layered multi-mode optimal control strategy is presented which is that three control strategies: bang-bang, fuzzy and adaptive proportienai integral derivative (PID) are adopted according to different stages and expected performance of wind turbine to capture optimum wind power, compensate the nonlinearity and improve the wind turbine performance at low, rated and high wind speed.

Relay-aided multi-cell broadcasting with random network coding

DEFF Research Database (Denmark)

Lu, Lu; Sun, Fan; Xiao, Ming

2010-01-01

We investigate a relay-aided multi-cell broadcasting system using random network codes, where the focus is on devising efficient scheduling algorithms between relay and base stations. Two scheduling algorithms are proposed based on different feedback strategies; namely, a one-step scheduling...

QoE-based transmission strategies for multi-user wireless information and power transfer

Directory of Open Access Journals (Sweden)

Taehun Jung

2015-12-01

Full Text Available One solution to the problem of supplying energy to wireless networks is wireless power transfer. One such technology–electromagnetic radiation enabled wireless power transfer–will change traditional wireless networks. In this paper, we investigate a transmission strategy for multi-user wireless information and power transfer. We consider a multi-user multiple-input multiple-output (MIMO channel that includes one base station (BS and two user terminals (UT consisting of one energy harvesting (EH receiver and one information decoding (ID receiver. Our system provides transmission strategies that can be executed and implemented in practical scenarios. The paper then analyzes the rate–energy (R–E pair of our strategies and compares them to those of the theoretical optimal strategy. We furthermore propose a QoE-based mode selection algorithm by mapping the R–E pair to the utility functions.

Product bundling, the key to a successful multi-utility strategy; Buendelung: Der Schluessel zu einer erfolgreichen Multi Utility-Strategie

Energy Technology Data Exchange (ETDEWEB)

Laker, M.; Nigge, K.M.; Wuebker, G. [Simon, Kucher und Partner Strategy and Marketing Consultants GmbH, Berlin (Germany)

2002-04-01

The article explains essential aspects of successful multi-utility management strategies for local utilities. Product bundling and the creation of incentives for enhancing the consumers' propensity to conclude multi-utility contracts, as e.g. pricing policy and the range of services that can be offered in a package are discussed. (orig./CB) [German] Das Thema Multi Utility, d.h. die Integration von Strom, Erdgas, Wasser, Entsorgung und Dienstleistungen wird ausfuehrlich diskutiert. Es muessen vielmehr Anreize dafuer geschaffen werden, dass die Kunden die Komplettangebote auch wahrnehmen. Dies ist eine Frage der Produkt- und Preisgestaltung. Buendelung ist das ideale Instrument zur Schaffung solcher Anreize. (orig./CB)

Improving the Reliability of Network Metrics in Structural Brain Networks by Integrating Different Network Weighting Strategies into a Single Graph

Directory of Open Access Journals (Sweden)

Stavros I. Dimitriadis

2017-12-01

Full Text Available Structural brain networks estimated from diffusion MRI (dMRI via tractography have been widely studied in healthy controls and patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost fully-weighted. Here, we scanned five healthy participants five times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROI from the Automated Anatomical Labeling (AAL template. The edges were weighted according to nine different methods. We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an Integrated Weighted Structural Brain Network (ISWBN. Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of: (a intra-class correlation coefficient (ICC of well-known network metrics, both node-wise and per network level; and (b the recognition accuracy of each subject compared to the remainder of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject, after first applying our proposed topological filtering scheme. Based on a threshold where the network level ICC should be >0.90, our findings revealed that six out of nine NWS lead to unreliable results at the network level, while all nine NWS were unreliable at the node level. In comparison, our proposed ISWBN performed as well as the best performing individual NWS at the network level, and the ICC was higher compared to all individual NWS at the node

Bi-objective integrating sustainable order allocation and sustainable supply chain network strategic design with stochastic demand using a novel robust hybrid multi-objective metaheuristic

DEFF Research Database (Denmark)

Govindan, Kannan; Jafarian, Ahmad; Nourbakhsh, Vahid

2015-01-01

simultaneously considering the sustainable OAP in the sustainable SCND as a strategic decision. The proposed supply chain network is composed of five echelons including suppliers classified in different classes, plants, distribution centers that dispatch products via two different ways, direct shipment......, a novel multi-objective hybrid approach called MOHEV with two strategies for its best particle selection procedure (BPSP), minimum distance, and crowding distance is proposed. MOHEV is constructed through hybridization of two multi-objective algorithms, namely the adapted multi-objective electromagnetism...

An integrated environment monitoring system for underground coal mines--Wireless Sensor Network subsystem with multi-parameter monitoring.

Science.gov (United States)

Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

2014-07-21

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

Science.gov (United States)

Zhang, Yu; Yang, Wei; Han, Dongsheng; Kim, Young-Il

2014-01-01

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected. PMID:25051037

An Integrated Environment Monitoring System for Underground Coal Mines—Wireless Sensor Network Subsystem with Multi-Parameter Monitoring

Directory of Open Access Journals (Sweden)

Yu Zhang

2014-07-01

Full Text Available Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs. We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

Hyper Hospital on the satellite multi-media network.

Science.gov (United States)

Yamaguchi, T

1997-01-01

We have been developing the Hyper Hospital, a network based VR mediated medical care system. The Hyper Hospital is composed of two seamlessly integrated environments, that is, the virtual and the real worlds. Of them, its virtual environment expands the conventional medical care system using the virtual reality technology as a principal human interface and a collaboration tool, in the present study, an attempt to extend the Hyper Hospital system to various modalities of communication network is reported. A satellite communication based multi-media network using Internet protocols with the WWW interface is used. Data transmission rate and other performances were measured under various conditions and the satellite network was shown to be suitable to the Hyper Hospital network.

The integration of weighted gene association networks based on information entropy.

Science.gov (United States)

Yang, Fan; Wu, Duzhi; Lin, Limei; Yang, Jian; Yang, Tinghong; Zhao, Jing

2017-01-01

Constructing genome scale weighted gene association networks (WGAN) from multiple data sources is one of research hot spots in systems biology. In this paper, we employ information entropy to describe the uncertain degree of gene-gene links and propose a strategy for data integration of weighted networks. We use this method to integrate four existing human weighted gene association networks and construct a much larger WGAN, which includes richer biology information while still keeps high functional relevance between linked gene pairs. The new WGAN shows satisfactory performance in disease gene prediction, which suggests the reliability of our integration strategy. Compared with existing integration methods, our method takes the advantage of the inherent characteristics of the component networks and pays less attention to the biology background of the data. It can make full use of existing biological networks with low computational effort.

Control strategies for power distribution networks with electric vehicles integration

DEFF Research Database (Denmark)

Hu, Junjie

of electrical energy. A smart grid can also be dened as an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both - in order to eciently deliver sustainable, economic and secure electricity supplies. This thesis focuses...... of the ii market. To build a complete solution for integration of EVs into the distribution network, a price coordinated hierarchical scheduling system is proposed which can well characterize the involved actors in the smart grid. With this system, we demonstrate that it is possible to schedule the charging......Demand side resources, like electric vehicles (EVs), can become integral parts of a smart grids because instead of just consuming power they are capable of providing valuable services to power systems. EVs can be used to balance the intermittent renewable energy resources such as wind and solar...

A mathematical model for optimization of an integrated network logistic design

Directory of Open Access Journals (Sweden)

Lida Tafaghodi

2011-10-01

Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.

Energetic Performance of Service-oriented Multi-radio Networks: Issues and Perspectives

OpenAIRE

Caporuscio , Mauro; Charlet , Damien; Issarny , Valérie; Navarra , Alfredo

2006-01-01

Wireless devices now hold multiple radio interfaces, allowing to switch from one network to another according to required connectivity and related quality. Still, the selection of the best radio interface for a specific connection is under the responsibility of the end-user in most cases. Integrated multi-radio network management so as to improve the overall performance of the network(s) has led to a number of research efforts over the last few years. However, several challenges remain due to...

Ubiquitous Integrity via Network Integration and Parallelism—Sustaining Pedestrian/Bike Urbanism

Directory of Open Access Journals (Sweden)

Li-Yen Hsu

2013-08-01

Full Text Available Nowadays, due to the concern regarding environmental issues, establishing pedestrian/bike friendly urbanism is widely encouraged. To promote safety-assured, mobile communication environments, efficient, reliable maintenance, and information integrity need to be designed, especially in highly possibly interfered places. For busy traffic areas, regular degree-3 dedicated short range communication (DSRC networks are safety and information featured with availability, reliability, and maintainability in paths of multi-lanes. For sparsely populated areas, probes of wireless sensors are rational, especially if sensor nodes can be organized to enhance security, reliability, and flexibility. Applying alternative network topologies, such as spider-webs, generalized honeycomb tori, and cube-connected cycles, for comparing and analyzing is proposed in DSRC and cellular communications to enhance integrity in communications.

Multi-threshold white matter structural networks fusion for accurate diagnosis of Tourette syndrome children

Science.gov (United States)

Wen, Hongwei; Liu, Yue; Wang, Shengpei; Li, Zuoyong; Zhang, Jishui; Peng, Yun; He, Huiguang

2017-03-01

Tourette syndrome (TS) is a childhood-onset neurobehavioral disorder. To date, TS is still misdiagnosed due to its varied presentation and lacking of obvious clinical symptoms. Therefore, studies of objective imaging biomarkers are of great importance for early TS diagnosis. As tic generation has been linked to disturbed structural networks, and many efforts have been made recently to investigate brain functional or structural networks using machine learning methods, for the purpose of disease diagnosis. However, few studies were related to TS and some drawbacks still existed in them. Therefore, we propose a novel classification framework integrating a multi-threshold strategy and a network fusion scheme to address the preexisting drawbacks. Here we used diffusion MRI probabilistic tractography to construct the structural networks of 44 TS children and 48 healthy children. We ameliorated the similarity network fusion algorithm specially to fuse the multi-threshold structural networks. Graph theoretical analysis was then implemented, and nodal degree, nodal efficiency and nodal betweenness centrality were selected as features. Finally, support vector machine recursive feature extraction (SVM-RFE) algorithm was used for feature selection, and then optimal features are fed into SVM to automatically discriminate TS children from controls. We achieved a high accuracy of 89.13% evaluated by a nested cross validation, demonstrated the superior performance of our framework over other comparison methods. The involved discriminative regions for classification primarily located in the basal ganglia and frontal cortico-cortical networks, all highly related to the pathology of TS. Together, our study may provide potential neuroimaging biomarkers for early-stage TS diagnosis.

A novel power control strategy of Modular Multi-level Converter in HVDC-AC hybrid transmission systems for passive networks

DEFF Research Database (Denmark)

Hu, Zhenda; Wu, Rui; Yang, Xiaodong

2014-01-01

With the development of High Voltage DC Transmission (HVDC) technology, there will be more and more HVDC-AC hybrid transmission system in the world. A basic challenge in HVDC-AC hybrid transmission systems is to optimize the power sharing between DC and AC lines, which become more severe when sup...... control strategy of Modular Multi-level Converter in VSC-HVDC, which can optimize converter output power according to passive network loading variation. Proposal method is studied with a case study of a VSC-HVDC AC hybrid project by PSCAD/EMTDC simulations....

Design of energy efficient optical networks with software enabled integrated control plane

DEFF Research Database (Denmark)

Wang, Jiayuan; Yan, Ying; Dittmann, Lars

2015-01-01

energy consumption by proposing a new integrated control plane structure utilising Software Defined Networking technologies. The integrated control plane increases the efficiencies of exchanging control information across different network domains, while introducing new possibilities to the routing...... methods and the control over quality of service (QoS). The structure is defined as an overlay generalised multi-protocol label switching (GMPLS) control model. With the defined structure, the integrated control plane is able to gather information from different domains (i.e. optical core network......'s) routing behaviours. With the flexibility of the routing structure, results show that the energy efficiency of the network can be improved without compromising the QoS for delay/blocking sensitive services....

Wireless Multi Hop Access Networks and Protocols

OpenAIRE

Nilsson Plymoth, Anders

2007-01-01

As more and more applications and services in our society now depend on the Internet, it is important that dynamically deployed wireless multi hop networks are able to gain access to the Internet and other infrastructure networks and services. This thesis proposes and evaluates solutions for providing multi hop Internet Access. It investigates how ad hoc networks can be combined with wireless and mesh networks in order to create wireless multi hop access networks. When several access points t...

Integrated Network Analysis and Effective Tools in Plant Systems Biology

Directory of Open Access Journals (Sweden)

Atsushi eFukushima

2014-11-01

Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks

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Bishnu P. Bhattarai

2017-01-01

Full Text Available This paper presents a multi-timescale control strategy to deploy electric vehicle (EV demand flexibility for simultaneously providing power balancing, grid congestion management, and economic benefits to participating actors. First, an EV charging problem is investigated from consumer, aggregator, and distribution system operator’s perspectives. A hierarchical control architecture (HCA comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating multi-time scale controls that work from a day-ahead scheduling up to real-time adaptive control. The performance of the developed method is investigated with high EV penetration in a typical residential distribution grid. The simulation results demonstrate that HCA efficiently utilizes demand flexibility stemming from EVs to solve grid unbalancing and congestions with simultaneous maximization of economic benefits to the participating actors. This is ensured by enabling EV participation in day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to five times the cost they were paying without control.

Competitive Supply Chain Network Design Considering Marketing Strategies: A Hybrid Metaheuristic Algorithm

Directory of Open Access Journals (Sweden)

Ali Akbar Hasani

2016-11-01

Full Text Available In this paper, a comprehensive model is proposed to design a network for multi-period, multi-echelon, and multi-product inventory controlled the supply chain. Various marketing strategies and guerrilla marketing approaches are considered in the design process under the static competition condition. The goal of the proposed model is to efficiently respond to the customers’ demands in the presence of the pre-existing competitors and the price inelasticity of demands. The proposed optimization model considers multiple objectives that incorporate both market share and total profit of the considered supply chain network, simultaneously. To tackle the proposed multi-objective mixed-integer nonlinear programming model, an efficient hybrid meta-heuristic algorithm is developed that incorporates a Taguchi-based non-dominated sorting genetic algorithm-II and a particle swarm optimization. A variable neighborhood decomposition search is applied to enhance a local search process of the proposed hybrid solution algorithm. Computational results illustrate that the proposed model and solution algorithm are notably efficient in dealing with the competitive pressure by adopting the proper marketing strategies.

Load Situation Awareness Design for Integration in Multi-Energy System

DEFF Research Database (Denmark)

Cai, Hanmin; You, Shi; Bindner, Henrik W.

2017-01-01

Renewable Energy Sources (RESs) have been penetrating in power system at a staggering pace in recent years. Their intermittent nature is, however, posing great threat to system operation. Recently, active load management has been suggested as a tool to counteract these side effects. In multi......-energy system, thermal load management will benefit not only electric network but also district heating network. Electric heater will be the main focus of this paper as a common thermal load. A situation awareness framework for its integration into electric and district heating network will be proposed...

Reconfigurable microfluidic hanging drop network for multi-tissue interaction and analysis.

Science.gov (United States)

Frey, Olivier; Misun, Patrick M; Fluri, David A; Hengstler, Jan G; Hierlemann, Andreas

2014-06-30

Integration of multiple three-dimensional microtissues into microfluidic networks enables new insights in how different organs or tissues of an organism interact. Here, we present a platform that extends the hanging-drop technology, used for multi-cellular spheroid formation, to multifunctional complex microfluidic networks. Engineered as completely open, 'hanging' microfluidic system at the bottom of a substrate, the platform features high flexibility in microtissue arrangements and interconnections, while fabrication is simple and operation robust. Multiple spheroids of different cell types are formed in parallel on the same platform; the different tissues are then connected in physiological order for multi-tissue experiments through reconfiguration of the fluidic network. Liquid flow is precisely controlled through the hanging drops, which enable nutrient supply, substance dosage and inter-organ metabolic communication. The possibility to perform parallelized microtissue formation on the same chip that is subsequently used for complex multi-tissue experiments renders the developed platform a promising technology for 'body-on-a-chip'-related research.

Control Systems Cyber Security:Defense in Depth Strategies

Energy Technology Data Exchange (ETDEWEB)

David Kuipers; Mark Fabro

2006-05-01

Information infrastructures across many public and private domains share several common attributes regarding IT deployments and data communications. This is particularly true in the control systems domain. A majority of the systems use robust architectures to enhance business and reduce costs by increasing the integration of external, business, and control system networks. However, multi-network integration strategies often lead to vulnerabilities that greatly reduce the security of an organization, and can expose mission-critical control systems to cyber threats. This document provides guidance and direction for developing ‘defense-in-depth’ strategies for organizations that use control system networks while maintaining a multi-tier information architecture that requires: Maintenance of various field devices, telemetry collection, and/or industrial-level process systems Access to facilities via remote data link or modem Public facing services for customer or corporate operations A robust business environment that requires connections among the control system domain, the external Internet, and other peer organizations.

Clinical multi-omics strategies for the effective cancer management.

Science.gov (United States)

Yoo, Byong Chul; Kim, Kyung-Hee; Woo, Sang Myung; Myung, Jae Kyung

2017-08-15

Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis. In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles.

Science.gov (United States)

Fleury, Marie-Josée; Grenier, Guy; Vallée, Catherine; Aubé, Denise; Farand, Lambert

2017-03-10

This study evaluates implementation of the Quebec Mental Health Reform (2005-2015), which promoted the development of integrated service networks, in 11 local service networks organized into four territorial groups according to socio-demographic characteristics and mental health services offered. Data were collected from documents concerning networks; structured questionnaires completed by 90 managers and by 16 respondent-psychiatrists; and semi-structured interviews with 102 network stakeholders. Factors associated with implementation and integration were organized according to: 1) reform characteristics; 2) implementation context; 3) organizational characteristics; and 4) integration strategies. While local networks were in a process of development and expansion, none were fully integrated at the time of the study. Facilitators and barriers to implementation and integration were primarily associated with organizational characteristics. Integration was best achieved in larger networks including a general hospital with a psychiatric department, followed by networks with a psychiatric hospital. Formalized integration strategies such as service agreements, liaison officers, and joint training reduced some barriers to implementation in networks experiencing less favourable conditions. Strategies for the implementation of healthcare reform and integrated service networks should include sustained support and training in best-practices, adequate performance indicators and resources, formalized integration strategies to improve network coordination and suitable initiatives to promote staff retention.

Innovating Rural Tourism Targeting Poverty Alleviation through a Multi-Industries Integration Network: the Case of Zhuanshui Village, Anhui Province, China

Directory of Open Access Journals (Sweden)

Nanping Feng

2018-06-01

Full Text Available For an impoverished area to employ rural tourism (RT as an avenue of poverty alleviation, there are two main challenges: building competitiveness with a very limited endowed resource base, and targeting the poor who generally lack financial capital or key capabilities as the main beneficiaries. With a case of Zhuanshui in China, an impoverished village without prominent tourism resource endowment, this paper has shown that the two challenges can be met through an innovation to construct a multi-industries integration network. This paper explores the development of the network, examines its characteristics, and analyzes its operation mechanisms. Results indicate that (1 the common objective of poverty alleviation and the same fundamental resource, combine RT and its extension industries tightly into an integration network; (2 sufficient evidence has been found for the embeddedness, endogeneity and empowerment of the network, but for empowerment, the poor’s participation is just the first stage to make appropriate decisions about the development due to their inadequate capabilities; and (3 vision developing, demonstration driving and centralized decentralization governance are three vital operational mechanisms to encourage the participation and collaboration of stakeholders. We also discussed the possible challenges for sustainability, being replicability of established competitive advantages, temporality of the major leader, and potential environmental degradation.

Intelligent control and maintenance of management integrated system based on multi-agents for coal preparation plant

Energy Technology Data Exchange (ETDEWEB)

Meng, F.; Wang, Y. [China University of Mining and technology, Xuzhou (China). School of Information and Electrical Engineering

2006-06-15

This paper discusses the progress of computer integrated processing (CIPS) of coal preparation and then presents an intelligence controlled production process, device-maintenance and production-management system of coal preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing a distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implementation methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption. 17 refs., 4 figs.

Some Issues of the Paradigm of Multi-learning Machine - Modular Neural Networks

DEFF Research Database (Denmark)

Wang, Pan; Feng, Shuai; Fan, Zhun

2009-01-01

This paper addresses some issues on the weighted linear integration of modular neural networks (MNN: a paradigm of hybrid multi-learning machines). First, from the general meaning of variable weights and variable elements synthesis, three basic kinds of integrated models are discussed...... a general form while the corresponding computational algorithms are described briefly. The authors present a new training algorithm of sub-networks named “'Expert in one thing and good at many' (EOGM).” In this algorithm, every sub-network is trained on a primary dataset with some of its near neighbors...... as the accessorial datasets. Simulated results with a kind of dynamic integration methods show the effectiveness of these algorithms, where the performance of the algorithm with EOGM is better than that of the algorithm with a common training method....

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

Science.gov (United States)

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

2011-01-01

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

Design and implementation of space physics multi-model application integration based on web

Science.gov (United States)

Jiang, Wenping; Zou, Ziming

With the development of research on space environment and space science, how to develop network online computing environment of space weather, space environment and space physics models for Chinese scientific community is becoming more and more important in recent years. Currently, There are two software modes on space physics multi-model application integrated system (SPMAIS) such as C/S and B/S. the C/S mode which is traditional and stand-alone, demands a team or workshop from many disciplines and specialties to build their own multi-model application integrated system, that requires the client must be deployed in different physical regions when user visits the integrated system. Thus, this requirement brings two shortcomings: reducing the efficiency of researchers who use the models to compute; inconvenience of accessing the data. Therefore, it is necessary to create a shared network resource access environment which could help users to visit the computing resources of space physics models through the terminal quickly for conducting space science research and forecasting spatial environment. The SPMAIS develops high-performance, first-principles in B/S mode based on computational models of the space environment and uses these models to predict "Space Weather", to understand space mission data and to further our understanding of the solar system. the main goal of space physics multi-model application integration system (SPMAIS) is to provide an easily and convenient user-driven online models operating environment. up to now, the SPMAIS have contained dozens of space environment models , including international AP8/AE8 IGRF T96 models and solar proton prediction model geomagnetic transmission model etc. which are developed by Chinese scientists. another function of SPMAIS is to integrate space observation data sets which offers input data for models online high-speed computing. In this paper, service-oriented architecture (SOA) concept that divides system into

Integration of multi-technology on oil spill emergency preparedness.

Science.gov (United States)

Liao, Zhenliang; Hannam, Phillip M; Xia, Xiaowei; Zhao, Tingting

2012-10-01

This paper focuses on the integration of technologies including Case-Based Reasoning (CBR), Genetic Algorithm (GA) and Artificial Neural Network (ANN) for establishing emergency preparedness for oil spill accidents. In CBR, the Frame method is used to define case representation, and the HEOM (Heterogeneous Euclidean-Overlap Metric) is improved to define the similarity of case properties. In GA, we introduce an Improved Genetic Algorithm (IGA) that achieves case adaptation, in which technologies include the Multi-Parameter Cascade Code method, the Small Section method for generation of an initial population, the Multi-Factor Integrated Fitness Function, and Niche technology for genetic operations including selection, crossover, and mutation. In ANN, a modified back-propagation algorithm is employed to train the algorithm to quickly improve system preparedness. Through the analysis of 32 fabricated oil spill cases, an oil spill emergency preparedness system based on the integration of CBR, GA and ANN is introduced. In particular, the development of ANN is presented and analyzed. The paper also discusses the efficacy of our integration approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

Science.gov (United States)

Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

2015-07-01

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analysis of Probability of Non-zero Secrecy Capacity for Multi-hop Networks in Presence of Hardware Impairments over Nakagami-m Fading Channels

Directory of Open Access Journals (Sweden)

T.-T. Phu

2016-12-01

Full Text Available In this paper, we evaluate probability of non-zero secrecy capacity of multi-hop relay networks over Nakagami-m fading channels in presence of hardware impairments. In the considered protocol, a source attempts to transmit its data to a destination by using multi-hop randomize-and-forward (RF strategy. The data transmitted by the source and relays are overheard by an eavesdropper. For performance evaluation, we derive exact expressions of probability of non-zero secrecy capacity (PoNSC, which are expressed by sums of infinite series of exponential functions and exponential integral functions. We then perform Monte Carlo simulations to verify the theoretical analysis.

A multi-agent system architecture for sensor networks.

Science.gov (United States)

Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

2009-01-01

The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

Multi-Model Prediction for Demand Forecast in Water Distribution Networks

Directory of Open Access Journals (Sweden)

Rodrigo Lopez Farias

2018-03-01

Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.

Aerodynamic multi-objective integrated optimization based on principal component analysis

Directory of Open Access Journals (Sweden)

Jiangtao HUANG

2017-08-01

Full Text Available Based on improved multi-objective particle swarm optimization (MOPSO algorithm with principal component analysis (PCA methodology, an efficient high-dimension multi-objective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency, the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil, and the proposed method is integrated into aircraft multi-disciplinary design (AMDEsign platform, which contains aerodynamics, stealth and structure weight analysis and optimization module. Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.

ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

Science.gov (United States)

Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

2015-01-01

Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

Multi-GNSS PPP-RTK: From Large- to Small-Scale Networks

Directory of Open Access Journals (Sweden)

Nandakumaran Nadarajah

2018-04-01

Full Text Available Precise point positioning (PPP and its integer ambiguity resolution-enabled variant, PPP-RTK (real-time kinematic, can benefit enormously from the integration of multiple global navigation satellite systems (GNSS. In such a multi-GNSS landscape, the positioning convergence time is expected to be reduced considerably as compared to the one obtained by a single-GNSS setup. It is therefore the goal of the present contribution to provide numerical insights into the role taken by the multi-GNSS integration in delivering fast and high-precision positioning solutions (sub-decimeter and centimeter levels using PPP-RTK. To that end, we employ the Curtin PPP-RTK platform and process data-sets of GPS, BeiDou Navigation Satellite System (BDS and Galileo in stand-alone and combined forms. The data-sets are collected by various receiver types, ranging from high-end multi-frequency geodetic receivers to low-cost single-frequency mass-market receivers. The corresponding stations form a large-scale (Australia-wide network as well as a small-scale network with inter-station distances less than 30 km. In case of the Australia-wide GPS-only ambiguity-float setup, 90% of the horizontal positioning errors (kinematic mode are shown to become less than five centimeters after 103 min. The stated required time is reduced to 66 min for the corresponding GPS + BDS + Galieo setup. The time is further reduced to 15 min by applying single-receiver ambiguity resolution. The outcomes are supported by the positioning results of the small-scale network.

Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

Science.gov (United States)

Lin, Yi-Kuei; Yeh, Cheng-Ta

2013-05-01

From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.

A review on machine learning principles for multi-view biological data integration.

Science.gov (United States)

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

A Model of Building Multi-campus Library Education Ｒesourses Network Based on MPLS VPN

Directory of Open Access Journals (Sweden)

WANG Guang-ze

2017-06-01

Full Text Available For the problems of most merged schools that it is difficulty to integrate the original library education resources network due to scattered campus，and it is inconvenient to use teaching resources for outwork teachers and students，this paper puts forward the technology of using multi － protocol label switching virtual private network ( MPLS VPN to integrate education resources in multi － campus library． Through setting up security tunnel between the library education subnet，MPLS VPN ensure the safety of data transmission，so as achieve the goal of resource integration，optimization and share，implements the exclusive use for the electronic teaching business of library． Experimental data show that this model has advantages compared with traditional VPN networking．

Coordinated Control of Multi-terminal DC Grid for Wind Power Integration

DEFF Research Database (Denmark)

Hao, Yu; Zhao, Haoran; Wu, Qiuwei

2016-01-01

Multi-terminal HVDC (MTDC) technology using voltage source converter (VSC) is a good option for wind power integration. Compared with point to point DC connection, MTDC provide better controllability based on different control strategies. In this paper, proportional-integral (PI) controllers...... with tuned PI parameters are designed to coordinate DC flow among the DC grid with good dynamic performance. In order to overcome the disadvantages of the conventional PI control, a simple adaptive PI control strategy is proposed based on the system transfer function. Case studies were conducted with PowerFactory....

USING DEMATEL-ANP INTEGRATED APPROACH FOR DECIDING PRODUCTION STRATEGY FOR A PRODUCTION LINE

Directory of Open Access Journals (Sweden)

Sinan APAK

2017-09-01

Full Text Available Production planning includes push, pull and hybrid production systems that production firms determine their production strategies according to many variables before starting production. The administration of this process requires experience and time. The intensity of rivalry makes this kind of decision processes important, because no firm has the luxury to waste time and to make a wrong decision. In order to solve this problem, research proposes to use integrated decision-making trial and evaluation laboratory (DEMATEL and analytic network process (ANP together which are methods of multi-criteria decision-making models. The process being used to establish which options are found to be most acceptable for operations managers has been demonstrated how applicable it is by using the generated model in automotive industry.

Learning and innovative elements of strategy adoption rules expand cooperative network topologies.

Science.gov (United States)

Wang, Shijun; Szalay, Máté S; Zhang, Changshui; Csermely, Peter

2008-04-09

Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoner's Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.

INTEGRATED METHODOLOGY FOR PRODUCT PLANNING USING MULTI CRITERIA ANALYSIS

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Tarun Soota

2016-09-01

Full Text Available Integrated approach to multi-criteria decision problems is proposed using quality function deployment and analytical network process. The objective of the work is to rationalize and improve the method of analyzing and interpreting customer needs and technical requirements. The methodology is used to determine, prioritize engineering requirements based on customer needs for development of best product. Framework allows decision maker to decompose a complex problem in a hierarchical structure to show relationship between objective and criteria. Multi-criteria decision modeling is used for extending the hierarchy process to both dependence and feedback. A case study on bikes is presented for the proposed model.

MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

Synthesis and Design of Integrated Process and Water Networks

DEFF Research Database (Denmark)

Handani, Zainatul B.; Quaglia, Alberto; Gani, Rafiqul

2015-01-01

This work presents the development of a systematic framework for a simultaneous synthesis and design of process and water networks using the superstructure-based optimization approach. In this framework, a new superstructure combining both networks is developed by attempting to consider all...... possible options with respect to the topology of the process and water networks, leading to Mixed Integer Non Linear Programming (MINLP) problem. A solution strategy to solve the multi-network problem accounts explicitly the interactions between the networks by selecting suitable technologies in order...... to transform raw materials into products and produce clean water to be reused in the process at the early stage of design. Since the connection between the process network and the wastewater treatment network is not a straight forward connection, a new converter interval is introduced in order to convert...

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.

Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management

International Nuclear Information System (INIS)

Catrinu, M.D.; Nordgard, D.E.

2011-01-01

Asset managers in electricity distribution companies generally recognize the need and the challenge of adding structure and a higher degree of formal analysis into the increasingly complex asset management decisions. This implies improving the present asset management practice by making the best use of the available data and expert knowledge and by adopting new methods for risk analysis and decision support and nevertheless better ways to document the decisions made. This paper discusses methods for integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management. The focus is on how to include the different company objectives and risk analyses into a structured decision framework when deciding how to handle the physical assets of the electricity distribution network. This paper presents an illustrative example of decision support for maintenance and reinvestment strategies based, using expert knowledge, simplified risk analyses and multi-criteria decision analysis under uncertainty.

Exploring the dynamics of formal and informal networks in complex multi-team development projects

DEFF Research Database (Denmark)

Kratzer, J.; Gemuenden, H. G.; Lettl, Christopher

2007-01-01

The increasing number of complex multi-team projects and the scarcity of knowledge about how to run them successfully, create a need for systematic empirical studies. We attempt to lessen this empirical gap by examining the overlap and structure of formally ascribed design interfaces and informal...... communication networks between participating teams in two complex multi-team projects in the space industry. We study the two projects longitudinally throughout the design and integration phases of product development. There are three major findings. First, formally ascribed design interfaces and informal...... communication networks overlap only marginally. Second, the structure of informal communication remains largely stable in the transition from the design to the integration phase. The third and most intriguing finding is that the weak overlap between formally ascribed design interfaces and the informal...

Unveiling network-based functional features through integration of gene expression into protein networks.

Science.gov (United States)

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Poster: A Software-Defined Multi-Camera Network

OpenAIRE

Chen, Po-Yen; Chen, Chien; Selvaraj, Parthiban; Claesen, Luc

2016-01-01

The widespread popularity of OpenFlow leads to a significant increase in the number of applications developed in SoftwareDefined Networking (SDN). In this work, we propose the architecture of a Software-Defined Multi-Camera Network consisting of small, flexible, economic, and programmable cameras which combine the functions of the processor, switch, and camera. A Software-Defined Multi-Camera Network can effectively reduce the overall network bandwidth and reduce a large amount of the Capex a...

A Multi-Agent System Architecture for Sensor Networks

Directory of Open Access Journals (Sweden)

María Guijarro

2009-12-01

Full Text Available The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work.

Improved Road-Network-Flow Control Strategy Based on Macroscopic Fundamental Diagrams and Queuing Length in Connected-Vehicle Network

Directory of Open Access Journals (Sweden)

Xiaohui Lin

2017-01-01

Full Text Available Connected-vehicles network provides opportunities and conditions for improving traffic signal control, and macroscopic fundamental diagrams (MFD can control the road network at the macrolevel effectively. This paper integrated proposed real-time access to the number of mobile vehicles and the maximum road queuing length in the Connected-vehicles network. Moreover, when implementing a simple control strategy to limit the boundary flow of a road network based on MFD, we determined whether the maximum queuing length of each boundary section exceeds the road-safety queuing length in real-time calculations and timely adjusted the road-network influx rate to avoid the overflow phenomenon in the boundary section. We established a road-network microtraffic simulation model in VISSIM software taking a district as the experimental area, determined MFD of the region based on the number of mobile vehicles, and weighted traffic volume of the road network. When the road network was tending to saturate, we implemented a simple control strategy and our algorithm limits the boundary flow. Finally, we compared the traffic signal control indicators with three strategies: (1 no control strategy, (2 boundary control, and (3 boundary control with limiting queue strategy. The results show that our proposed algorithm is better than the other two.

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

Multi-step-prediction of chaotic time series based on co-evolutionary recurrent neural network

International Nuclear Information System (INIS)

Ma Qianli; Zheng Qilun; Peng Hong; Qin Jiangwei; Zhong Tanwei

2008-01-01

This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability of recurrent neural network to incorporate past experience due to internal recurrence. The effectiveness of CERNN is evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey-Glass series and real-world sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic time series

NASA Integrated Network COOP

Science.gov (United States)

Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

2012-01-01

Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

Directory of Open Access Journals (Sweden)

Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Functional brain networks underlying detection and integration of disconfirmatory evidence.

Science.gov (United States)

Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

2015-05-15

.g., 17s after trial onset) the hemodynamic responses associated with all three networks were simultaneously active. These findings highlight distinct cognitive processes and corresponding functional brain networks underlying stages of disconfirmatory evidence integration, and demonstrate the power of multivariate and multi-experiment methodology in cognitive neuroscience. Copyright © 2015 Elsevier Inc. All rights reserved.

Control of a Multi-Functional Inverter for Grid Integration of PV and Battery Energy Storage System

DEFF Research Database (Denmark)

Mousazadeh, Seyyed Yousef; Firoozabadi, Mehdi Savaghebi; Beirami, A.

2015-01-01

This paper presents a multi-functional control of a DC/AC inverter for Power Quality compensation of nonlinear and unequal local loads and grid integration of hybrid photovoltaic (PV) and battery energy storage systems. Multi-layer neural network estimator and a DC/DC converter are used for maximum...... is used for delivering desire power to the grid. For compensation aim, instantaneous active and reactive power theory (p-q) is used. Via the algorithm, the DC/AC inverter not only can be controlled to inject the power of battery and PV, but also it is used as shunt active filter for compensating unequal...... power point tracking (MPPT) of PV array. The power system is 3-phase 4-wires and the DC/AC inverter is chosen 4-leg three phase inverter which has good performance in presence of zero sequence components. Battery energy storage is connected to PV system in common DC bus and a power management strategy...

A systematic and efficient method to compute multi-loop master integrals

Science.gov (United States)

Liu, Xiao; Ma, Yan-Qing; Wang, Chen-Yu

2018-04-01

We propose a novel method to compute multi-loop master integrals by constructing and numerically solving a system of ordinary differential equations, with almost trivial boundary conditions. Thus it can be systematically applied to problems with arbitrary kinematic configurations. Numerical tests show that our method can not only achieve results with high precision, but also be much faster than the only existing systematic method sector decomposition. As a by product, we find a new strategy to compute scalar one-loop integrals without reducing them to master integrals.

Automation of multi-agent control for complex dynamic systems in heterogeneous computational network

Science.gov (United States)

Oparin, Gennady; Feoktistov, Alexander; Bogdanova, Vera; Sidorov, Ivan

2017-01-01

The rapid progress of high-performance computing entails new challenges related to solving large scientific problems for various subject domains in a heterogeneous distributed computing environment (e.g., a network, Grid system, or Cloud infrastructure). The specialists in the field of parallel and distributed computing give the special attention to a scalability of applications for problem solving. An effective management of the scalable application in the heterogeneous distributed computing environment is still a non-trivial issue. Control systems that operate in networks, especially relate to this issue. We propose a new approach to the multi-agent management for the scalable applications in the heterogeneous computational network. The fundamentals of our approach are the integrated use of conceptual programming, simulation modeling, network monitoring, multi-agent management, and service-oriented programming. We developed a special framework for an automation of the problem solving. Advantages of the proposed approach are demonstrated on the parametric synthesis example of the static linear regulator for complex dynamic systems. Benefits of the scalable application for solving this problem include automation of the multi-agent control for the systems in a parallel mode with various degrees of its detailed elaboration.

Including 10-Gigabit-capable Passive Optical Network under End-to-End Generalized Multi-Protocol Label Switching Provisioned Quality of Service

DEFF Research Database (Denmark)

Brewka, Lukasz Jerzy; Gavler, Anders; Wessing, Henrik

2012-01-01

of the network where quality of service signaling is bridged. This article proposes strategies for generalized multi-protocol label switching control over next emerging passive optical network standard, i.e., the 10-gigabit-capable passive optical network. Node management and resource allocation approaches...... are discussed, and possible issues are raised. The analysis shows that consideration of a 10-gigabit-capable passive optical network as a generalized multi-protocol label switching controlled domain is valid and may advance end-to-end quality of service provisioning for passive optical network based customers.......End-to-end quality of service provisioning is still a challenging task despite many years of research and development in this area. Considering a generalized multi-protocol label switching based core/metro network and resource reservation protocol capable home gateways, it is the access part...

THE INTEGRATION OF EDUCATION IN MULTI-RACIAL AND MULTI-CULTURAL SOCIETY

Directory of Open Access Journals (Sweden)

Chamisah Chamisah

2017-07-01

Full Text Available This study aims to know the reasons of education ina multi-racial and multi-cultural society demands integration.. The studywhich focuses onMalaysia country typified by three major ethnic groups, namely Malays, Chinese and Indians,foundthat, firstlythe integration of curriculum in creating a holistic education isvital for the society to create a competitive human capital with value laden such as trustworthiness, dedication, creativity, civic awareness and many more. Secondly, integration curriculum emphasizes on the equity and equality of education for all.Through interacting with individuals from a range of religious and ethnic backgrounds, people will learn to understand, accept and embrace differences. Throughsharing experiences and aspirations,a common national identity and ultimately unity can be achieved. Therefore, integrating curriculum is not only to integrate Islamic concepts in the education system but alsoto integrate all the concepts that make one comprehensive curriculum. Thirdly, it is important to integrate the curriculum with a value-laden perspective to encourage solidarity and harmony. Keywords: Multi-racial; Multi-cultural society; Education; Malaysia

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

Science.gov (United States)

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

A multi-level, multi-jurisdictional strategy: Transnational tobacco companies' attempts to obstruct tobacco packaging restrictions.

Science.gov (United States)

Hawkins, Benjamin; Holden, Chris; Mackinder, Sophie

2018-03-09

Despite the extensive literature on the tobacco industry, there has been little attempt to study how transnational tobacco companies (TTCs) coordinate their political activities globally, or to theorise TTC strategies within the context of global governance structures and policy processes. This article draws on three concepts from political science - policy transfer, multi-level governance and venue shifting - to analyse TTCs' integrated, global strategies to oppose augmented packaging requirements across multiple jurisdictions. Following Uruguay's introduction of extended labelling requirements, Australia became the first country in the world to require tobacco products to be sold in standardised ('plain') packaging in 2012. Governments in the European Union, including in the United Kingdom and Ireland, adopted similar laws, with other member states due to follow. TTCs vehemently opposed these measures and developed coordinated, global strategies to oppose their implementation, exploiting the complexity of contemporary global governance arrangements. These included a series of legal challenges in various jurisdictions, alongside political lobbying and public relations campaigns. This article draws on analysis of public documents and 32 semi-structured interviews with key policy actors. It finds that TTCs developed coordinated and highly integrated strategies to oppose packaging restrictions across multiple jurisdictions and levels of governance.

Study on integrated TRU multi-recycling in sodium cooled fast reactor CDFR

International Nuclear Information System (INIS)

Hu Yun; Xu Mi; Wang Kan

2010-01-01

In view of recently proposed closed fuel cycle strategy which would recycle the integrated transuranics (TRU) from PWR spent fuel in the fast reactors, the neutronics characteristics of TRU recycled in China Demonstration Fast Reactor (CDFR) are studied in this paper. The results show that loading integrated TRU to substitute pure Pu as driver fuel will mainly make the influence on sodium void worth and negligible effects on other parameters, and hence TRU recycling in CDFR is feasible from viewpoint of core neutronics. If TRU is multi-recycled, the variation of TRU composition depends on fuel types and the ratio of TRU and U when recycling. It is indicated that, when TRU is multi-recycled in CDFR with MOX fuel, the minor actinides (MA) fraction in TRU will firstly decrease to ∼7.24% (minimum) within 8 TRU recycle times and then slowly increase to ∼7.7% after 20 TRU recycle times; while when TRU is multi-recycled in CDFR with metal fuel (TRU-U-10Zr), the MA fraction in TRU will gradually approach to an equilibrium state with the MA fraction of ∼3.8%, demonstrating better MA transmutation effect in metal fuel core. No matter 7.7 or 3.8%, they are both lower than ∼10% in PWR spent fuel with burnup of 45 GWd/tU, which presents satisfying effect of MA amount controlling for TRU multi-recycling strategy. On the other hand, the corresponding recycling parameters such as TRU heat release and neutron emission rate are also much lower in metal fuel than those in MOX fuel. Moreover, TRU recycled in metal fuel will bring greater fissile Pu isotopes equilibrium fraction due to better breeding capability of metal fuel. Finally, it could be summarized that integrated TRU multi-recycling in fast reactor can make contributions to both breeding and transmutation, and such strategy is a prospective closed fuel cycle manner to achieve the object of effective control of cumulated MA amount and sustainable development of nuclear energy.

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models......Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

A systematic and efficient method to compute multi-loop master integrals

Directory of Open Access Journals (Sweden)

Xiao Liu

2018-04-01

Full Text Available We propose a novel method to compute multi-loop master integrals by constructing and numerically solving a system of ordinary differential equations, with almost trivial boundary conditions. Thus it can be systematically applied to problems with arbitrary kinematic configurations. Numerical tests show that our method can not only achieve results with high precision, but also be much faster than the only existing systematic method sector decomposition. As a by product, we find a new strategy to compute scalar one-loop integrals without reducing them to master integrals.

Energy-aware architecture for multi-rate ad hoc networks

Directory of Open Access Journals (Sweden)

Ahmed Yahya

2010-06-01

Full Text Available The backbone of ad hoc network design is energy performance and bandwidth resources limitations. Multi-rate adaptation architectures have been proposed to reduce the control overhead and to increase bandwidth utilization efficiency. In this paper, we propose a multi-rate protocol to provide the highest network performance under very low control overhead. The efficiency of the proposed auto multi-rate protocol is validated extensive simulations using QualNet network simulator. The simulation results demonstrate that our solution significantly improves the overall network performance.

BiologicalNetworks 2.0 - an integrative view of genome biology data

Directory of Open Access Journals (Sweden)

Ponomarenko Julia

2010-12-01

Full Text Available Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other and their relations (interactions, co-expression, co-citations, and other. The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.

Collaborative multi-layer network coding for cellular cognitive radio networks

KAUST Repository

Sorour, Sameh

2013-06-01

In this paper, we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in underlay cellular cognitive radio networks. This scheme allows the collocated primary and cognitive radio base-stations to collaborate with each other, in order to minimize their own and each other\\'s packet recovery overheads, and thus improve their throughput, without any coordination between them. This non-coordinated collaboration is done using a novel multi-layer instantly decodable network coding scheme, which guarantees that each network\\'s help to the other network does not result in any degradation in its own performance. It also does not cause any violation to the primary networks interference thresholds in the same and adjacent cells. Yet, our proposed scheme both guarantees the reduction of the recovery overhead in collocated primary and cognitive radio networks, and allows early recovery of their packets compared to non-collaborative schemes. Simulation results show that a recovery overhead reduction of 15% and 40% can be achieved by our proposed scheme in the primary and cognitive radio networks, respectively, compared to the corresponding non-collaborative scheme. © 2013 IEEE.

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

Science.gov (United States)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

A Communication-Less Distributed Voltage Control Strategy for a Multi-Bus AC Islanded Microgrid

DEFF Research Database (Denmark)

Wang, Yanbo; Tan, Yongdong; Chen, Zhe

2014-01-01

This paper presents a communication-less distributed voltage control strategy for a multi-bus AC islanded microgrid. First, a Kalman Filter-based network voltage estimator is proposed to obtain voltage responses without communication links in the presence of load disturbances. Then, a voltage...... and reliability is improved for islanded microgrids due to communication-less operation. The simulations and experimental results are presented to validate the proposed distributed voltage control strategy....... optimal controller using MPC (Model Predictive Control) are developed to implement voltage optimal control. The contributions of this paper are demonstrated: (1) The proposed voltage estimator can dynamically obtain network voltage responses just through local voltage and current associated with each DG...

Intelligent Multi-Media Integrated Interface Project

Science.gov (United States)

1990-06-01

been devoted to the application of aritificial intelligence technology to the development of human -computer interface technology that integrates speech...RADC-TR-90-128 Final Technical Report June 1090 AD-A225 973 INTELLIGENT MULTI-MEDIA INTEGRATED INTERFACE PROJECT Calspan-University of Buffalo...contractual obligations or notices on a specific document require that it be returned. INTELLIGENT MULTI-MEDIA INTEGRATED INTERFACE PROJECT J. G. Neal J. M

A dynamic routing strategy with limited buffer on scale-free network

Science.gov (United States)

Wang, Yufei; Liu, Feng

2016-04-01

In this paper, we propose an integrated routing strategy based on global static topology information and local dynamic data packet queue lengths to improve the transmission efficiency of scale-free networks. The proposed routing strategy is a combination of a global static routing strategy (based on the shortest path algorithm) and local dynamic queue length management, in which, instead of using an infinite buffer, the queue length of each node i in the proposed routing strategy is limited by a critical queue length Qic. When the network traffic is lower and the queue length of each node i is shorter than its critical queue length Qic, it forwards packets according to the global routing table. With increasing network traffic, when the buffers of the nodes with higher degree are full, they do not receive packets due to their limited buffers and the packets have to be delivered to the nodes with lower degree. The global static routing strategy can shorten the transmission time that it takes a packet to reach its destination, and the local limited queue length can balance the network traffic. The optimal critical queue lengths of nodes have been analysed. Simulation results show that the proposed routing strategy can get better performance than that of the global static strategy based on topology, and almost the same performance as that of the global dynamic routing strategy with less complexity.

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Institute of Scientific and Technical Information of China (English)

Su YAN; Kaiquan CAI

2017-01-01

Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO),the network-wide 4D flight trajectories planning (N4DFTP) problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs) (3D position and time) for all the flights in the whole airway network.Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity,an efficient model for strategic level conflict management is developed in this paper.Specifically,a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated.In consideration of the large-scale,high-complexity,and multi-objective characteristics of the N4DFTP problem,a multi-objective multi-memetic algorithm (MOMMA) that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented.It is capable of rapidly and effectively allocating 4DTs via rerouting,target time controlling,and flight level changing.Additionally,to balance the ability of exploitation and exploration of the algorithm,a special hybridization scheme is adopted for the integration of local and global search.Empirical studies using real air traffic data in China with different network complexities show that the pro posed MOMMA is effective to solve the N4DFTP problem.The solutions achieved are competitive for elaborate decision support under a TBO environment.

A multi-objective multi-memetic algorithm for network-wide conflict-free 4D flight trajectories planning

Directory of Open Access Journals (Sweden)

Su YAN

2017-06-01

Full Text Available Under the demand of strategic air traffic flow management and the concept of trajectory based operations (TBO, the network-wide 4D flight trajectories planning (N4DFTP problem has been investigated with the purpose of safely and efficiently allocating 4D trajectories (4DTs (3D position and time for all the flights in the whole airway network. Considering that the introduction of large-scale 4DTs inevitably increases the problem complexity, an efficient model for strategic-level conflict management is developed in this paper. Specifically, a bi-objective N4DFTP problem that aims to minimize both potential conflicts and the trajectory cost is formulated. In consideration of the large-scale, high-complexity, and multi-objective characteristics of the N4DFTP problem, a multi-objective multi-memetic algorithm (MOMMA that incorporates an evolutionary global search framework together with three problem-specific local search operators is implemented. It is capable of rapidly and effectively allocating 4DTs via rerouting, target time controlling, and flight level changing. Additionally, to balance the ability of exploitation and exploration of the algorithm, a special hybridization scheme is adopted for the integration of local and global search. Empirical studies using real air traffic data in China with different network complexities show that the proposed MOMMA is effective to solve the N4DFTP problem. The solutions achieved are competitive for elaborate decision support under a TBO environment.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

Science.gov (United States)

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Tao Huang

2016-11-01

Full Text Available Wireless sensor networks (WSNs have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs. However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

International Nuclear Information System (INIS)

Santos, Sérgio F.; Fitiwi, Desta Z.; Cruz, Marco R.M.; Cabrita, Carlos M.P.; Catalão, João P.S.

2017-01-01

Highlights: • A dynamic and multi-objective stochastic mixed integer linear programming model is developed. • A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented. • Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs. • As high as 90% of RES integration level may be possible in distribution network systems. • Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. - Abstract: Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not

A multi-disciplinary approach for the integrated assessment of multiple risks in delta areas.

Science.gov (United States)

Sperotto, Anna; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2016-04-01

The assessment of climate change related risks is notoriously difficult due to the complex and uncertain combinations of hazardous events that might happen, the multiplicity of physical processes involved, the continuous changes and interactions of environmental and socio-economic systems. One important challenge lies in predicting and modelling cascades of natural and man -made hazard events which can be triggered by climate change, encompassing different spatial and temporal scales. Another regard the potentially difficult integration of environmental, social and economic disciplines in the multi-risk concept. Finally, the effective interaction between scientists and stakeholders is essential to ensure that multi-risk knowledge is translated into efficient adaptation and management strategies. The assessment is even more complex at the scale of deltaic systems which are particularly vulnerable to global environmental changes, due to the fragile equilibrium between the presence of valuable natural ecosystems and relevant economic activities. Improving our capacity to assess the combined effects of multiple hazards (e.g. sea-level rise, storm surges, reduction in sediment load, local subsidence, saltwater intrusion) is therefore essential to identify timely opportunities for adaptation. A holistic multi-risk approach is here proposed to integrate terminology, metrics and methodologies from different research fields (i.e. environmental, social and economic sciences) thus creating shared knowledge areas to advance multi risk assessment and management in delta regions. A first testing of the approach, including the application of Bayesian network analysis for the assessment of impacts of climate change on key natural systems (e.g. wetlands, protected areas, beaches) and socio-economic activities (e.g. agriculture, tourism), is applied in the Po river delta in Northern Italy. The approach is based on a bottom-up process involving local stakeholders early in different

A study on group decision-making based fault multi-symptom-domain consensus diagnosis

International Nuclear Information System (INIS)

He Yongyong; Chu Fulei; Zhong Binglin

2001-01-01

In the field of fault diagnosis for rotating machines, the conventional methods or the neural network based methods are mainly single symptom domain based methods, and the diagnosis accuracy of which is not always satisfactory. In this paper, in order to utilize multiple symptom domains to improve the diagnosis accuracy, an idea of fault multi-symptom-domain consensus diagnosis is developed. From the point of view of the group decision-making, two particular multi-symptom-domain diagnosis strategies are proposed. The proposed strategies use BP (Back-Propagation) neural networks as diagnosis models in various symptom domains, and then combine the outputs of these networks by two combination schemes, which are based on Dempster-Shafer evidence theory and fuzzy integral theory, respectively. Finally, a case study pertaining to the fault diagnosis for rotor-bearing systems is given in detail, and the results show that the proposed diagnosis strategies are feasible and more efficient than conventional stacked-vector methods

Data-driven integration of genome-scale regulatory and metabolic network models

Science.gov (United States)

Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

2015-01-01

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

Low Power Multi-Hop Networking Analysis in Intelligent Environments.

Science.gov (United States)

Etxaniz, Josu; Aranguren, Gerardo

2017-05-19

Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

Organization of Multi-controller Interaction in Software Defined Networks

Directory of Open Access Journals (Sweden)

Sergey V. Morzhov

2018-01-01

Full Text Available Software Defined Networking (SDN is a promising paradigm for network management. It is a centralized network intelligence on a dedicated server, which runs network operating system, and is called SDN controller. It was assumed that such an architecture should have an improved network performance and monitoring. However, the centralized control architecture of the SDNs brings novel challenges to reliability, scalability, fault tolerance and interoperability. These problems are especially acute for large data center networks and can be solved by combining SDN controllers into clusters, called multi-controllers. Multi-controller architecture became very important for SDN-enabled networks nowadays. This paper gives a comprehensive overview of SDN multi-controller architectures. The authors review several most popular distributed controllers in order to indicate their strengths and weaknesses. They also investigate and classify approaches used. This paper explains in details the difference among various types of multi-controller architectures, the distribution method and the communication system. Furthermore, it provides already implemented architectures and some examples of architectures under consideration by describing their design, communication process, and performance results. In this paper, the authors show their own classification of multi-controllers and claim that, despite the existence of undeniable advantages, all reviewed controllers have serious drawbacks, which must be eliminated. These drawbacks hamper the development of multi-controllers and their widespread adoption in corporate networks. In the end, the authors conclude that now it is impossible to find a solution capable to solve all the tasks assigned to it adequately and fully. The article is published in the authors’ wording.

A New Multi-Sensor Track Fusion Architecture for Multi-Sensor Information Integration

National Research Council Canada - National Science Library

Jean, Buddy H; Younker, John; Hung, Chih-Cheng

2004-01-01

.... This new technology will integrate multi-sensor information and extract integrated multi-sensor information to detect, track and identify multiple targets at any time, in any place under all weather conditions...

Multi-Hop Link Capacity of Multi-Route Multi-Hop MRC Diversity for a Virtual Cellular Network

Science.gov (United States)

Daou, Imane; Kudoh, Eisuke; Adachi, Fumiyuki

In virtual cellular network (VCN), proposed for high-speed mobile communications, the signal transmitted from a mobile terminal is received by some wireless ports distributed in each virtual cell and relayed to the central port that acts as a gateway to the core network. In this paper, we apply the multi-route MHMRC diversity in order to decrease the transmit power and increase the multi-hop link capacity. The transmit power, the interference power and the link capacity are evaluated for DS-CDMA multi-hop VCN by computer simulation. The multi-route MHMRC diversity can be applied to not only DS-CDMA but also other access schemes (i. e. MC-CDMA, OFDM, etc.).

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

Science.gov (United States)

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

2018-04-16

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

Integration of 100% Micro-Distributed Energy Resources in the Low Voltage Distribution Network

DEFF Research Database (Denmark)

You, Shi; Segerberg, Helena

2014-01-01

of heat pumps (HPs) and plug-in electric vehicles (PEVs) at 100% penetration level on a representative urban residential low voltage (LV) distribution network of Denmark are investigated by performing a steady-state load flow analysis through an integrated simulation setup. Three DERs integration...... oriented integration strategies, having 100% integration of DER in the provided LV network is feasible.......The existing electricity infrastructure may to a great extent limit a high penetration of the micro-sized Distributed Energy Resources (DERs), due to the physical bottlenecks, e.g. thermal capacitates of cables, transformers and the voltage limitations. In this study, the integration impacts...

Performance evaluation of multi-stratum resources integrated resilience for software defined inter-data center interconnect.

Science.gov (United States)

Yang, Hui; Zhang, Jie; Zhao, Yongli; Ji, Yuefeng; Wu, Jialin; Lin, Yi; Han, Jianrui; Lee, Young

2015-05-18

Inter-data center interconnect with IP over elastic optical network (EON) is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented multi-stratum resources integration among IP networks, optical networks and application stratums resources that allows to accommodate data center services. In view of this, this study extends to consider the service resilience in case of edge optical node failure. We propose a novel multi-stratum resources integrated resilience (MSRIR) architecture for the services in software defined inter-data center interconnect based on IP over EON. A global resources integrated resilience (GRIR) algorithm is introduced based on the proposed architecture. The MSRIR can enable cross stratum optimization and provide resilience using the multiple stratums resources, and enhance the data center service resilience responsiveness to the dynamic end-to-end service demands. The overall feasibility and efficiency of the proposed architecture is experimentally verified on the control plane of our OpenFlow-based enhanced SDN (eSDN) testbed. The performance of GRIR algorithm under heavy traffic load scenario is also quantitatively evaluated based on MSRIR architecture in terms of path blocking probability, resilience latency and resource utilization, compared with other resilience algorithms.

Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

Science.gov (United States)

Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

2014-05-01

The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

Neural PID Control Strategy for Networked Process Control

Directory of Open Access Journals (Sweden)

Jianhua Zhang

2013-01-01

Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

Linear and Non-linear Multi-Input Multi-Output Model Predictive Control of Continuous Stirred Tank Reactor

Directory of Open Access Journals (Sweden)

Muayad Al-Qaisy

2015-02-01

Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.

The Integration of Education in Multi-racial and Multi-cultural Society

OpenAIRE

Chamisah, Chamisah; M. Daud, Ridhwan

2016-01-01

This study aims to know the reasons of education ina multi-racial and multi-cultural society demands integration.. The studywhich focuses onMalaysia country typified by three major ethnic groups, namely Malays, Chinese and Indians,foundthat, firstlythe integration of curriculum in creating a holistic education isvital for the society to create a competitive human capital with value laden such as trustworthiness, dedication, creativity, civic awareness and many more. Secondly, integration curr...

Multi-Objective Design Of Optimal Greenhouse Gas Observation Networks

Science.gov (United States)

Lucas, D. D.; Bergmann, D. J.; Cameron-Smith, P. J.; Gard, E.; Guilderson, T. P.; Rotman, D.; Stolaroff, J. K.

2010-12-01

One of the primary scientific functions of a Greenhouse Gas Information System (GHGIS) is to infer GHG source emission rates and their uncertainties by combining measurements from an observational network with atmospheric transport modeling. Certain features of the observational networks that serve as inputs to a GHGIS --for example, sampling location and frequency-- can greatly impact the accuracy of the retrieved GHG emissions. Observation System Simulation Experiments (OSSEs) provide a framework to characterize emission uncertainties associated with a given network configuration. By minimizing these uncertainties, OSSEs can be used to determine optimal sampling strategies. Designing a real-world GHGIS observing network, however, will involve multiple, conflicting objectives; there will be trade-offs between sampling density, coverage and measurement costs. To address these issues, we have added multi-objective optimization capabilities to OSSEs. We demonstrate these capabilities by quantifying the trade-offs between retrieval error and measurement costs for a prototype GHGIS, and deriving GHG observing networks that are Pareto optimal. [LLNL-ABS-452333: This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Differential neural network configuration during human path integration

Science.gov (United States)

Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

2014-01-01

Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

A DC Microgrid Coordinated Control Strategy Based on Integrator Current-Sharing

DEFF Research Database (Denmark)

Gao, Liyuan; Liu, Yao; Ren, Huisong

2017-01-01

The DC microgrid has become a new trend for microgrid study with the advantages of high reliability, simple control and low losses. With regard to the drawbacks of the traditional droop control strategies, an improved DC droop control strategy based on integrator current-sharing is introduced....... In the strategy, the principle of eliminating deviation through an integrator is used, constructing the current-sharing term in order to make the power-sharing between different distributed generation (DG) units uniform and reasonable, which can reduce the circulating current between DG units. Furthermore......, at the system coordinated control level, a hierarchical/droop control strategy based on the DC bus voltage is proposed. In the strategy, the operation modes of the AC main network and micro-sources are determined through detecting the DC voltage variation, which can ensure the power balance of the DC microgrid...

An integrated approach to uncover quality marker underlying the effects of Alisma orientale on lipid metabolism, using chemical analysis and network pharmacology.

Science.gov (United States)

Liao, Maoliang; Shang, Haihua; Li, Yazhuo; Li, Tian; Wang, Miao; Zheng, Yanan; Hou, Wenbin; Liu, Changxiao

2018-06-01

Quality control of traditional Chinese medicines is currently a great concern, due to the correlation between the quality control indicators and clinic effect is often questionable. According to the "multi-components and multi-targets" property of TCMs, a new special quality and bioactivity evaluation system is urgently needed. Present study adopted an integrated approach to provide new insights relating to uncover quality marker underlying the effects of Alisma orientale (AO) on lipid metabolism. In this paper, guided by the concept of the quality marker (Q-marker), an integrated strategies "effect-compound-target-fingerprint" was established to discovery and screen the potential quality marker of AO based on network pharmacology and chemical analysis. Firstly, a bioactivity evaluation was performed to screen the main active fractions. Then the chemical compositions were rapidly identified by chemical analysis. Next, networks were constructed to illuminate the interactions between these component and their targets for lipid metabolism, and the potential Q-marker of AO was initially screened. Finally, the activity of the Q-markers was validated in vitro. 50% ethanol extract fraction was found to have the strongest lipid-lowering activity. Then, the network pharmacology was used to clarify the unique relationship between the Q-markers and their integral pharmacological action. Combined with the results obtained, five active ingredients in the 50% ethanol extract fraction were given special considerations to be representative Q-markers: Alisol A, Alisol B, Alisol A 23-acetate, Alisol B 23-acetate and Alisol A 24-acetate, respectively. The chromatographic fingerprints based Q-marker was establishment. The integrated Q-marker screen may offer an alternative quality assessment of herbal medicines. Copyright © 2018. Published by Elsevier GmbH.

An integrated analog O/E/O link for multi-channel laser neurons

Energy Technology Data Exchange (ETDEWEB)

Nahmias, Mitchell A., E-mail: mnahmias@princeton.edu; Tait, Alexander N.; Tolias, Leonidas; Chang, Matthew P.; Ferreira de Lima, Thomas; Shastri, Bhavin J.; Prucnal, Paul R. [Electrical Engineering Department, Princeton University, 41 Olden St, Princeton, New Jersey 08540 (United States)

2016-04-11

We demonstrate an analog O/E/O electronic link to allow integrated laser neurons to accept many distinguishable, high bandwidth input signals simultaneously. This device utilizes wavelength division multiplexing to achieve multi-channel fan-in, a photodetector to sum signals together, and a laser cavity to perform a nonlinear operation. Its speed outpaces accelerated-time neuromorphic electronics, and it represents a viable direction towards scalable networking approaches.

Data-driven integration of genome-scale regulatory and metabolic network models

Directory of Open Access Journals (Sweden)

Saheed eImam

2015-05-01

Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

Science.gov (United States)

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

Science.gov (United States)

Ismail, M. A.; Said, M. N.

2014-06-01

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis.

Integration of geospatial multi-mode transportation Systems in Kuala Lumpur

International Nuclear Information System (INIS)

Ismail, M A; Said, M N

2014-01-01

Public transportation serves people with mobility and accessibility to workplaces, health facilities, community resources, and recreational areas across the country. Development in the application of Geographical Information Systems (GIS) to transportation problems represents one of the most important areas of GIS-technology today. To show the importance of GIS network analysis, this paper highlights the determination of the optimal path between two or more destinations based on multi-mode concepts. The abstract connector is introduced in this research as an approach to integrate urban public transportation in Kuala Lumpur, Malaysia including facilities such as Light Rapid Transit (LRT), Keretapi Tanah Melayu (KTM) Komuter, Express Rail Link (ERL), KL Monorail, road driving as well as pedestrian modes into a single intelligent data model. To assist such analysis, ArcGIS's Network Analyst functions are used whereby the final output includes the total distance, total travelled time, directional maps produced to find the quickest, shortest paths, and closest facilities based on either time or distance impedance for multi-mode route analysis

Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

KAUST Repository

Moubayed, Abdallah J.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2015-01-01

In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio Networks

KAUST Repository

Moubayed, Abdallah J.

2014-01-01

In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated

Integrated healthcare networks' performance: a growth curve modeling approach.

Science.gov (United States)

Wan, Thomas T H; Wang, Bill B L

2003-05-01

This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.

Integration of Self-Assembled Microvascular Networks with Microfabricated PEG-Based Hydrogels.

Science.gov (United States)

Cuchiara, Michael P; Gould, Daniel J; McHale, Melissa K; Dickinson, Mary E; West, Jennifer L

2012-11-07

Despite tremendous efforts, tissue engineered constructs are restricted to thin, simple tissues sustained only by diffusion. The most significant barrier in tissue engineering is insufficient vascularization to deliver nutrients and metabolites during development in vitro and to facilitate rapid vascular integration in vivo. Tissue engineered constructs can be greatly improved by developing perfusable microvascular networks in vitro in order to provide transport that mimics native vascular organization and function. Here a microfluidic hydrogel is integrated with a self-assembling pro-vasculogenic co-culture in a strategy to perfuse microvascular networks in vitro. This approach allows for control over microvascular network self-assembly and employs an anastomotic interface for integration of self-assembled micro-vascular networks with fabricated microchannels. As a result, transport within the system shifts from simple diffusion to vessel supported convective transport and extra-vessel diffusion, thus improving overall mass transport properties. This work impacts the development of perfusable prevascularized tissues in vitro and ultimately tissue engineering applications in vivo.

Multi-actor involvement for integrating ecosystem services in strategic environmental assessment of spatial plans

International Nuclear Information System (INIS)

Rozas-Vásquez, Daniel; Fürst, Christine; Geneletti, Davide; Muñoz, Francisco

2017-01-01

Integrating an ecosystem services (ES) approach into Strategic Environmental Assessment (SEA) of spatial plans potentially enhances the consideration of the value of nature in decision making and policy processes. However, there is increasing concern about the institutional context and a lack of a common understanding of SEA and ecosystem services for adopting them as an integrated framework. This paper addresses this concern by analysing the current understanding and network relations in a multi-actor arrangement as a first step towards a successful integration of ES in SEA and spatial planning. Our analysis focuses on a case study in Chile, where we administered a questionnaire survey to some of the main actors involved in the spatial planning process. The questionnaire focused on issues such as network relations among actors and on conceptual understanding, perceptions and challenges for integrating ES in SEA and spatial planning, knowledge on methodological approaches, and the connections and gaps in the science-policy interface. Our findings suggest that a common understanding of SEA and especially of ES in a context of multiple actors is still at an initial stage in Chile. Additionally, the lack of institutional guidelines and methodological support is considered the main challenge for integration. We conclude that preconditions exist in Chile for integrating ES in SEA for spatial planning, but they strongly depend on appropriate governance schemes that promote a close science-policy interaction, as well as collaborative work and learning. - Highlights: • Linking ecosystem services in SEA is an effective framework for sustainability. • Multi-actor understanding and networks in ecosystem services and SEA were analyzed. • Understanding of SEA and especially of ES is still in an initial stage in Chile. • A lack of institutional guidelines is one of the key challenges for this link.

Multi-actor involvement for integrating ecosystem services in strategic environmental assessment of spatial plans

Energy Technology Data Exchange (ETDEWEB)

Rozas-Vásquez, Daniel, E-mail: danielrozas@gmail.com [Center for Development Research, Dept. Ecology and Natural Resources Management, University of Bonn, Walter Flex Str. 3, 53113 Bonn (Germany); Laboratorio de Planificación Territorial, Universidad Católica de Temuco, Rudecindo ortega, 02950 Temuco (Chile); Fürst, Christine [Martin Luther University Halle-Wittenberg, Dept. Natural Sciences III, Institute for Geosciences and Geography, Von Seckendorff-Platz 4, 06120 Halle-Saale (Germany); Geneletti, Davide [University of Trento, Department of Civil, Environmental and Mechanical Engineering, via Mesiano, 77, Trento 38123 (Italy); Muñoz, Francisco [Laboratorio de Planificación Territorial, Universidad Católica de Temuco, Rudecindo ortega, 02950 Temuco (Chile)

2017-01-15

Integrating an ecosystem services (ES) approach into Strategic Environmental Assessment (SEA) of spatial plans potentially enhances the consideration of the value of nature in decision making and policy processes. However, there is increasing concern about the institutional context and a lack of a common understanding of SEA and ecosystem services for adopting them as an integrated framework. This paper addresses this concern by analysing the current understanding and network relations in a multi-actor arrangement as a first step towards a successful integration of ES in SEA and spatial planning. Our analysis focuses on a case study in Chile, where we administered a questionnaire survey to some of the main actors involved in the spatial planning process. The questionnaire focused on issues such as network relations among actors and on conceptual understanding, perceptions and challenges for integrating ES in SEA and spatial planning, knowledge on methodological approaches, and the connections and gaps in the science-policy interface. Our findings suggest that a common understanding of SEA and especially of ES in a context of multiple actors is still at an initial stage in Chile. Additionally, the lack of institutional guidelines and methodological support is considered the main challenge for integration. We conclude that preconditions exist in Chile for integrating ES in SEA for spatial planning, but they strongly depend on appropriate governance schemes that promote a close science-policy interaction, as well as collaborative work and learning. - Highlights: • Linking ecosystem services in SEA is an effective framework for sustainability. • Multi-actor understanding and networks in ecosystem services and SEA were analyzed. • Understanding of SEA and especially of ES is still in an initial stage in Chile. • A lack of institutional guidelines is one of the key challenges for this link.

Export policies for multi-domain WDM networks

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Ruepp, Sarah Renée

2010-01-01

We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking......We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking...

Neural networks within multi-core optic fibers.

Science.gov (United States)

Cohen, Eyal; Malka, Dror; Shemer, Amir; Shahmoon, Asaf; Zalevsky, Zeev; London, Michael

2016-07-07

Hardware implementation of artificial neural networks facilitates real-time parallel processing of massive data sets. Optical neural networks offer low-volume 3D connectivity together with large bandwidth and minimal heat production in contrast to electronic implementation. Here, we present a conceptual design for in-fiber optical neural networks. Neurons and synapses are realized as individual silica cores in a multi-core fiber. Optical signals are transferred transversely between cores by means of optical coupling. Pump driven amplification in erbium-doped cores mimics synaptic interactions. We simulated three-layered feed-forward neural networks and explored their capabilities. Simulations suggest that networks can differentiate between given inputs depending on specific configurations of amplification; this implies classification and learning capabilities. Finally, we tested experimentally our basic neuronal elements using fibers, couplers, and amplifiers, and demonstrated that this configuration implements a neuron-like function. Therefore, devices similar to our proposed multi-core fiber could potentially serve as building blocks for future large-scale small-volume optical artificial neural networks.

Connectivity model for Inter-working multi-hop wireless networks

CSIR Research Space (South Africa)

Salami, O

2009-08-01

Full Text Available pairs in inter-working multi-hop wireless networks can be evaluated based on the availability of radio links and communication routes. This paper presents an analytical study of the link and route availability in inter-working multi-hop wireless networks....

Controlling the dynamics of multi-state neural networks

International Nuclear Information System (INIS)

Jin, Tao; Zhao, Hong

2008-01-01

In this paper, we first analyze the distribution of local fields (DLF) which is induced by the memory patterns in the Q-Ising model. It is found that the structure of the DLF is closely correlated with the network dynamics and the system performance. However, the design rule adopted in the Q-Ising model, like the other rules adopted for multi-state neural networks with associative memories, cannot be applied to directly control the DLF for a given set of memory patterns, and thus cannot be applied to further study the relationships between the structure of the DLF and the dynamics of the network. We then extend a design rule, which was presented recently for designing binary-state neural networks, to make it suitable for designing general multi-state neural networks. This rule is able to control the structure of the DLF as expected. We show that controlling the DLF not only can affect the dynamic behaviors of the multi-state neural networks for a given set of memory patterns, but also can improve the storage capacity. With the change of the DLF, the network shows very rich dynamic behaviors, such as the 'chaos phase', the 'memory phase', and the 'mixture phase'. These dynamic behaviors are also observed in the binary-state neural networks; therefore, our results imply that they may be the universal behaviors of feedback neural networks

Knowledge Strategies in Using Social Networks

Directory of Open Access Journals (Sweden)

Contantin BRĂTIANU

2013-05-01

Full Text Available Knowledge strategy selection is a multiple criteria decision-making (MCDM problem, and requires adequate methods to solve it appropriately. Knowledge strategies are also intrinsically linked to individuals and their ability to comprehend the world and leverage their intellectual assets to respond e!ectively to a fast changing environment. the essential features of social networking sites include but are not limited to: blogging, grouping, networking and instant messaging. Since the social networks facilitate communication and interaction among users, there is a continuous need of researches to examine what are the motives that a!ect the acceptance of usage of the social networks. This study aims at examining the role of the knowledge strategies that individuals employ in using social networks with respect to the overall objective of increasing the knowledge level. For this purpose we have used the Analytic Hierarchy Process (AHP mathematical model since it allows us a structuring of the overall objective on the main components. For the present research we considered a structure composed of three levels: L1 – the purpose of networking, L2 – strategies used to achieve that purpose, and L3 – activities needed for strategies implementation. At the upper level (L1, the main objective of a person in using social networks is to increase its knowledge level. To obtain the aforementioned objective we considered for the second level (L2 the following strategies: S1 – to learn from other persons; S2 – to make new friends; S3 – to increase the personal experience and visibility. the implementation of these strategies is realized through the following activities considered at the third hierarchy level (L3: A1– joining general social networks (e.g. Facebook, Google+, MySpace, Hi5 etc.; A2– joining professional social networks (e.g. LinkedIn etc.; A3– creating a personal blog (e.g. Blogster, Wordpress etc.; A4– joining online communities of

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.

Topology Control in Aerial Multi-Beam Directional Networks

Science.gov (United States)

2017-04-24

Topology Control in Aerial Multi-Beam Directional Networks Brian Proulx, Nathaniel M. Jones, Jennifer Madiedo, Greg Kuperman {brian.proulx, njones...significant interference. Topology control (i.e., selecting a subset of neighbors to communicate with) is vital to reduce the interference. Good topology ...underlying challenges to topology control in multi-beam direction networks. Two topology control algorithms are developed: a centralized algorithm

A multi-lateral trading model for coupled gas-heat-power energy networks

International Nuclear Information System (INIS)

Chen, Yue; Wei, Wei; Liu, Feng; Mei, Shengwei

2017-01-01

Highlights: •Optimal energy flows in the gas, heat, and power systems are modeled in detail. •A multi-lateral trading model for the coupled energy markets is proposed. •A two-phase algorithm for computing the market equilibrium. •Case studies demonstrate that market competition pilots reasonable energy prices. -- Abstract: The proliferation of cogeneration technology and the need for more resilient energy utilization inspire the emerging trend of integration of multi-resource energy systems, in which natural gas, heat, and electricity are produced, delivered, converted, and distributed more efficiently and flexibly. The increasing interactions and interdependencies across heterogenous physical networks impose remarkable challenges on the operation and market organization. This paper envisions the market trading scheme in the network-coupled natural gas system, district heating system, and power system. Based on the physical energy flow models of each system and their interdependency, a multi-lateral trading gas-heat-power (MLT-GHP) model is suggested, and a mixed-integer linear programming based two-phase algorithm is developed to find the market equilibrium. Case studies on two testing systems demonstrate the effectiveness of the proposed model and method, showing that the multi-lateral trading essentially results in market competition that orientates reasonable energy prices. Some prospects for future researches are also summarized.

Immune networks: multi-tasking capabilities at medium load

Science.gov (United States)

Agliari, E.; Annibale, A.; Barra, A.; Coolen, A. C. C.; Tantari, D.

2013-08-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ˜ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ˜ Nδ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ frameworks are required to achieve effective retrieval.

Network coding for multi-resolution multicast

DEFF Research Database (Denmark)

2013-01-01

A method, apparatus and computer program product for utilizing network coding for multi-resolution multicast is presented. A network source partitions source content into a base layer and one or more refinement layers. The network source receives a respective one or more push-back messages from one...... or more network destination receivers, the push-back messages identifying the one or more refinement layers suited for each one of the one or more network destination receivers. The network source computes a network code involving the base layer and the one or more refinement layers for at least one...... of the one or more network destination receivers, and transmits the network code to the one or more network destination receivers in accordance with the push-back messages....

Multi-Level Secure Local Area Network

OpenAIRE

Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

2011-01-01

Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

New optimization strategies of pavement maintenance: A case study for national road network in Indonesia using integrated road management system

Science.gov (United States)

Hamdi, Hadiwardoyo, Sigit P.; Correia, A. Gomes; Pereira, Paulo

2017-06-01

A road network requires timely maintenance to keep the road surface in good condition onward better services to improve accessibility and mobility. Strategies and maintenance techniques must be chosen in order to maximize road service level through cost-effective interventions. This approach requires an updated database, which the road network in Indonesia is supported by a manual and visual survey, also using NAASRA profiler. Furthermore, in this paper, the deterministic model of deterioration was used. This optimization model uses life cycle cost analysis (LCCA), applied in an integrated manner, using IRI indicator, and allows determining the priority of treatment, type of treatment and its relation to the cost. The purpose of this paper was focussed on the aspects of road maintenance management, i.e., maintenance optimization models for different levels of traffic and various initial of road distress conditions on the national road network in Indonesia. The implementation of Integrated Road Management System (IRMS) can provide a solution to the problem of cost constraints in the maintenance of the national road network. The results from this study found that as the lowest as agency cost, it will affect the increasing of user cost. With the achievement of the target plan scenario Pl000 with initial value IRI 2, it was found that the routine management throughout the year and in early reconstruction and periodic maintenance with a 30 mm thick overlay, will simultaneously provide a higher net benefit value and has the lowest total cost of transportation.

Reflections on a vision for integrated research and monitoring after 15 years

Science.gov (United States)

Murdoch, Peter S.; McHale, Michael; Baron, Jill S.

2014-01-01

In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating

Adjusting Sensing Range to Maximize Throughput on Ad-Hoc Multi-Hop Wireless Networks

National Research Council Canada - National Science Library

Roberts, Christopher

2003-01-01

.... Such a network is referred to as a multi-hop ad-hoc network, or simply a multi-hop network. Most multi-hop network protocols use some form of carrier sensing to determine if the wireless channel is in use...

Handoff Triggering and Network Selection Algorithms for Load-Balancing Handoff in CDMA-WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Khalid Qaraqe

2008-10-01

Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.

Handoff Triggering and Network Selection Algorithms for Load-Balancing Handoff in CDMA-WLAN Integrated Networks

Directory of Open Access Journals (Sweden)

Kim Jang-Sub

2008-01-01

Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.

Problems With Deployment of Multi-Domained, Multi-Homed Mobile Networks

Science.gov (United States)

Ivancic, William D.

2008-01-01

This document describes numerous problems associated with deployment of multi-homed mobile platforms consisting of multiple networks and traversing large geographical areas. The purpose of this document is to provide insight to real-world deployment issues and provide information to groups that are addressing many issues related to multi-homing, policy-base routing, route optimization and mobile security - particularly those groups within the Internet Engineering Task Force.

Stochastic noncooperative and cooperative evolutionary game strategies of a population of biological networks under natural selection.

Science.gov (United States)

Chen, Bor-Sen; Yeh, Chin-Hsun

2017-12-01

We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.

Pinning adaptive synchronization of a class of uncertain complex dynamical networks with multi-link against network deterioration

International Nuclear Information System (INIS)

Li, Lixiang; Li, Weiwei; Kurths, Jürgen; Luo, Qun; Yang, Yixian; Li, Shudong

2015-01-01

For the reason that the uncertain complex dynamic network with multi-link is quite close to various practical networks, there is superiority in the fields of research and application. In this paper, we focus upon pinning adaptive synchronization for uncertain complex dynamic networks with multi-link against network deterioration. The pinning approach can be applied to adapt uncertain coupling factors of deteriorated networks which can compensate effects of uncertainty. Several new synchronization criterions for networks with multi-link are derived, which ensure the synchronized states to be local or global stable with uncertainty and deterioration. Results of simulation are shown to demonstrate the feasibility and usefulness of our method

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Directory of Open Access Journals (Sweden)

Syed Ali Abbas Kazmi

2017-02-01

Full Text Available Distribution networks (DNWs are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN needs to consider choices, primarily distributed generation (DG, network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs based on mult-objective optimizations (MOOs in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at

Comparison of Multi-Criteria Decision Support Methods for Integrated Rehabilitation Prioritization

Directory of Open Access Journals (Sweden)

Franz Tscheikner-Gratl

2017-01-01

Full Text Available The decisions taken in rehabilitation planning for the urban water networks will have a long lasting impact on the functionality and quality of future services provided by urban infrastructure. These decisions can be assisted by different approaches ranging from linear depreciation for estimating the economic value of the network over using a deterioration model to assess the probability of failure or the technical service life to sophisticated multi-criteria decision support systems. Subsequently, the aim of this paper is to compare five available multi-criteria decision-making (MCDM methods (ELECTRE, AHP, WSM, TOPSIS, and PROMETHEE for the application in an integrated rehabilitation management scheme for a real world case study and analyze them with respect to their suitability to be used in integrated asset management of water systems. The results of the different methods are not equal. This occurs because the chosen score scales, weights and the resulting distributions of the scores within the criteria do not have the same impact on all the methods. Independently of the method used, the decision maker must be familiar with its strengths but also weaknesses. Therefore, in some cases, it would be rational to use one of the simplest methods. However, to check for consistency and increase the reliability of the results, the application of several methods is encouraged.

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management.

Science.gov (United States)

Cruz-Piris, Luis; Rivera, Diego; Fernandez, Susel; Marsa-Maestre, Ivan

2018-02-02

One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO) traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS) Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic) in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Range based power control for multi-radio multi-channel wireless mesh networks

CSIR Research Space (South Africa)

Olwal, TO

2009-08-01

Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in Wireless Mesh Networks (WMNs). In this paper, researchers present a range based dynamic power control for MRMC WMNs. First, WMN is represented as a set of disjoint Unified...

Multi-Valued Associative Memory Neural Network

Institute of Scientific and Technical Information of China (English)

修春波; 刘向东; 张宇河

2003-01-01

A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.

A global, multi-disciplinary, multi-sectorial initiative to combat leptospirosis: Global Leptospirosis Environmental Action Network (GLEAN).

Science.gov (United States)

Durski, Kara N; Jancloes, Michel; Chowdhary, Tej; Bertherat, Eric

2014-06-05

Leptospirosis has emerged as a major public health problem in both animals and humans. The true burden of this epidemic and endemic disease is likely to be grossly under-estimated due to the non-specific clinical presentations of the disease and the difficulty of laboratory confirmation. The complexity that surrounds the transmission dynamics, particularly in epidemic situations, requires a coordinated, multi-disciplinary effort. Therefore, the Global Leptospirosis Environmental Action Network (GLEAN) was developed to improve global and local strategies of how to predict, prevent, detect, and intervene in leptospirosis outbreaks in order to prevent and control leptospirosis in high-risk populations.

Balanced sensitivity functions for tuning multi-dimensional Bayesian network classifiers

NARCIS (Netherlands)

Bolt, J.H.; van der Gaag, L.C.

Multi-dimensional Bayesian network classifiers are Bayesian networks of restricted topological structure, which are tailored to classifying data instances into multiple dimensions. Like more traditional classifiers, multi-dimensional classifiers are typically learned from data and may include

Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

Science.gov (United States)

Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

2014-08-01

Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

A data-driven modeling approach to identify disease-specific multi-organ networks driving physiological dysregulation.

Directory of Open Access Journals (Sweden)

Warren D Anderson

2017-07-01

Full Text Available Multiple physiological systems interact throughout the development of a complex disease. Knowledge of the dynamics and connectivity of interactions across physiological systems could facilitate the prevention or mitigation of organ damage underlying complex diseases, many of which are currently refractory to available therapeutics (e.g., hypertension. We studied the regulatory interactions operating within and across organs throughout disease development by integrating in vivo analysis of gene expression dynamics with a reverse engineering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences. We obtained experimental data on the expression of 22 genes across five organs, over a time span that encompassed the development of autonomic nervous system dysfunction and hypertension. We pursued a unique approach for identification of continuous-time models that jointly described the dynamics and structure of multi-organ networks by estimating a sparse subset of ∼12,000 possible gene regulatory interactions. Our analyses revealed that an autonomic dysfunction-specific multi-organ sequence of gene expression activation patterns was associated with a distinct gene regulatory network. We analyzed the model structures for adaptation motifs, and identified disease-specific network motifs involving genes that exhibited aberrant temporal dynamics. Bioinformatic analyses identified disease-specific single nucleotide variants within or near transcription factor binding sites upstream of key genes implicated in maintaining physiological homeostasis. Our approach illustrates a novel framework for investigating the pathogenesis through model-based analysis of multi-organ system dynamics and network properties. Our results yielded novel candidate molecular targets driving the development of cardiovascular disease, metabolic syndrome, and immune dysfunction.

Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties

Directory of Open Access Journals (Sweden)

Vahid Amir

2017-11-01

Full Text Available A microgrid (MG is a small-scale version of the power system which makes possible the integration of renewable resources as well as achieving maximum demand side management (DSM utilization. The future power system will be faced with severe uncertainties owing to penetration of renewable resources. Consequently, the uncertainty assessment of system performance is essential. The conventional energy scheduling in an MG may not be suitable for active distribution networks. Hence, this study focuses on the probabilistic analysis of optimal power dispatch considering economic aspects in a multi-carrier networked microgrid. The aim is to study the impact of uncertain behavior of loads, renewable resources, and electricity market on the optimal management of a multi-carrier networked microgrid. Furthermore, a novel time-based demand side management is proposed in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. The optimization model is formulated as a mixed integer nonlinear program (MINLP and is solved using MATLAB and GAMS software. Results show that the energy sharing capability between MCMGs and MCMGs and the main grids as well as utilization of demand side management can decrease operating costs for smart distribution grids.

Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

Science.gov (United States)

Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

2018-02-01

The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A path finding implementation for multi-layer networks

NARCIS (Netherlands)

Dijkstra, F.; van der Ham, J.; Grosso, P.; de Laat, C.

2009-01-01

The goal of the OptIPuter project is to tightly couple research applications with dynamically allocated paths. Since OptIPuter is a multi-disciplinary project, the paths through the network often span multiple network domains, and the applications are challenged to find valid network connections

A path finding implementation for multi-layer network

NARCIS (Netherlands)

Dijkstra, F.; Ham, J.J. van der; Grosso, P.; Laat, C. de

2009-01-01

The goal of the OptIPuter project is to tightly couple research applications with dynamically allocated paths. Since OptIPuter is a multi-disciplinary project, the paths through the network often span multiple network domains, and the applications are challenged to find valid network connections

Integrated System for Performance Monitoring of ATLAS TDAQ Network

CERN Document Server

Savu, D; The ATLAS collaboration; Martin, B; Sjoen, R; Batraneanu, S; Stancu, S

2010-01-01

The ATLAS TDAQ Network consists of three separate networks spanning four levels of the experimental building. Over 200 edge switches and 5 multi-blade chassis routers are used to interconnect 2000 processors, adding up to more than 7000 high speed interfaces. In order to substantially speed-up ad-hoc and post mortem analysis, a scalable, yet flexible, integrated system for monitoring both network statistics and environmental conditions, processor parameters and data taking characteristics was required. For successful up-to-the-minute monitoring, information from many SNMP compliant devices, independent databases and custom APIs was gathered, stored and displayed in an optimal way. Easy navigation and compact aggregation of multiple data sources were the main requirements; characteristics not found in any of the tested products, either open-source or commercial. This paper describes how performance, scalability and display issues were addressed and what challenges the project faced during development and deplo...

Multi-state supernetworks: recent progress and prospects

Directory of Open Access Journals (Sweden)

Feixiong Liao

2014-02-01

Full Text Available Supernetworks have long been adopted to address multi-dimensional choice problems, which are thorny to solve for classic singular networks. Originated from combining transport mode and route choice into a multi-modal network, supernetworks have been extended into multi-state networks to include activity-travel scheduling, centered around activity-based models of travel demand. A key feature of the network extensions is that multiple choice facets pertaining to conducting a full activity program can be modeled in a consistent and integrative fashion. Thus, interdependencies and constraints between related choice facets can be readily captured. Given this advantage of integrity, the modeling of supernetwork has become an emerging topic in transportation research. This paper summarizes the recent progress in modeling multi-state supernetworks and discusses future prospects.

Intelligent Networks Data Fusion Web-based Services for Ad-hoc Integrated WSNs-RFID

Directory of Open Access Journals (Sweden)

Falah Alshahrany

2016-01-01

Full Text Available The use of variety of data fusion tools and techniques for big data processing poses the problem of the data and information integration called data fusion having objectives which can differ from one application to another. The design of network data fusion systems aimed at meeting these objectives, need to take into account of the necessary synergy that can result from distributed data processing within the data networks and data centres, involving increased computation and communication. This papers reports on how this processing distribution is functionally structured as configurable integrated web-based support services, in the context of an ad-hoc wireless sensor network used for sensing and tracking, in the context of distributed detection based on complete observations to support real rime decision making. The interrelated functional and hardware RFID-WSN integration is an essential aspect of the data fusion framework that focuses on multi-sensor collaboration as an innovative approach to extend the heterogeneity of the devices and sensor nodes of ad-hoc networks generating a huge amount of heterogeneous soft and hard raw data. The deployment and configuration of these networks require data fusion processing that includes network and service management and enhances the performance and reliability of networks data fusion support systems providing intelligent capabilities for real-time control access and fire detection.

Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

Science.gov (United States)

He, Yongqun

2014-07-01

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

Balancing energy consumption with hybrid clustering and routing strategy in wireless sensor networks.

Science.gov (United States)

Xu, Zhezhuang; Chen, Liquan; Liu, Ting; Cao, Lianyang; Chen, Cailian

2015-10-20

Multi-hop data collection in wireless sensor networks (WSNs) is a challenge issue due to the limited energy resource and transmission range of wireless sensors. The hybrid clustering and routing (HCR) strategy has provided an effective solution, which can generate a connected and efficient cluster-based topology for multi-hop data collection in WSNs. However, it suffers from imbalanced energy consumption, which results in the poor performance of the network lifetime. In this paper, we evaluate the energy consumption of HCR and discover an important result: the imbalanced energy consumption generally appears in gradient k = 1, i.e., the nodes that can communicate with the sink directly. Based on this observation, we propose a new protocol called HCR-1, which includes the adaptive relay selection and tunable cost functions to balance the energy consumption. The guideline of setting the parameters in HCR-1 is provided based on simulations. The analytical and numerical results prove that, with minor modification of the topology in Sensors 2015, 15 26584 gradient k = 1, the HCR-1 protocol effectively balances the energy consumption and prolongs the network lifetime.

Comparison of immunization strategies in geographical networks

Energy Technology Data Exchange (ETDEWEB)

Wang Bing; Aihara, Kazuyuki [Institute of Industrial Science, The University of Tokyo, Tokyo (Japan)] [ERATO Aihara Complexity Modelling Project, JST, Institute of Industrial Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8505 (Japan); Kim, Beom Jun, E-mail: beomjun@skku.ed [BK21 Physics Research Division and Department of Energy Science, Sungkyunkwan University, Suwon 440-746 (Korea, Republic of)] [Department of Computational Biology, School of Computer Science and Communication, Royal Institute of Technology, 100 44 Stockholm (Sweden)

2009-10-12

The epidemic spread and immunizations in geographically embedded scale-free (SF) and Watts-Strogatz (WS) networks are numerically investigated. We make a realistic assumption that it takes time which we call the detection time, for a vertex to be identified as infected, and implement two different immunization strategies: one is based on connection neighbors (CN) of the infected vertex with the exact information of the network structure utilized and the other is based on spatial neighbors (SN) with only geographical distances taken into account. We find that the decrease of the detection time is crucial for a successful immunization in general. Simulation results show that for both SF networks and WS networks, the SN strategy always performs better than the CN strategy, especially for more heterogeneous SF networks at long detection time. The observation is verified by checking the number of the infected nodes being immunized. We found that in geographical space, the distance preferences in the network construction process and the geographically decaying infection rate are key factors that make the SN immunization strategy outperforms the CN strategy. It indicates that even in the absence of the full knowledge of network connectivity we can still stop the epidemic spread efficiently only by using geographical information as in the SN strategy, which may have potential applications for preventing the real epidemic spread.

Comparison of immunization strategies in geographical networks

International Nuclear Information System (INIS)

Wang Bing; Aihara, Kazuyuki; Kim, Beom Jun

2009-01-01

The epidemic spread and immunizations in geographically embedded scale-free (SF) and Watts-Strogatz (WS) networks are numerically investigated. We make a realistic assumption that it takes time which we call the detection time, for a vertex to be identified as infected, and implement two different immunization strategies: one is based on connection neighbors (CN) of the infected vertex with the exact information of the network structure utilized and the other is based on spatial neighbors (SN) with only geographical distances taken into account. We find that the decrease of the detection time is crucial for a successful immunization in general. Simulation results show that for both SF networks and WS networks, the SN strategy always performs better than the CN strategy, especially for more heterogeneous SF networks at long detection time. The observation is verified by checking the number of the infected nodes being immunized. We found that in geographical space, the distance preferences in the network construction process and the geographically decaying infection rate are key factors that make the SN immunization strategy outperforms the CN strategy. It indicates that even in the absence of the full knowledge of network connectivity we can still stop the epidemic spread efficiently only by using geographical information as in the SN strategy, which may have potential applications for preventing the real epidemic spread.

Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; Ko, King-Tim

2011-01-01

the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolution algorithm to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general, presumes that we have product form between the nodes. Otherwise, we have the state space explosion. Even so, the detailed state space of each node may become very large because there is no product form between chains inside a node. A prerequisite for product form...

Security for multi-hop wireless networks

CERN Document Server

Mahmoud, Mohamed M E A

2014-01-01

This Springer Brief discusses efficient security protocols and schemes for multi-hop wireless networks. It presents an overview of security requirements for these networks, explores challenges in securing networks and presents system models. The authors introduce mechanisms to reduce the overhead and identify malicious nodes that drop packets intentionally. Also included is a new, efficient cooperation incentive scheme to stimulate the selfish nodes to relay information packets and enforce fairness. Many examples are provided, along with predictions for future directions of the field. Security

A control technique for integration of DG units to the electrical networks

DEFF Research Database (Denmark)

Pouresmaeil, Edris; Miguel-Espinar, Carlos; Massot-Campos, Miquel

2013-01-01

This paper deals with a multiobjective control technique for integration of distributed generation (DG) resources to the electrical power network. The proposed strategy provides compensation for active, reactive, and harmonic load current components during connection of DG link to the grid...

Optimized Sensor Network and Multi-Agent Decision Support for Smart Traffic Light Management

Directory of Open Access Journals (Sweden)

Luis Cruz-Piris

2018-02-01

Full Text Available One of the biggest challenges in modern societies is to solve vehicular traffic problems. Sensor networks in traffic environments have contributed to improving the decision-making process of Intelligent Transportation Systems. However, one of the limiting factors for the effectiveness of these systems is in the deployment of sensors to provide accurate information about the traffic. Our proposal is using the centrality measurement of a graph as a base to locate the best locations for sensor installation in a traffic network. After integrating these sensors in a simulation scenario, we define a Multi-Agent Systems composed of three types of agents: traffic light management agents, traffic jam detection agents, and agents that control the traffic lights at an intersection. The ultimate goal of these Multi-Agent Systems is to improve the trip duration for vehicles in the network. To validate our solution, we have developed the needed elements for modelling the sensors and agents in the simulation environment. We have carried out experiments using the Simulation of Urban MObility (SUMO traffic simulator and the Travel and Activity PAtterns Simulation (TAPAS Cologne traffic scenario. The obtained results show that our proposal allows to reduce the sensor network while still obtaining relevant information to have a global view of the environment. Finally, regarding the Multi-Agent Systems, we have carried out experiments that show that our proposal is able to improve other existing solutions such as conventional traffic light management systems (static or dynamic in terms of reduction of vehicle trip duration and reduction of the message exchange overhead in the sensor network.

Multiple-state based power control for multi-radio multi-channel wireless mesh networks

CSIR Research Space (South Africa)

Olwal, TO

2009-01-01

Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in wireless mesh networks (WMNs). In this paper, we present asynchronous multiple-state based power control for MRMC WMNs. First, WMN is represented as a set of disjoint...

Multi-Tenant Isolation via Reconfigurable Networks

Energy Technology Data Exchange (ETDEWEB)

Aderholdt, Ferrol [Tennessee Technological Univ., Cookeville, TN (United States); Caldwell, Blake A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hicks, Susan Elaine [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Koch, Scott M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pelfrey, Daniel S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pogge, James R. [Tennessee Technological Univ., Cookeville, TN (United States); Scott, Stephen L. [Tennessee Technological Univ., Cookeville, TN (United States); Shipman, Galen M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Sorrillo, Lawrence [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

2014-12-01

High performance computing environments are often used for a wide variety of workloads ranging from simulation, data transformation and analysis, and complex workflows to name just a few. These systems may process data at various security levels but in so doing are often enclaved at the highest security posture. This approach places significant restrictions on the users of the system even when processing data at a lower security level and exposes data at higher levels of confidentiality to a much broader population than otherwise necessary. The traditional approach of isolation, while effective in establishing security enclaves poses significant challenges for the use of shared infrastructure in HPC environments. This report details current state-of-the-art in reconfigurable network enclaving through Software Defined Networking (SDN) and Network Function Virtualization (NFV) and their applicability to secure enclaves in HPC environments. SDN and NFV methods are based on a solid foundation of system wide virtualization. The purpose of which is very straight forward, the system administrator can deploy networks that are more amenable to customer needs, and at the same time achieve increased scalability making it easier to increase overall capacity as needed without negatively affecting functionality. The network administration of both the server system and the virtual sub-systems is simplified allowing control of the infrastructure through well-defined APIs (Application Programming Interface). While SDN and NFV technologies offer significant promise in meeting these goals, they also provide the ability to address a significant component of the multi-tenant challenge in HPC environments, namely resource isolation. Traditional HPC systems are built upon scalable high-performance networking technologies designed to meet specific application requirements. Dynamic isolation of resources within these environments has remained difficult to achieve. SDN and NFV methodology

Coordinated Multi-layer Multi-domain Optical Network (COMMON) for Large-Scale Science Applications (COMMON)

Energy Technology Data Exchange (ETDEWEB)

Vokkarane, Vinod [University of Massachusetts

2013-09-01

We intend to implement a Coordinated Multi-layer Multi-domain Optical Network (COMMON) Framework for Large-scale Science Applications. In the COMMON project, specific problems to be addressed include 1) anycast/multicast/manycast request provisioning, 2) deployable OSCARS enhancements, 3) multi-layer, multi-domain quality of service (QoS), and 4) multi-layer, multidomain path survivability. In what follows, we outline the progress in the above categories (Year 1, 2, and 3 deliverables).

A Multi-Agent Based Energy Management Solution for Integrated Buildings and Microgrid System

DEFF Research Database (Denmark)

Anvari-Moghaddam, Amjad; Rahimi-Kian, Ashkan; Mirian, Maryam S.

2017-01-01

-reflex to complex learning agents are designed and implemented to cooperate with each other to reach an optimal operating strategy for the mentioned integrated energy system (IES) while meeting the system’s objectives and related constraints. The optimization process for the EMS is defined as a coordinated......In this paper, an ontology-driven multi-agent based energy management system (EMS) is proposed for monitoring and optimal control of an integrated homes/buildings and microgrid system with various renewable energy resources (RESs) and controllable loads. Different agents ranging from simple...... distributed generation (DG) and demand response (DR) management problem within the studied environment and is solved by the proposed agent-based approach utilizing cooperation and communication among decision agents. To verify the effectiveness and applicability of the proposed multi-agent based EMS, several...

Effects of multi-state links in network community detection

International Nuclear Information System (INIS)

Rocco, Claudio M.; Moronta, José; Ramirez-Marquez, José E.; Barker, Kash

2017-01-01

A community is defined as a group of nodes of a network that are densely interconnected with each other but only sparsely connected with the rest of the network. The set of communities (i.e., the network partition) and their inter-community links could be derived using special algorithms account for the topology of the network and, in certain cases, the possible weights associated to the links. In general, the set of weights represents some characteristic as capacity, flow and reliability, among others. The effects of considering weights could be translated to obtain a different partition. In many real situations, particularly when modeling infrastructure systems, networks must be modeled as multi-state networks (e.g., electric power networks). In such networks, each link is characterized by a vector of known random capacities (i.e., the weight on each link could vary according to a known probability distribution). In this paper a simple Monte Carlo approach is proposed to evaluate the effects of multi-state links on community detection as well as on the performance of the network. The approach is illustrated with the topology of an electric power system. - Highlights: • Identify network communities when considering multi-state links. • Identified how effects of considering weights translate to different partition. • Identified importance of Inter-Community Links and changes with respect to community. • Preamble to performing a resilience assessment able to mimic the evolution of the state of each community.

Immune networks: multi-tasking capabilities at medium load

International Nuclear Information System (INIS)

Agliari, E; Annibale, A; Barra, A; Coolen, A C C; Tantari, D

2013-01-01

Associative network models featuring multi-tasking properties have been introduced recently and studied in the low-load regime, where the number P of simultaneously retrievable patterns scales with the number N of nodes as P ∼ log N. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions. Here we develop further the statistical mechanical analysis of such systems, by studying the medium-load regime, P ∼ N δ with δ ∈ (0, 1]. We derive three main results. First, we reveal the nontrivial architecture of these networks: they exhibit a high degree of modularity and clustering, which is linked to their retrieval abilities. Second, by solving the model we demonstrate for δ < 1 the existence of large regions in the phase diagram where the network can retrieve all stored patterns simultaneously. Finally, in the high-load regime δ = 1 we find that the system behaves as a spin-glass, suggesting that finite-connectivity frameworks are required to achieve effective retrieval. (paper)

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules.

Science.gov (United States)

Zhang, Zhen; Ma, Cheng; Zhu, Rong

2016-10-14

High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial-temporal complexity. This paper presents a multi-input multi-output (MIMO) self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional-integral-derivative (PID) neural network (FCPIDNN) and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

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Antônio Dâmaso

2017-11-01

Full Text Available Power consumption is a primary interest in Wireless Sensor Networks (WSNs, and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

Science.gov (United States)

Dâmaso, Antônio; Maciel, Paulo

2017-01-01

Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

Recognizing Multi-user Activities using Body Sensor Networks

DEFF Research Database (Denmark)

Gu, Tao; Wang, Liang; Chen, Hanhua

2011-01-01

The advances of wireless networking and sensor technology open up an interesting opportunity to infer human activities in a smart home environment. Existing work in this paradigm focuses mainly on recognizing activities of a single user. In this work, we address the fundamental problem...... activity classes of data—for building activity models and design a scalable, noise-resistant, Emerging Pattern based Multi-user Activity Recognizer (epMAR) to recognize both single- and multi-user activities. We develop a multi-modal, wireless body sensor network for collecting real-world traces in a smart...... home environment, and conduct comprehensive empirical studies to evaluate our system. Results show that epMAR outperforms existing schemes in terms of accuracy, scalability and robustness....

Multi-agent: a technique to implement geo-visualization of networked virtual reality

Science.gov (United States)

Lin, Zhiyong; Li, Wenjing; Meng, Lingkui

2007-06-01

Networked Virtual Reality (NVR) is a system based on net connected and spatial information shared, whose demands cannot be fully meet by the existing architectures and application patterns of VR to some extent. In this paper, we propose a new architecture of NVR based on Multi-Agent framework. which includes the detailed definition of various agents and their functions and full description of the collaboration mechanism, Through the prototype system test with DEM Data and 3D Models Data, the advantages of Multi-Agent based Networked Virtual Reality System in terms of the data loading time, user response time and scene construction time etc. are verified. First, we introduce the characters of Networked Virtual Realty and the characters of Multi-Agent technique in Section 1. Then we give the architecture design of Networked Virtual Realty based on Multi-Agent in Section 2.The Section 2 content includes the rule of task division, the multi-agent architecture design to implement Networked Virtual Realty and the function of agents. Section 3 shows the prototype implementation according to the design. Finally, Section 4 discusses the benefits of using Multi-Agent to implement geovisualization of Networked Virtual Realty.

Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system

International Nuclear Information System (INIS)

Logenthiran, T.; Srinivasan, Dipti; Khambadkone, Ashwin M.

2011-01-01

This paper proposes a multi-agent system for energy resource scheduling of an islanded power system with distributed resources, which consists of integrated microgrids and lumped loads. Distributed intelligent multi-agent technology is applied to make the power system more reliable, efficient and capable of exploiting and integrating alternative sources of energy. The algorithm behind the proposed energy resource scheduling has three stages. The first stage is to schedule each microgrid individually to satisfy its internal demand. The next stage involves finding the best possible bids for exporting power to the network and compete in a whole sale energy market. The final stage is to reschedule each microgrid individually to satisfy the total demand, which is the addition of internal demand and the demand from the results of the whole sale energy market simulation. The simulation results of a power system with distributed resources comprising three microgrids and five lumped loads show that the proposed multi-agent system allows efficient management of micro-sources with minimum operational cost. The case studies demonstrate that the system is successfully monitored, controlled and operated by means of the developed multi-agent system. (author)

Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system

Energy Technology Data Exchange (ETDEWEB)

Logenthiran, T.; Srinivasan, Dipti; Khambadkone, Ashwin M. [Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576 (Singapore)

2011-01-15

This paper proposes a multi-agent system for energy resource scheduling of an islanded power system with distributed resources, which consists of integrated microgrids and lumped loads. Distributed intelligent multi-agent technology is applied to make the power system more reliable, efficient and capable of exploiting and integrating alternative sources of energy. The algorithm behind the proposed energy resource scheduling has three stages. The first stage is to schedule each microgrid individually to satisfy its internal demand. The next stage involves finding the best possible bids for exporting power to the network and compete in a whole sale energy market. The final stage is to reschedule each microgrid individually to satisfy the total demand, which is the addition of internal demand and the demand from the results of the whole sale energy market simulation. The simulation results of a power system with distributed resources comprising three microgrids and five lumped loads show that the proposed multi-agent system allows efficient management of micro-sources with minimum operational cost. The case studies demonstrate that the system is successfully monitored, controlled and operated by means of the developed multi-agent system. (author)

Integrative analysis of many weighted co-expression networks using tensor computation.

Directory of Open Access Journals (Sweden)

Wenyuan Li

2011-06-01

Full Text Available The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

A Comprehensive Strategy for Accurate Reactive Power Distribution, Stability Improvement, and Harmonic Suppression of Multi-Inverter-Based Micro-Grid

Directory of Open Access Journals (Sweden)

Henan Dong

2018-03-01

Full Text Available Among the issues of accurate power distribution, stability improvement, and harmonic suppression in micro-grid, each has been well studied as an individual, and most of the strategies about these issues aim at one inverter-based micro-grid, hence there is a need to establish a model to achieve these functions as a whole, aiming at a multi-inverter-based micro-grid. This paper proposes a comprehensive strategy which achieves this goal successfully; since the output voltage and frequency of micro-grid all consist of fundamental and harmonic components, the strategy contains two parts accordingly. On one hand, a fundamental control strategy is proposed upon the conventional droop control. The virtual impedance is introduced to solve the problem of accurate allocation of reactive power between inverters. Meanwhile, a secondary power balance controller is added to improve the stability of voltage and frequency while considering the aggravating problem of stability because of introducing virtual impedance. On the other hand, the fractional frequency harmonic control strategy is proposed. It can solve the influence of nonlinear loads, micro-grid inverters, and the distribution network on output voltage of inverters, which is focused on eliminating specific harmonics caused by the nonlinear loads, micro-grid converters, and the distribution network so that the power quality of micro-grid can be improved effectively. Finally, small signal analysis is used to analyze the stability of the multi-converter parallel system after introducing the whole control strategy. The simulation results show that the strategy proposed in this paper has a great performance on distributing reactive power, regulating and stabilizing output voltage of inverters and frequency, eliminating harmonic components, and improving the power quality of multi-inverter-based micro-grid.

Algorithm for queueing networks with multi-rate traffic

DEFF Research Database (Denmark)

Iversen, Villy Bæk; King-Tim, Ko

2011-01-01

the nodes behave as independent nodes. For closed queueing networks with multiple servers in every node and multi-rate services we may apply multidimensional convolutions to aggregate the nodes so that we end up with two nodes, the aggregated node and a single node, for which we can calculate the detailed......In this paper we present a new algorithm for evaluating queueing networks with multi-rate traffic. The detailed state space of a node is evaluated by explicit formulæ. We consider reversible nodes with multi-rate traffic and find the state probabilities by taking advantage of local balance. Theory...... of queueing networks in general presumes that we have product form between the nodes. Other ways we have the state space explosion. Even so the detailed state space of each node may easily become very large because there is no product form between chains inside a node. A prerequisite for product form...

Integrated environmental research and networking of economy and information in rural areas of Finland

Directory of Open Access Journals (Sweden)

M. LUOSTARINEN

2008-12-01

Full Text Available This article uses material from many extensive research projects starting from the construction of the electric power supply network and its water supply systems in northern Finland in 1973-1986, to the Agropolis agricultural strategy and networking for the Loimijoki project. A list of the material and references of the publications is available in Agronet on the Internet. All these projects applied integrated environmental research covering biology, the natural sciences, social sciences, and planning methodology. To be able to promote sustainable agriculture and rural development there is a pressing need to improve research methodology and applications for integrated environmental research. This article reviews the philosophy and development of the theory behind integrated environmental re-search and the theory of network economy.

Multi-equilibrium property of metabolic networks: SSI module

Directory of Open Access Journals (Sweden)

Chen Luonan

2011-06-01

Full Text Available Abstract Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Restoration in multi-domain GMPLS-based networks

DEFF Research Database (Denmark)

Manolova, Anna; Ruepp, Sarah Renée; Dittmann, Lars

2011-01-01

In this paper, we evaluate the efficiency of using restoration mechanisms in a dynamic multi-domain GMPLS network. Major challenges and solutions are introduced and two well-known restoration schemes (End-to-End and Local-to-End) are evaluated. Additionally, new restoration mechanisms are introdu......In this paper, we evaluate the efficiency of using restoration mechanisms in a dynamic multi-domain GMPLS network. Major challenges and solutions are introduced and two well-known restoration schemes (End-to-End and Local-to-End) are evaluated. Additionally, new restoration mechanisms...... are introduced: one based on the position of a failed link, called Location-Based, and another based on minimizing the additional resources consumed during restoration, called Shortest-New. A complete set of simulations in different network scenarios show where each mechanism is more efficient in terms, such as...

A Practice Approach of Multi-source Geospatial Data Integration for Web-based Geoinformation Services

Science.gov (United States)

Huang, W.; Jiang, J.; Zha, Z.; Zhang, H.; Wang, C.; Zhang, J.

2014-04-01

Geospatial data resources are the foundation of the construction of geo portal which is designed to provide online geoinformation services for the government, enterprise and public. It is vital to keep geospatial data fresh, accurate and comprehensive in order to satisfy the requirements of application and development of geographic location, route navigation, geo search and so on. One of the major problems we are facing is data acquisition. For us, integrating multi-sources geospatial data is the mainly means of data acquisition. This paper introduced a practice integration approach of multi-source geospatial data with different data model, structure and format, which provided the construction of National Geospatial Information Service Platform of China (NGISP) with effective technical supports. NGISP is the China's official geo portal which provides online geoinformation services based on internet, e-government network and classified network. Within the NGISP architecture, there are three kinds of nodes: national, provincial and municipal. Therefore, the geospatial data is from these nodes and the different datasets are heterogeneous. According to the results of analysis of the heterogeneous datasets, the first thing we do is to define the basic principles of data fusion, including following aspects: 1. location precision; 2.geometric representation; 3. up-to-date state; 4. attribute values; and 5. spatial relationship. Then the technical procedure is researched and the method that used to process different categories of features such as road, railway, boundary, river, settlement and building is proposed based on the principles. A case study in Jiangsu province demonstrated the applicability of the principle, procedure and method of multi-source geospatial data integration.

An evidential path logic for multi-relational networks

Energy Technology Data Exchange (ETDEWEB)

Rodriguez, Marko A [Los Alamos National Laboratory; Geldart, Joe [UNIV OF DURHAM

2008-01-01

Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a knowledge network is to reason; that is, to alter the topology of the network according to an algorithm that uses the existing topological structure as its input. There exist many such reasoning algorithms. With respect to the Semantic Web, the bivalent, axiomatic reasoners of the RDF Schema (RDFS) and the Web Ontology Language (OWL) are the most prevalent. However, nothing prevents other forms of reasoning from existing in the Semantic Web. This article presents a non-bivalent, non-axiomatic, evidential logic and reasoner that is an algebraic ring over a multi-relational network and two binary operations that can be composed to perform various forms of inference. Given its multi-relational grounding, it is possible to use the presented evidential framework as another method for structuring knowledge and reasoning in the Semantic Web. The benefits of this framework are that it works with arbitrary, partial, and contradictory knowledge while, at the same time, supporting a tractable approximate reasoning process.

Students' network integration vs. persistence in introductory physics courses

Science.gov (United States)

Zwolak, Justyna; Brewe, Eric

2017-01-01

Society is constantly in flux, which demands the continuous development of our educational system to meet new challenges and impart the appropriate knowledge/skills to students. In order to improve student learning, among other things, the way we are teaching has significantly changed over the past few decades. We are moving away from traditional, lecture-based teaching towards more interactive, engagement-based strategies. A current, major challenge for universities is to increase student retention. While students' academic and social integration into an institution seems to be vital for student retention, research on the effect of interpersonal interactions is rare. I use of network analysis to investigate academic and social experiences of students in and beyond the classroom. In particular, there is a compelling case that transformed physics classes, such as Modeling Instruction (MI), promote persistence by the creation of learning communities that support the integration of students into the university. I will discuss recent results on pattern development in networks of MI students' interactions throughout the semester, as well as the effect of students' position within the network on their persistence in physics.

Integrated design strategy for product life-cycle management

Science.gov (United States)

Johnson, G. Patrick

2001-02-01

Two major trends suggest new considerations for environmentally conscious manufacturing (ECM) -- the continuation of dematerialization and the growing trend toward goods becoming services. A diversity of existing research could be integrated around those trends in ways that can enhance ECM. Major research-based achievements in information, computation, and communications systems, sophisticated and inexpensive sensing capabilities, highly automated and precise manufacturing technologies, and new materials continue to drive the phenomenon of dematerialization - the reduction of the material and energy content of per capita GDP. Knowledge is also growing about the sociology, economics, mathematics, management and organization of complex socio-economic systems. And that has driven a trend towards goods evolving into services. But even with these significant trends, the value of material, energy, information and human resources incorporated into the manufacture, use and disposal of modern products and services often far exceeds the benefits realized. Multi-disciplinary research integrating these drivers with advances in ECM concepts could be the basis for a new strategy of production. It is argued that a strategy of integrating information resources with physical and human resources over product life cycles, together with considering products as streams of service over time, could lead to significant economic payoff. That strategy leads to an overall design concept to minimize costs of all resources over the product life cycle to more fully capture benefits of all resources incorporated into modern products. It is possible by including life cycle monitoring, periodic component replacement, re-manufacture, salvage and human factor skill enhancement into initial design.

MULTI-SENSOR NETWORK FOR LANDSLIDES SIMULATION AND HAZARD MONITORING - DESIGN AND DEPLOYMENT

Directory of Open Access Journals (Sweden)

H. Wu

2012-08-01

Full Text Available This paper describes a newly developed multi-sensor network system for landslide and hazard monitoring. Landslide hazard is one of the most destructive natural disasters, which has severely affected human safety, properties and infrastructures. We report the results of designing and deploying the multi-sensor network, based on the simulated landslide model, to monitor typical landslide areas and with a goal to predict landslide hazard and mitigate damages. The integration and deployment of the prototype sensor network were carried out in an experiment area at Tongji University in Shanghai. In order to simulate a real landslide, a contractible landslide body is constructed in the experiment area by 7m*1.5m. Then, some different kind of sensors, such as camera, GPS, crackmeter, accelerometer, laser scanning system, inclinometer, etc., are installed near or in the landslide body. After the sensors are powered, continuous sampling data will be generated. With the help of communication method, such as GPRS, and certain transport devices, such as iMesh and 3G router, all the sensor data will be transported to the server and stored in Oracle. These are the current results of an ongoing project of the center. Further research results will be updated and presented in the near future.

Adaptive Voltage Control Strategy for Variable-Speed Wind Turbine Connected to a Weak Network

DEFF Research Database (Denmark)

Abulanwar, Elsayed; Hu, Weihao; Chen, Zhe

2016-01-01

and smoothness at the point of connection (POC) in order to maximise the wind power penetration into such networks. Intensive simulation case studies under different network topology and wind speed ranges reveal the effectiveness of the AVC scheme to effectively suppress the POC voltage variations particularly......Significant voltage fluctuations and power quality issues pose considerable constraints on the efficient integration of remotely located wind turbines into weak networks. Besides, 3p oscillations arising from the wind shear and tower shadow effects induce further voltage perturbations during...... continuous operation. This study investigates and analyses the repercussions raised by integrating a doubly-fed induction generator wind turbine into an ac network of different parameters and very weak conditions. An adaptive voltage control (AVC) strategy is proposed to retain voltage constancy...

Scalable and practical multi-objective distribution network expansion planning

NARCIS (Netherlands)

Luong, N.H.; Grond, M.O.W.; Poutré, La J.A.; Bosman, P.A.N.

2015-01-01

We formulate the distribution network expansion planning (DNEP) problem as a multi-objective optimization (MOO) problem with different objectives that distribution network operators (DNOs) would typically like to consider during decision making processes for expanding their networks. Objectives are

INTEGRATED CORPORATE STRATEGY MODEL

Directory of Open Access Journals (Sweden)

CATALINA SORIANA SITNIKOV

2014-02-01

Full Text Available Corporations are at present operating in demanding and highly unsure periods, facing a mixture of increased macroeconomic need, competitive and capital market dangers, and in many cases, the prospect for significant technical and regulative gap. Throughout these demanding and highly unsure times, the corporations must pay particular attention to corporate strategy. In present times, corporate strategy must be perceived and used as a function of various fields, covers, and characters as well as a highly interactive system. For the corporation's strategy to become a competitive advantage is necessary to understand and also to integrate it in a holistic model to ensure sustainable progress of corporation activities under the optimum conditions of profitability. The model proposed in this paper is aimed at integrating the two strategic models, Hoshin Kanri and Integrated Strategy Model, as well as their consolidation with the principles of sound corporate governance set out by the OECD.

Designing optimal bioethanol networks with purification for integrated biorefineries

International Nuclear Information System (INIS)

Shenoy, Akshay U.; Shenoy, Uday V.

2014-01-01

Highlights: • An analytical method is devised for bioethanol network integration with purification. • Minimum fresh bioethanol flow and pinch are found by the Unified Targeting Algorithm. • Optimal bioethanol networks are then synthesized by the Nearest Neighbors Algorithm. • Continuous targets and networks are developed over the purifier inlet flowrate range. • Case study of a biorefinery producing bioethanol from wheat shows large savings. - Abstract: Bioethanol networks with purification for processing pathways in integrated biorefineries are targeted and designed in this work by an analytical approach not requiring graphical constructions. The approach is based on six fundamental equations involving eight variables: two balance equations for the stream flowrate and the bioethanol load over the total network system; one equation for the above-pinch bioethanol load being picked up by the minimum fresh resource and the purified stream; and three equations for the purification unit. A solution strategy is devised by specifying the two variables associated with the purifier inlet stream. Importantly, continuous targeting is then possible over the entire purifier inlet flowrate range on deriving elegant formulae for the remaining six variables. The Unified Targeting Algorithm (UTA) is utilized to establish the minimum fresh bioethanol resource flowrate and identify the pinch purity. The fresh bioethanol resource flowrate target is shown to decrease linearly with purifier inlet flowrate provided the pinch is held by the same point. The Nearest Neighbors Algorithm (NNA) is used to methodically synthesize optimal networks matching bioethanol demands and sources. A case study of a biorefinery producing bioethanol from wheat with arabinoxylan (AX) coproduction is presented. It illustrates the versatility of the approach in generating superior practical designs with up to nearly 94% savings for integrated bioethanol networks, both with and without process

Improved routing strategies for data traffic in scale-free networks

International Nuclear Information System (INIS)

Wu, Zhi-Xi; Peng, Gang; Wong, Wing-Ming; Yeung, Kai-Hau

2008-01-01

We study the information packet routing process in scale-free networks by mimicking Internet traffic delivery. We incorporate both the global shortest paths information and local degree information of the network in the dynamic process, via two tunable parameters, α and β, to guide the packet routing. We measure the performance of the routing method by both the average transit times of packets and the critical packet generation rate (above which packet aggregation occurs in the network). We found that the routing strategies which integrate ingredients of both global and local topological information of the underlying networks perform much better than the traditional shortest path routing protocol taking into account the global topological information only. Moreover, by doing comparative studies with some related works, we found that the performance of our proposed method shows universal efficiency characteristic against the amount of traffic

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Li Ran

2017-01-01

Full Text Available Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability.

Integrable multi parametric SU(N) chain

International Nuclear Information System (INIS)

Foerster, Angela; Roditi, Itzhak; Rodrigues, Ligia M.C.S.

1996-03-01

We analyse integrable models associated to a multi parametric SU(N) R-matrix. We show that the Hamiltonians describe SU(N) chains with twisted boundary conditions and that the underlying algebraic structure is the multi parametric deformation of SU(N) enlarged by the introduction of a central element. (author). 15 refs

Cancer-Related Triplets of mRNA-lncRNA-miRNA Revealed by Integrative Network in Uterine Corpus Endometrial Carcinoma

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Chenglin Liu

2017-01-01

Full Text Available The regulation of transcriptome expression level is a complex process involving multiple-level interactions among molecules such as protein coding RNA (mRNA, long noncoding RNA (lncRNA, and microRNA (miRNA, which are essential for the transcriptome stability and maintenance and regulation of body homeostasis. The availability of multilevel expression data enables a comprehensive view of the regulatory network. In this study, we analyzed the coding and noncoding gene expression profiles of 301 patients with uterine corpus endometrial carcinoma (UCEC. A new method was proposed to construct a genome-wide integrative network based on variance inflation factor (VIF regression method. The cross-regulation relations of mRNA, lncRNA, and miRNA were then selected based on clique-searching algorithm from the network, when any two molecules of the three were shown as interacting according to the integrative network. Such relation, which we call the mRNA-lncRNA-miRNA triplet, demonstrated the complexity in transcriptome regulation process. Finally, six UCEC-related triplets were selected in which the mRNA participates in endometrial carcinoma pathway, such as CDH1 and TP53. The multi-type RNAs are proved to be cross-regulated as to each of the six triplets according to literature. All the triplets demonstrated the association with the initiation and progression of UCEC. Our method provides a comprehensive strategy for the investigation of transcriptome regulation mechanism.

Multi-business firms, knowledge flows and intra-network open innovations

OpenAIRE

Villasalero, Manuel

2015-01-01

The increasing competition in the marketplace has led firms to change their innovation patterns to a more open system according to which they rely on networks to manage knowledge resources and innovate. The so-called open innovation paradigm has been developed by taking single-business firms and external networks as cornerstones of the standard model. However, in the case of multi-business firms, the role of internal networks has been neglected. Business units within multi-business corporatio...

Search for Directed Networks by Different Random Walk Strategies

Science.gov (United States)

Zhu, Zi-Qi; Jin, Xiao-Ling; Huang, Zhi-Long

2012-03-01

A comparative study is carried out on the efficiency of five different random walk strategies searching on directed networks constructed based on several typical complex networks. Due to the difference in search efficiency of the strategies rooted in network clustering, the clustering coefficient in a random walker's eye on directed networks is defined and computed to be half of the corresponding undirected networks. The search processes are performed on the directed networks based on Erdös—Rényi model, Watts—Strogatz model, Barabási—Albert model and clustered scale-free network model. It is found that self-avoiding random walk strategy is the best search strategy for such directed networks. Compared to unrestricted random walk strategy, path-iteration-avoiding random walks can also make the search process much more efficient. However, no-triangle-loop and no-quadrangle-loop random walks do not improve the search efficiency as expected, which is different from those on undirected networks since the clustering coefficient of directed networks are smaller than that of undirected networks.

Power consumption optimization strategy for wireless networks

DEFF Research Database (Denmark)

Cornean, Horia; Kumar, Sanjay; Marchetti, Nicola

2011-01-01

in order to reduce the total power consumption in a multi cellular network. We present an algorithm for power optimization under no interference and in presence of interference conditions, targeting to maximize the network capacity. The convergence of the algorithm is guaranteed if the interference...

Deep multi-scale convolutional neural network for hyperspectral image classification

Science.gov (United States)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Challenges of Integrating NASA's Space Communications Networks

Science.gov (United States)

Reinert, Jessica; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Challenges of Integrating NASAs Space Communication Networks

Science.gov (United States)

Reinert, Jessica M.; Barnes, Patrick

2013-01-01

The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

Integration of RFID and Wireless Sensor Networks

Institute of Scientific and Technical Information of China (English)

Miodrag; Bolic; Amiya; Nayak; Ivan; Stojmenovi.

2007-01-01

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide limitless future potentials. However,RFID and sensor networks almost are under development in parallel way. Integration of RFID and wireless sensor networks attracts little attention from research community. This paper first presents a brief introduction on RFID,and then investigates recent research works,new products/patents and applications that integrate RFID with sensor networks. Four types of integration are discussed. They are integrating tags with sensors,integrating tags with wireless sensor nodes,integrating readers with wireless sensor nodes and wire-less devices,and mix of RFID and sensors. New challenges and future works are discussed in the end.

Identifying the community structure of the food-trade international multi-network

Science.gov (United States)

Torreggiani, S.; Mangioni, G.; Puma, M. J.; Fagiolo, G.

2018-05-01

Achieving international food security requires improved understanding of how international trade networks connect countries around the world through the import-export flows of food commodities. The properties of international food trade networks are still poorly documented, especially from a multi-network perspective. In particular, nothing is known about the multi-network’s community structure. Here we find that the individual crop-specific layers of the multi-network have densely connected trading groups, a consistent characteristic over the period 2001–2011. Further, the multi-network is characterized by low variability over this period but with substantial heterogeneity across layers in each year. In particular, the layers are mostly assortative: more-intensively connected countries tend to import from and export to countries that are themselves more connected. We also fit econometric models to identify social, economic and geographic factors explaining the probability that any two countries are co-present in the same community. Our estimates indicate that the probability of country pairs belonging to the same food trade community depends more on geopolitical and economic factors—such as geographical proximity and trade-agreement co-membership—than on country economic size and/or income. These community-structure findings of the multi-network are especially valuable for efforts to understand past and emerging dynamics in the global food system, especially those that examine potential ‘shocks’ to global food trade.

Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

International Nuclear Information System (INIS)

Yang Hongyong; Lu Lan; Cao Kecai; Zhang Siying

2010-01-01

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration. (interdisciplinary physics and related areas of science and technology)

Multi-modular neural networks for the classification of e+e- hadronic events

International Nuclear Information System (INIS)

Proriol, J.

1994-01-01

Some multi-modular neural network methods of classifying e + e - hadronic events are presented. We compare the performances of the following neural networks: MLP (multilayer perceptron), MLP and LVQ (learning vector quantization) trained sequentially, and MLP and RBF (radial basis function) trained sequentially. We introduce a MLP-RBF cooperative neural network. Our last study is a multi-MLP neural network. (orig.)

Offensive Strategy in the 2D Soccer Simulation League Using Multi-Group Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Shengbing Chen

2016-02-01

Full Text Available The 2D soccer simulation league is one of the best test beds for the research of artificial intelligence (AI. It has achieved great successes in the domain of multi-agent cooperation and machine learning. However, the problem of integral offensive strategy has not been solved because of the dynamic and unpredictable nature of the environment. In this paper, we present a novel offensive strategy based on multi-group ant colony optimization (MACO-OS. The strategy uses the pheromone evaporation mechanism to count the preference value of each attack action in different environments, and saves the values of success rate and preference in an attack information tree in the background. The decision module of the attacker then selects the best attack action according to the preference value. The MACO-OS approach has been successfully implemented in our 2D soccer simulation team in RoboCup competitions. The experimental results have indicated that the agents developed with this strategy, along with related techniques, delivered outstanding performances.

Multi-processor network implementations in Multibus II and VME

International Nuclear Information System (INIS)

Briegel, C.

1992-01-01

ACNET (Fermilab Accelerator Controls Network), a proprietary network protocol, is implemented in a multi-processor configuration for both Multibus II and VME. The implementations are contrasted by the bus protocol and software design goals. The Multibus II implementation provides for multiple processors running a duplicate set of tasks on each processor. For a network connected task, messages are distributed by a network round-robin scheduler. Further, messages can be stopped, continued, or re-routed for each task by user-callable commands. The VME implementation provides for multiple processors running one task across all processors. The process can either be fixed to a particular processor or dynamically allocated to an available processor depending on the scheduling algorithm of the multi-processing operating system. (author)

A multi-layered network of the (Colombian) sovereign securities market

NARCIS (Netherlands)

Renneboog, Luc; Leon Rincon, Carlos; Pérez, Jhonatan; Alexandrova-Kabadjova, Bilana; Diehl, Martin; Heuver, Richard; Martinez-Jaramillo, Serafín

2015-01-01

We study the network of Colombian sovereign securities settlements. With data from the settlement market infrastructure we study financial institutions’ transactions from three different trading and registering individual networks that we combine into a multi-layer network. Examining this network of

DETERMINANTS OF NETWORK OUTCOMES: THE IMPACT OF MANAGEMENT STRATEGIES.

Science.gov (United States)

Ysa, Tamyko; Sierra, Vicenta; Esteve, Marc

2014-09-01

The literature on network management is extensive. However, it generally explores network structures, neglecting the impact of management strategies. In this article we assess the effect of management strategies on network outcomes, providing empirical evidence from 119 urban revitalization networks. We go beyond current work by testing a path model for the determinants of network outcomes and considering the interactions between the constructs: management strategies, trust, complexity, and facilitative leadership. Our results suggest that management strategies have a strong effect on network outcomes and that they enhance the level of trust. We also found that facilitative leadership has a positive impact on network management as well as on trust in the network. Our findings also show that complexity has a negative impact on trust. A key finding of our research is that managers may wield more influence on network dynamics than previously theorized.

Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

Directory of Open Access Journals (Sweden)

Aydin Torkabadi

2018-03-01

Full Text Available Purpose: Just-In-Time (JIT production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP, and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.

Effects Comparison of Different Resilience Enhancing Strategies for Municipal Water Distribution Network: A Multidimensional Approach

Directory of Open Access Journals (Sweden)

Xudong Zhao

2015-01-01

Full Text Available Water distribution network (WDN is critical to the city service, economic rehabilitation, public health, and safety. Reconstructing the WDN to improve its resilience in seismic disaster is an important and ongoing issue. Although a considerable body of research has examined the effects of different reconstruction strategies on seismic resistance, it is still hard for decision-makers to choose optimal resilience enhancing strategy. Taking the pipeline ductile retrofitting and network meshed expansion as demonstration, we proposed a feasible framework to contrast the resilience enhancing effects of two reconstruction strategies—units retrofitting strategy and network optimization strategy—in technical and organizational dimension. We also developed a new performance response function (PRF which is based on network equilibrium theory to conduct the effects comparison in integrated technical and organizational dimension. Through the case study of municipal WDN in Lianyungang, China, the comparison results were thoroughly shown and the holistic decision-making support was provided.

An integrated artificial neural networks approach for predicting global radiation

International Nuclear Information System (INIS)

Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

2009-01-01

This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

Toward a Theory of Industrial Supply Networks: A Multi-Level Perspective via Network Analysis

Directory of Open Access Journals (Sweden)

Yi Zuo

2017-07-01

Full Text Available In most supply chains (SCs, transaction relationships between suppliers and customers are commonly considered to be an extrapolation from a linear perspective. However, this traditional linear concept of an SC is egotistic and oversimplified and does not sufficiently reflect the complex and cyclical structure of supplier-customer relationships in current economic and industrial situations. The interactional relationships and topological characteristics between suppliers and customers should be analyzed using supply networks (SNs rather than traditional linear SCs. Therefore, this paper reconceptualizes SCs as SNs in complex adaptive systems (CAS, and presents three main contributions. First, we propose an integrated framework of CAS network by synthesizing multi-level network analysis from the network-, community- and vertex-perspective. The CAS perspective enables us to understand the advances of SN properties. Second, in order to emphasize the CAS properties of SNs, we conducted a real-world SN based on the Japanese industry and describe an advanced investigation of SN theory. The CAS properties help in enriching the SN theory, which can benefit SN management, community economics and industrial resilience. Third, we propose a quantitative metric of entropy to measure the complexity and robustness of SNs. The results not only support a specific understanding of the structural outcomes relevant to SNs, but also deliver efficient and effective support to the management and design of SNs.

Routing strategies in traffic network and phase transition in network ...

Indian Academy of Sciences (India)

The dynamics of information traffic over scale-free networks has been investigated systematically. A series of routing strategies of data packets have been proposed, including the local routing strategy, the next-nearest-neighbour routing strategy, and the mixed routing strategy based on local static and dynamic information.

The Genome-Scale Integrated Networks in Microorganisms

Directory of Open Access Journals (Sweden)

Tong Hao

2018-02-01

Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units

Directory of Open Access Journals (Sweden)

Jinjiao Hou

2018-05-01

Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.

Dynamic clustering scheme based on the coordination of management and control in multi-layer and multi-region intelligent optical network

Science.gov (United States)

Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi

2011-12-01

A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.

Multi-disciplinary coupling for integrated design of propulsion systems

Science.gov (United States)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions for determining the true response of propulsion systems. Results are presented for propulsion system responses including multi-discipline coupling effects via (1) coupled multi-discipline tailoring, (2) an integrated system of multidisciplinary simulators, (3) coupled material-behavior/fabrication-process tailoring, (4) sensitivities using a probabilistic simulator, and (5) coupled materials/structures/fracture/probabilistic behavior simulator. The results show that the best designs can be determined if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated interactive multi-discipline numerical propulsion system simulator.

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

Directory of Open Access Journals (Sweden)

Qian Li

Full Text Available BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671 between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation

A network-based multi-target computational estimation scheme for anticoagulant activities of compounds.

Science.gov (United States)

Li, Qian; Li, Xudong; Li, Canghai; Chen, Lirong; Song, Jun; Tang, Yalin; Xu, Xiaojie

2011-03-22

Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by

Habitat Demonstration Unit (HDU) Pressurized Excursion Module (PEM) Systems Integration Strategy

Science.gov (United States)

Gill, Tracy; Merbitz, Jerad; Kennedy, Kriss; Tri, Terry; Toups, Larry; Howe, A. Scott

2011-01-01

The Habitat Demonstration Unit (HDU) project team constructed an analog prototype lunar surface laboratory called the Pressurized Excursion Module (PEM). The prototype unit subsystems were integrated in a short amount of time, utilizing a rapid prototyping approach that brought together over 20 habitation-related technologies from a variety of NASA centers. This paper describes the system integration strategies and lessons learned, that allowed the PEM to be brought from paper design to working field prototype using a multi-center team. The system integration process was based on a rapid prototyping approach. Tailored design review and test and integration processes facilitated that approach. The use of collaboration tools including electronic tools as well as documentation enabled a geographically distributed team take a paper concept to an operational prototype in approximately one year. One of the major tools used in the integration strategy was a coordinated effort to accurately model all the subsystems using computer aided design (CAD), so conflicts were identified before physical components came together. A deliberate effort was made following the deployment of the HDU PEM for field operations to collect lessons learned to facilitate process improvement and inform the design of future flight or analog versions of habitat systems. Significant items within those lessons learned were limitations with the CAD integration approach and the impact of shell design on flexibility of placing systems within the HDU shell.

Coping strategies for domestic violence against pregnant female adolescents: integrative review.

Science.gov (United States)

Macedo, Cibele Monteiro; Miura, Paula Orchiucci; Barrientos, Dora Mariela Salcedo; Lopes, Gisele Almeida; Egry, Emiko Yoshikawa

2018-01-01

To investigate and analyze in the scientific literature coping strategies for domestic violence against pregnant female adolescents. This is an integrative literature review, conducted from July to August 2017 on LILACS, SciELO and PubMed, using the descriptors and the MeSH terms: confrontation, violence, adolescent, pregnant women, prenatal care. The sample comprised 9 articles that were organized and characterized according to year, country of study and coping strategy used. The main forms of coping involved the active search for cases and the primary care approach with all family members. Individualized prenatal care, the change in professional training and networking activities were pointed out as important components of the strategies for coping with violence against pregnant adolescents.

Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

Science.gov (United States)

Milana; Khan, M. K.; Munive, J. E.

2014-07-01

The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective.

Development the conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation

International Nuclear Information System (INIS)

Milana; Khan, M K; Munive, J E

2014-01-01

The importance of maintenance has escalated significantly by the increasing of automation in manufacturing process. This condition switches traditional maintenance perspective of inevitable cost into the business competitive driver. Consequently, maintenance strategy and operation decision needs to be synchronized to business and manufacturing concerns. This paper shows the development of conceptual design of Knowledge Based System for Integrated Maintenance Strategy and Operation (KBIMSO). The framework of KBIMSO is elaborated to show the process of how the KBIMSO works to reach the maintenance decision. By considering the multi-criteria of maintenance decision making, the KB system embedded with GAP and AHP to support integrated maintenance strategy and operation which is novel in this area. The KBIMSO is useful to review the existing maintenance system and give reasonable recommendation of maintenance decisions in respect to business and manufacturing perspective

Wolf pack hunting strategy for automatic generation control of an islanding smart distribution network

International Nuclear Information System (INIS)

Xi, Lei; Zhang, Zeyu; Yang, Bo; Huang, Linni; Yu, Tao

2016-01-01

Highlights: • A mixed homogeneous and heterogeneous multi-agent based wolf pack hunting (WPH) method is proposed. • WPH can effectively handle the ever-increasing penetration of renewable energy in smart grid. • An AGC power dispatch, coordinated control, and electric power autonomy of an ISDN is achieved. - Abstract: As the conventional centralized automatic generation control (AGC) is inadequate to handle the ever-increasing penetration of renewable energy and the requirement of plug-and-play of smart grid, this paper proposes a mixed homogeneous and heterogeneous multi-agent based wolf pack hunting (WPH) strategy to achieve a fast AGC power dispatch, optimal coordinated control, and electric power autonomy of an islanding smart distribution network (ISDN). A virtual consensus variable is employed to deal with the topology variation resulted from the excess of power limits and to achieve the plug-and-play of AGC units. Then an integrated objective of frequency deviation and short-term economic dispatch is developed, such that all units can maintain an optimal operation in the presence of load disturbances. Four case studies are undertaken to an ISDN with various distributed generations and microgrids. Simulation results demonstrate that WPH has a greater robustness and a faster dynamic optimization than that of conventional approaches, which can increase the utilization rate of the renewable energy and effectively resolve the coordination and electric power autonomy of ISDN.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

Science.gov (United States)

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Multi-modal Social Networks: A MRF Learning Approach

Science.gov (United States)

2016-06-20

Network forensics: random infection vs spreading epidemic , Proceedings of ACM Sigmetrics. 11-JUN-12, London, UK. : , TOTAL: 4 06/09/2016 Received Paper...Multi-modal Social Networks A MRF Learning Approach The work primarily focused on two lines of research. 1. We propose new greedy algorithms...Box 12211 Research Triangle Park, NC 27709-2211 social networks , learning and inference REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT

Improved Efficient Routing Strategy on Scale-Free Networks

Science.gov (United States)

Jiang, Zhong-Yuan; Liang, Man-Gui

Since the betweenness of nodes in complex networks can theoretically represent the traffic load of nodes under the currently used routing strategy, we propose an improved efficient (IE) routing strategy to enhance to the network traffic capacity based on the betweenness centrality. Any node with the highest betweenness is susceptible to traffic congestion. An efficient way to improve the network traffic capacity is to redistribute the heavy traffic load from these central nodes to non-central nodes, so in this paper, we firstly give a path cost function by considering the sum of node betweenness with a tunable parameter β along the actual path. Then, by minimizing the path cost, our IE routing strategy achieved obvious improvement on the network transport efficiency. Simulations on scale-free Barabási-Albert (BA) networks confirmed the effectiveness of our strategy, when compared with the efficient routing (ER) and the shortest path (SP) routing.

Multi-Input Convolutional Neural Network for Flower Grading

Directory of Open Access Journals (Sweden)

Yu Sun

2017-01-01

Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

A DC Microgrid Coordinated Control Strategy Based on Integrator Current-Sharing

Directory of Open Access Journals (Sweden)

Liyuan Gao

2017-08-01

Full Text Available The DC microgrid has become a new trend for microgrid study with the advantages of high reliability, simple control and low losses. With regard to the drawbacks of the traditional droop control strategies, an improved DC droop control strategy based on integrator current-sharing is introduced. In the strategy, the principle of eliminating deviation through an integrator is used, constructing the current-sharing term in order to make the power-sharing between different distributed generation (DG units uniform and reasonable, which can reduce the circulating current between DG units. Furthermore, at the system coordinated control level, a hierarchical/droop control strategy based on the DC bus voltage is proposed. In the strategy, the operation modes of the AC main network and micro-sources are determined through detecting the DC voltage variation, which can ensure the power balance of the DC microgrid under different operating conditions. Meanwhile, communication is not needed between different DG units, while each DG unit needs to sample the DC bus voltage, which retains the plug-and-play feature of the DC microgrid. The proposed control strategy is validated by simulation on a DC microgrid with permanent magnet synchronous generator-based wind turbines, solar arrays and energy storage batteries, which can be applied to small commercial or residential buildings.

Strategies to facilitate integrated care for people with alcohol and other drug problems: a systematic review.

Science.gov (United States)

Savic, Michael; Best, David; Manning, Victoria; Lubman, Dan I

2017-04-07

in areas beyond a clinician's primary area of practice was a common strategy for facilitating referral and integrated care, as was joint care planning. Despite considerable limitations and gaps in the literature in terms of the evaluation of integrated care strategies, particularly between AOD services, our review highlights several strategies that could be useful at multiple levels. Given the interconnectedness of integrated care strategies identified, implementation of multi-level strategies rather than single strategies is likely to be preferable.

European networks in structural integrity

International Nuclear Information System (INIS)

Crutzen, S.; Davies, M.; Hemsworth, B.; Hurst, R.; Kussmaul, K.

1994-01-01

Several institutions and electrical utilities in Europe, including the Joint Research Centre (JRC) have the capability to deal problems posed by the operation and ageing of structural components and with their structural integrity assessment. These institutions and the JRC have developed cooperative programmes now organised in networks. They include utilities, engineering companies, R and D laboratories and Regulatory Bodies. Networks are organised and managed like the successful PISC programme: The Institute for Advanced Materials of JRC plays the role of Operating Agent and Manager of these networks: ENIQ, AMES, NESC, each of them dealing with a specific aspect of fitness for purpose of materials in structural components. There exist strong links between the networks and EC Working Groups on Structural Integrity Codes and Standards. (orig.)

Reference Architecture for Multi-Layer Software Defined Optical Data Center Networks

Directory of Open Access Journals (Sweden)

Casimer DeCusatis

2015-09-01

Full Text Available As cloud computing data centers grow larger and networking devices proliferate; many complex issues arise in the network management architecture. We propose a framework for multi-layer; multi-vendor optical network management using open standards-based software defined networking (SDN. Experimental results are demonstrated in a test bed consisting of three data centers interconnected by a 125 km metropolitan area network; running OpenStack with KVM and VMW are components. Use cases include inter-data center connectivity via a packet-optical metropolitan area network; intra-data center connectivity using an optical mesh network; and SDN coordination of networking equipment within and between multiple data centers. We create and demonstrate original software to implement virtual network slicing and affinity policy-as-a-service offerings. Enhancements to synchronous storage backup; cloud exchanges; and Fibre Channel over Ethernet topologies are also discussed.

High-precision multi-node clock network distribution.

Science.gov (United States)

Chen, Xing; Cui, Yifan; Lu, Xing; Ci, Cheng; Zhang, Xuesong; Liu, Bo; Wu, Hong; Tang, Tingsong; Shi, Kebin; Zhang, Zhigang

2017-10-01

A high precision multi-node clock network for multiple users was built following the precise frequency transmission and time synchronization of 120 km fiber. The network topology adopts a simple star-shaped network structure. The clock signal of a hydrogen maser (synchronized with UTC) was recovered from a 120 km telecommunication fiber link and then was distributed to 4 sub-stations. The fractional frequency instability of all substations is in the level of 10 -15 in a second and the clock offset instability is in sub-ps in root-mean-square average.

Strategies for optical transport network recovery under epidemic network failures

DEFF Research Database (Denmark)

Ruepp, Sarah Renée; Fagertun, Anna Manolova; Kosteas, Vasileios

2015-01-01

The current trend in deploying automatic control plane solutions for increased flexibility in the optical transport layer leads to numerous advantages for both the operators and the customers, but also pose challenges related to the stability of the network and its ability to operate in a robust...... manner under different failure scenarios. This work evaluates two rerouting strategies and proposes four policies for failure handling in a connection-oriented optical transport network, under generalized multiprotocol label switching control plane. The performance of the strategies and the policies......, and that there exist a clear trade-off between policy performance and network resource consumption, which must be addressed by network operators for improved robustness of their transport infrastructures. Applying proactive methods for avoiding areas where epidemic failures spread results in 50% less connections...

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

Science.gov (United States)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Interference-aware power control for multi-radio multi-channel wireless mesh networks

CSIR Research Space (South Africa)

Olwal, TO

2009-09-01

Full Text Available are well known in [9], [6]. The operation of multi-radio multi-channel (MRMC) WMNs generally requires sustainable energy supply. Substantial deployments of WMNs have recently been witnessed in rural and remote communities [4]. In such applications...]. Power resources are dynamically adjusted by each NIC using intra and inter-subsystem (channel) states. Due to the decentralized nature, each MP assumes imperfect knowledge about the global network. Further we assume that there exists...

Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

Integrated circuit and method of arbitration in a network on an integrated circuit.

NARCIS (Netherlands)

2011-01-01

The invention relates to an integrated circuit and to a method of arbitration in a network on an integrated circuit. According to the invention, a method of arbitration in a network on an integrated circuit is provided, the network comprising a router unit, the router unit comprising a first input

Multi-channel distributed coordinated function over single radio in wireless sensor networks.

Science.gov (United States)

Campbell, Carlene E-A; Loo, Kok-Keong Jonathan; Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

2011-01-01

Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band.

Integrated monitoring of multi-domain backbone connections Operational experience in the LHC optical private network

CERN Document Server

Marcu, Patricia; Fritz, Wolfgang; Yampolskiy, Mark; Hommel, Wolfgang

2011-01-01

Novel large scale research projects often require cooperation between various different project partners that are spread among the entire world. They do not only need huge computing resources, but also a reliable network to operate on. The Large Hadron Collider (LHC) at CERN is a representative example for such a project. Its experiments result in a vast amount of data, which is interesting for researchers around the world. For transporting the data from CERN to 11 data processing and storage sites, an optical private network (OPN) has been constructed. As the experiment data is highly valuable, LHC defines very high requirements to the underlying network infrastructure. In order to fulfil those requirements, the connections have to be managed and monitored permanently. In this paper, we present the integrated monitoring solution developed for the LHCOPN. We first outline the requirements and show how they are met on the single network layers. After that, we describe, how those single measurements can be comb...

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim

2016-01-01

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.

2016-01-06

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Robustness analysis of interdependent networks under multiple-attacking strategies

Science.gov (United States)

Gao, Yan-Li; Chen, Shi-Ming; Nie, Sen; Ma, Fei; Guan, Jun-Jie

2018-04-01

The robustness of complex networks under attacks largely depends on the structure of a network and the nature of the attacks. Previous research on interdependent networks has focused on two types of initial attack: random attack and degree-based targeted attack. In this paper, a deliberate attack function is proposed, where six kinds of deliberate attacking strategies can be derived by adjusting the tunable parameters. Moreover, the robustness of four types of interdependent networks (BA-BA, ER-ER, BA-ER and ER-BA) with different coupling modes (random, positive and negative correlation) is evaluated under different attacking strategies. Interesting conclusions could be obtained. It can be found that the positive coupling mode can make the vulnerability of the interdependent network to be absolutely dependent on the most vulnerable sub-network under deliberate attacks, whereas random and negative coupling modes make the vulnerability of interdependent network to be mainly dependent on the being attacked sub-network. The robustness of interdependent network will be enhanced with the degree-degree correlation coefficient varying from positive to negative. Therefore, The negative coupling mode is relatively more optimal than others, which can substantially improve the robustness of the ER-ER network and ER-BA network. In terms of the attacking strategies on interdependent networks, the degree information of node is more valuable than the betweenness. In addition, we found a more efficient attacking strategy for each coupled interdependent network and proposed the corresponding protection strategy for suppressing cascading failure. Our results can be very useful for safety design and protection of interdependent networks.

Multi-objective optimization in computer networks using metaheuristics

CERN Document Server

Donoso, Yezid

2007-01-01

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the compu...

Self-Tuning Fully-Connected PID Neural Network System for Distributed Temperature Sensing and Control of Instrument with Multi-Modules

Directory of Open Access Journals (Sweden)

Zhen Zhang

2016-10-01

Full Text Available High integration of multi-functional instruments raises a critical issue in temperature control that is challenging due to its spatial–temporal complexity. This paper presents a multi-input multi-output (MIMO self-tuning temperature sensing and control system for efficiently modulating the temperature environment within a multi-module instrument. The smart system ensures that the internal temperature of the instrument converges to a target without the need of a system model, thus making the control robust. The system consists of a fully-connected proportional–integral–derivative (PID neural network (FCPIDNN and an on-line self-tuning module. The experimental results show that the presented system can effectively control the internal temperature under various mission scenarios, in particular, it is able to self-reconfigure upon actuator failure. The system provides a new scheme for a complex and time-variant MIMO control system which can be widely applied for the distributed measurement and control of the environment in instruments, integration electronics, and house constructions.

A Framework for Joint Optical-Wireless Resource Management in Multi-RAT, Heterogeneous Mobile Networks

DEFF Research Database (Denmark)

Zakrzewska, Anna; Popovska Avramova, Andrijana; Christiansen, Henrik Lehrmann

2013-01-01

Mobile networks are constantly evolving: new Radio Access Technologies (RATs) are being introduced, and backhaul architectures like Cloud-RAN (C-RAN) and distributed base stations are being proposed. Furthermore, small cells are being deployed to enhance network capacity. The end-users wish...... to be always connected to a high-quality service (high bit rates, low latency), thus causing a very complex network control task from an operator’s point of view. We thus propose a framework allowing joint overall network resource management. This scheme covers different types of network heterogeneity (multi......-RAT, multi-layer, multi-architecture) by introducing a novel, hierarchical approach to network resource management. Self-Organizing Networks (SON) and cognitive network behaviors are covered as well as more traditional mobile network features. The framework is applicable to all phases of network operation...

Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g

Directory of Open Access Journals (Sweden)

Guozheng Li

2018-03-01

Full Text Available The integration of renewable energies into combined cooling, heating, and power (CCHP systems has become increasingly popular in recent years. However, the optimization of renewable energies integrated CCHP (RECCHP systems (i.e., optimal component configurations is far from being well addressed, especially in isolated mode. This study aims to fill this research gap. A multi-objective optimization model characterizing the system reliability, system cost, and environmental sustainability is constructed. In this model, the objectives include minimization of annual total cost (ATC, carbon dioxide emission (CDE, and loss of energy supply probability (LESP. The decision variables representing the configuration of the RECCHP system include the number of photovoltaic (PV panels and wind turbines (WTs, the tilt angle of PV panels, the height of WTs, the maximum fuel consumption, and the capacity of battery and heat storage tanks (HSTs. The multi-objective model is solved by a multi-objective evolutionary algorithm, namely, the preference-inspired coevolutionary algorithm (PICEA-g, resulting in a set of Pareto optimal (trade-off solutions. Then, a decision-making process is demonstrated, selecting a preferred solution amongst those trade-off solutions by further considering the decision-maker preferences. Furthermore, on the optimization of the RECCHP system, operational strategies (i.e., following electric load, FEL, and following thermal load, FTL are considered, respectively. Experimental results show that the FEL and FTL strategies lead to different optimal configurations. In general, the FTL is recommended in summer and winter, while the FEL is more suitable for spring and autumn. Compared with traditional energy systems, RECCHP has better economic and environmental advantages.

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Multi-agent modelling framework for water, energy and other resource networks

Science.gov (United States)

Knox, S.; Selby, P. D.; Meier, P.; Harou, J. J.; Yoon, J.; Lachaut, T.; Klassert, C. J. A.; Avisse, N.; Mohamed, K.; Tomlinson, J.; Khadem, M.; Tilmant, A.; Gorelick, S.

2015-12-01

Bespoke modelling tools are often needed when planning future engineered interventions in the context of various climate, socio-economic and geopolitical futures. Such tools can help improve system operating policies or assess infrastructure upgrades and their risks. A frequently used approach is to simulate and/or optimise the impact of interventions in engineered systems. Modelling complex infrastructure systems can involve incorporating multiple aspects into a single model, for example physical, economic and political. This presents the challenge of combining research from diverse areas into a single system effectively. We present the Pynsim 'Python Network Simulator' framework, a library for building simulation models capable of representing, the physical, institutional and economic aspects of an engineered resources system. Pynsim is an open source, object oriented code aiming to promote integration of different modelling processes through a single code library. We present two case studies that demonstrate important features of Pynsim's design. The first is a large interdisciplinary project of a national water system in the Middle East with modellers from fields including water resources, economics, hydrology and geography each considering different facets of a multi agent system. It includes: modelling water supply and demand for households and farms; a water tanker market with transfer of water between farms and households, and policy decisions made by government institutions at district, national and international level. This study demonstrates that a well-structured library of code can provide a hub for development and act as a catalyst for integrating models. The second focuses on optimising the location of new run-of-river hydropower plants. Using a multi-objective evolutionary algorithm, this study analyses different network configurations to identify the optimal placement of new power plants within a river network. This demonstrates that Pynsim can be

Social network analysis via multi-state reliability and conditional influence models

International Nuclear Information System (INIS)

Schneider, Kellie; Rainwater, Chase; Pohl, Ed; Hernandez, Ivan; Ramirez-Marquez, Jose Emmanuel

2013-01-01

This paper incorporates multi-state reliability measures into the assessment of a social network in which influence is treated as a multi-state commodity that flows through the network. The reliability of the network is defined as the probability that at least a certain level of influence reaches an intended target. We consider an individual's influence level as a function of the influence levels received from preceding actors in the network. We define several communication functions which describe the level of influence a particular actor will pass along to other actors within the network. Illustrative examples are presented, and the network reliability under the various communication influence levels is computed using exhaustive enumeration for a small example and Monte Carlo simulation for larger, more realistic sized examples.

Multi-disciplinary coupling effects for integrated design of propulsion systems

Science.gov (United States)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions which govern the accurate response of propulsion systems. Results are presented for propulsion system responses including multi-disciplinary coupling effects using coupled multi-discipline thermal, structural, and acoustic tailoring; an integrated system of multi-disciplinary simulators; coupled material behavior/fabrication process tailoring; sensitivities using a probabilistic simulator; and coupled materials, structures, fracture, and probabilistic behavior simulator. The results demonstrate that superior designs can be achieved if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated coupled multi-discipline numerical propulsion system simulator.

Pheromone Static Routing Strategy for Complex Networks

Science.gov (United States)

Hu, Mao-Bin; Henry, Y. K. Lau; Ling, Xiang; Jiang, Rui

2012-12-01

We adopt the concept of using pheromones to generate a set of static paths that can reach the performance of global dynamic routing strategy [Phys. Rev. E 81 (2010) 016113]. The path generation method consists of two stages. In the first stage, a pheromone is dropped to the nodes by packets forwarded according to the global dynamic routing strategy. In the second stage, pheromone static paths are generated according to the pheromone density. The output paths can greatly improve traffic systems' overall capacity on different network structures, including scale-free networks, small-world networks and random graphs. Because the paths are static, the system needs much less computational resources than the global dynamic routing strategy.

Energy management and multi-layer control of networked microgrids

Science.gov (United States)

Zamora, Ramon

Networked microgrids is a group of neighboring microgrids that has ability to interchange power when required in order to increase reliability and resiliency. Networked microgrid can operate in different possible configurations including: islanded microgrid, a grid-connected microgrid without a tie-line converter, a grid-connected microgrid with a tie-line converter, and networked microgrids. These possible configurations and specific characteristics of renewable energy offer challenges in designing control and management algorithms for voltage, frequency and power in all possible operating scenarios. In this work, control algorithm is designed based on large-signal model that enables microgrid to operate in wide range of operating points. A combination between PI controller and feed-forward measured system responses will compensate for the changes in operating points. The control architecture developed in this work has multi-layers and the outer layer is slower than the inner layer in time response. The main responsibility of the designed controls are to regulate voltage magnitude and frequency, as well as output power of the DG(s). These local controls also integrate with a microgrid level energy management system or microgrid central controller (MGCC) for power and energy balance for. the entire microgrid in islanded, grid-connected, or networked microgid mode. The MGCC is responsible to coordinate the lower level controls to have reliable and resilient operation. In case of communication network failure, the decentralized energy management will operate locally and will activate droop control. Simulation results indicate the superiority of designed control algorithms compared to existing ones.

Building secure network by integrated technology

International Nuclear Information System (INIS)

An Dehai; Xu Rongsheng; Liu Baoxu

2000-01-01

The author introduces a method which can realize the most powerful network security prevention by the network security integrated technologies such as firewall, realtime monitor, network scanner, Web detection and security, etc

Toward an Integrative Model of Global Business Strategy

DEFF Research Database (Denmark)

Li, Xin

fragmentation-integration-fragmentation-integration upward spiral. In response to the call for integrative approach to strategic management research, we propose an integrative model of global business strategy that aims at integrating not only strategy and IB but also the different paradigms within the strategy...... field. We also discuss the merit and limitation of our model....

Crucial role of strategy updating for coexistence of strategies in interaction networks

Science.gov (United States)

Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

2015-04-01

Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their neighbors. Here we show that the assumptions made on strategy updating are of crucial importance for the strategy dynamics. In the first step, we demonstrate that seemingly small deviations from the standard assumptions on updating have major implications for the evolutionary outcome of two cooperation games: cooperation can more easily persist in a Prisoner's Dilemma game, while it can go more easily extinct in a Snowdrift game. To explain these outcomes, we develop a general model for the updating of states in a network that allows us to derive conditions for the steady-state coexistence of states (or strategies). The analysis reveals that coexistence crucially depends on the number of agents consulted for updating. We conclude that updating rules are as important for evolution on a network as network structure and the nature of the interaction.

The Value of Partial Resource Pooling: Should a Service Network Be Integrated or Product-Focused?

OpenAIRE

Bar{\\i}\\c{s} Ata; Jan A. Van Mieghem

2009-01-01

We investigate how dynamic resource substitution in service systems impacts capacity requirements and responsiveness. Inspired by the contrasting network strategies of FedEx and United Parcel Service (UPS), we study when two service classes (e.g., express or regular) should be served by dedicated resources (e.g., air or ground) or by an integrated network (e.g., air also serves regular). Using call center terminology, the question is whether to operate two independent queues or one N-network....

Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis.

Science.gov (United States)

Scholten, Lisa; Scheidegger, Andreas; Reichert, Peter; Maurer, Max; Mauer, Max; Lienert, Judit

2014-02-01

To overcome the difficulties of strategic asset management of water distribution networks, a pipe failure and a rehabilitation model are combined to predict the long-term performance of rehabilitation strategies. Bayesian parameter estimation is performed to calibrate the failure and replacement model based on a prior distribution inferred from three large water utilities in Switzerland. Multi-criteria decision analysis (MCDA) and scenario planning build the framework for evaluating 18 strategic rehabilitation alternatives under future uncertainty. Outcomes for three fundamental objectives (low costs, high reliability, and high intergenerational equity) are assessed. Exploitation of stochastic dominance concepts helps to identify twelve non-dominated alternatives and local sensitivity analysis of stakeholder preferences is used to rank them under four scenarios. Strategies with annual replacement of 1.5-2% of the network perform reasonably well under all scenarios. In contrast, the commonly used reactive replacement is not recommendable unless cost is the only relevant objective. Exemplified for a small Swiss water utility, this approach can readily be adapted to support strategic asset management for any utility size and based on objectives and preferences that matter to the respective decision makers. Copyright © 2013 Elsevier Ltd. All rights reserved.

Business Ethics, Strategy and Organizational Integrity

DEFF Research Database (Denmark)

Rendtorff, Jacob Dahl

2011-01-01

With focus on the role of integrity in relation to business ethics versus economic strategy the chapter contains following sections: 1. The concept of organizational integrity as a moral notion as it is described in the work of Lynn-Sharp Paine on organizational integrity. 2. The concept...... of integrity as an economic notion as it is described in the recent work of Michael Jensen. This section will discuss recent efforts in the business economics literature to consider integrity as an important notion of strategy. 3. Paine contra Jensen: A virtue or a workability concept of integrity. Here...

Coping strategies for domestic violence against pregnant female adolescents: integrative review

Directory of Open Access Journals (Sweden)

Cibele Monteiro Macedo

Full Text Available ABSTRACT Objective: To investigate and analyze in the scientific literature coping strategies for domestic violence against pregnant female adolescents. Method: This is an integrative literature review, conducted from July to August 2017 on LILACS, SciELO and PubMed, using the descriptors and the MeSH terms: confrontation, violence, adolescent, pregnant women, prenatal care. Result: The sample comprised 9 articles that were organized and characterized according to year, country of study and coping strategy used. The main forms of coping involved the active search for cases and the primary care approach with all family members. Conclusion: Individualized prenatal care, the change in professional training and networking activities were pointed out as important components of the strategies for coping with violence against pregnant adolescents.

Research of negotiation in network trade system based on multi-agent

Science.gov (United States)

Cai, Jun; Wang, Guozheng; Wu, Haiyan

2009-07-01

A construction and implementation technology of network trade based on multi-agent is described in this paper. First, we researched the technology of multi-agent, then we discussed the consumer's behaviors and the negotiation between purchaser and bargainer which emerges in the traditional business mode and analysed the key technology to implement the network trade system. Finally, we implement the system.

Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

Science.gov (United States)

Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand

2015-05-01

Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.

Effective Fusion of Multi-Modal Remote Sensing Data in a Fully Convolutional Network for Semantic Labeling

Directory of Open Access Journals (Sweden)

Wenkai Zhang

2017-12-01

Full Text Available In recent years, Fully Convolutional Networks (FCN have led to a great improvement of semantic labeling for various applications including multi-modal remote sensing data. Although different fusion strategies have been reported for multi-modal data, there is no in-depth study of the reasons of performance limits. For example, it is unclear, why an early fusion of multi-modal data in FCN does not lead to a satisfying result. In this paper, we investigate the contribution of individual layers inside FCN and propose an effective fusion strategy for the semantic labeling of color or infrared imagery together with elevation (e.g., Digital Surface Models. The sensitivity and contribution of layers concerning classes and multi-modal data are quantified by recall and descent rate of recall in a multi-resolution model. The contribution of different modalities to the pixel-wise prediction is analyzed explaining the reason of the poor performance caused by the plain concatenation of different modalities. Finally, based on the analysis an optimized scheme for the fusion of layers with image and elevation information into a single FCN model is derived. Experiments are performed on the ISPRS Vaihingen 2D Semantic Labeling dataset (infrared and RGB imagery as well as elevation and the Potsdam dataset (RGB imagery and elevation. Comprehensive evaluations demonstrate the potential of the proposed approach.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

Science.gov (United States)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

Pathway Relevance Ranking for Tumor Samples through Network-Based Data Integration.

Directory of Open Access Journals (Sweden)

Lieven P C Verbeke

Full Text Available The study of cancer, a highly heterogeneous disease with different causes and clinical outcomes, requires a multi-angle approach and the collection of large multi-omics datasets that, ideally, should be analyzed simultaneously. We present a new pathway relevance ranking method that is able to prioritize pathways according to the information contained in any combination of tumor related omics datasets. Key to the method is the conversion of all available data into a single comprehensive network representation containing not only genes but also individual patient samples. Additionally, all data are linked through a network of previously identified molecular interactions. We demonstrate the performance of the new method by applying it to breast and ovarian cancer datasets from The Cancer Genome Atlas. By integrating gene expression, copy number, mutation and methylation data, the method's potential to identify key pathways involved in breast cancer development shared by different molecular subtypes is illustrated. Interestingly, certain pathways were ranked equally important for different subtypes, even when the underlying (epi-genetic disturbances were diverse. Next to prioritizing universally high-scoring pathways, the pathway ranking method was able to identify subtype-specific pathways. Often the score of a pathway could not be motivated by a single mutation, copy number or methylation alteration, but rather by a combination of genetic and epi-genetic disturbances, stressing the need for a network-based data integration approach. The analysis of ovarian tumors, as a function of survival-based subtypes, demonstrated the method's ability to correctly identify key pathways, irrespective of tumor subtype. A differential analysis of survival-based subtypes revealed several pathways with higher importance for the bad-outcome patient group than for the good-outcome patient group. Many of the pathways exhibiting higher importance for the bad

Strategy and management of network security at KEK

International Nuclear Information System (INIS)

Kiyoharu Hashimoto; Teiji Nakamura; Hitoshi Hirose, Yukio Karita; Youhei Morita; Soh Suzuki; Fukuko Yuasa

2001-01-01

Recently the troubles related to the network security have often occurred at KEK. According to their security policy, the authors have started the strategy against the daily attacks. It consists of two fundamental things; the monitoring and the access control. To monitor the network, the authors have installed the intrusion detection system and have managed it since 1998. For the second thing, the authors arranged three categories to classify all hosts (about 5000 hosts) at KEK according to their security level. To realize these three categories, the authors filter the incoming packet from outside KEK whether it has a SYN flag or not. The network monitoring and the access control produced good effects in keeping the security level high. Since 2000 the authors have started the transition of LAN from shared-media network to switched network. Now almost part of LAN was re-configured and in this new LAN 10 Mbps 100 Mbps/1Gbps Ethernet are supported. Currently the authors are planning further speedup (10 Gbps) and redundancy of network. Not only LAN but also WAN, network speed will be upgraded to 10 Gbps thanks to the strong promotion of IT by Japanese government. In this very high speed network, the authors' current strategy will be affected and again the network security becomes a big issue. The authors describe the experiences in practice of the current strategy and management know-how together with the discussion on the new strategy

Routing protocol extension for resilient GMPLS multi-domain networks

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Ruepp, Sarah Renée; Romeral, Ricardo

2010-01-01

This paper evaluates the performance of multi-domain networks under the Generalized Multi-Protocol Label Switching control framework in case of a single inter-domain link failure. We propose and evaluate a routing protocol extension for the Border Gateway Protocol, which allows domains to obtain...... two Autonomous System disjoint paths and use them efficiently under failure conditions. Three main applications for the protocol extension are illustrated: reducing traffic loss on existing connections by xploiting pre-selected backup paths derived with our proposal, applying multi-domain restoration...... as survivability mechanism in case of single link failure, and employing proper failure notification mechanisms for routing of future connection requests under routing protocol re-convergence. Via simulations we illustrate the benefits of utilizing the proposed routing protocol extension for networks employing...

Robustness of airline alliance route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

2015-05-01

The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

Complexity and network dynamics in physiological adaptation: an integrated view.

Science.gov (United States)

Baffy, György; Loscalzo, Joseph

2014-05-28

Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. Published by Elsevier Inc.

Design of multi-specificity in protein interfaces.

Directory of Open Access Journals (Sweden)

Elisabeth L Humphris

2007-08-01

Full Text Available Interactions in protein networks may place constraints on protein interface sequences to maintain correct and avoid unwanted interactions. Here we describe a "multi-constraint" protein design protocol to predict sequences optimized for multiple criteria, such as maintaining sets of interactions, and apply it to characterize the mechanism and extent to which 20 multi-specific proteins are constrained by binding to multiple partners. We find that multi-specific binding is accommodated by at least two distinct patterns. In the simplest case, all partners share key interactions, and sequences optimized for binding to either single or multiple partners recover only a subset of native amino acid residues as optimal. More interestingly, for signaling interfaces functioning as network "hubs," we identify a different, "multi-faceted" mode, where each binding partner prefers its own subset of wild-type residues within the promiscuous binding site. Here, integration of preferences across all partners results in sequences much more "native-like" than seen in optimization for any single binding partner alone, suggesting these interfaces are substantially optimized for multi-specificity. The two strategies make distinct predictions for interface evolution and design. Shared interfaces may be better small molecule targets, whereas multi-faceted interactions may be more "designable" for altered specificity patterns. The computational methodology presented here is generalizable for examining how naturally occurring protein sequences have been selected to satisfy a variety of positive and negative constraints, as well as for rationally designing proteins to have desired patterns of altered specificity.

A multi-criteria decision analysis approach for importance identification and ranking of network components

International Nuclear Information System (INIS)

Almoghathawi, Yasser; Barker, Kash; Rocco, Claudio M.; Nicholson, Charles D.

2017-01-01

Analyzing network vulnerability is a key element of network planning in order to be prepared for any disruptive event that might impact the performance of the network. Hence, many importance measures have been proposed to identify the important components in a network with respect to vulnerability and rank them accordingly based on individual importance measure. However, in this paper, we propose a new approach to identify the most important network components based on multiple importance measures using a multi criteria decision making (MCDM) method, namely the technique for order performance by similarity to ideal solution (TOPSIS), able to take into account the preferences of decision-makers. We consider multiple edge-specific flow-based importance measures provided as the multiple criteria of a network where the alternatives are the edges. Accordingly, TOPSIS is used to rank the edges of the network based on their importance considering multiple different importance measures. The proposed approach is illustrated through different networks with different densities along with the effects of weighs. - Highlights: • We integrate several perspectives on network vulnerability to generate a component importance ranking. • We apply these measures to determine the importance of edges after disruptions. • Networks of varying size and density are explored.

Immunization strategy for epidemic spreading on multilayer networks

Science.gov (United States)

Buono, C.; Braunstein, L. A.

2015-01-01

In many real-world complex systems, individuals have many kinds of interactions among them, suggesting that it is necessary to consider a layered-structure framework to model systems such as social interactions. This structure can be captured by multilayer networks and can have major effects on the spreading of process that occurs over them, such as epidemics. In this letter we study a targeted immunization strategy for epidemic spreading over a multilayer network. We apply the strategy in one of the layers and study its effect in all layers of the network disregarding degree-degree correlation among layers. We found that the targeted strategy is not as efficient as in isolated networks, due to the fact that in order to stop the spreading of the disease it is necessary to immunize more than 80% of the individuals. However, the size of the epidemic is drastically reduced in the layer where the immunization strategy is applied compared to the case with no mitigation strategy. Thus, the immunization strategy has a major effect on the layer were it is applied, but does not efficiently protect the individuals of other layers.

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

Science.gov (United States)

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Integrated environmental research and networking of economy and information in rural areas of Finland

OpenAIRE

M. LUOSTARINEN

2008-01-01

This article uses material from many extensive research projects starting from the construction of the electric power supply network and its water supply systems in northern Finland in 1973-1986, to the Agropolis agricultural strategy and networking for the Loimijoki project. A list of the material and references of the publications is available in Agronet on the Internet. All these projects applied integrated environmental research covering biology, the natural sciences, social sciences, and...

Multi-Robot Assembly Strategies and Metrics

Science.gov (United States)

MARVEL, JEREMY A.; BOSTELMAN, ROGER; FALCO, JOE

2018-01-01

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies. PMID:29497234

Multi-Robot Assembly Strategies and Metrics.

Science.gov (United States)

Marvel, Jeremy A; Bostelman, Roger; Falco, Joe

2018-02-01

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies.

Simulation and evaluation of urban rail transit network based on multi-agent approach

Directory of Open Access Journals (Sweden)

Xiangming Yao

2013-03-01

Full Text Available Purpose: Urban rail transit is a complex and dynamic system, which is difficult to be described in a global mathematical model for its scale and interaction. In order to analyze the spatial and temporal characteristics of passenger flow distribution and evaluate the effectiveness of transportation strategies, a new and comprehensive method depicted such dynamic system should be given. This study therefore aims at using simulation approach to solve this problem for subway network. Design/methodology/approach: In this thesis a simulation model based on multi-agent approach has been proposed, which is a well suited method to design complex systems. The model includes the specificities of passengers’ travelling behaviors and takes into account of interactions between travelers and trains. Findings: Research limitations/implications: We developed an urban rail transit simulation tool for verification of the validity and accuracy of this model, using real passenger flow data of Beijing subway network to take a case study, results show that our simulation tool can be used to analyze the characteristic of passenger flow distribution and evaluate operation strategies well. Practical implications: The main implications of this work are to provide decision support for traffic management, making train operation plan and dispatching measures in emergency. Originality/value: A new and comprehensive method to analyze and evaluate subway network is presented, accuracy and computational efficiency of the model has been confirmed and meet with the actual needs for large-scale network.

Outage and ser performance of an opportunistic multi-user underlay cognitive network

KAUST Repository

Khan, Fahd Ahmed

2012-10-01

Consider a multi-user underlay cognitive network where multiple cognitive users concurrently share the spectrum with a primary network and a single secondary user is selected for transmission. The channel is assumed to have independent but not identical Nakagami-m fading. Closed form expressions for the outage performance and the symbol-error-rate performance of the opportunistic multi-user secondary network are derived when a peak interference power constraint is imposed on the secondary network in addition to the limited peak transmit power of each secondary user. © 2012 IEEE.

Research priorities for a multi-center child abuse pediatrics network - CAPNET.

Science.gov (United States)

Lindberg, Daniel M; Wood, Joanne N; Campbell, Kristine A; Scribano, Philip V; Laskey, Antoinette; Leventhal, John M; Pierce, Mary Clyde; Runyan, Desmond K

2017-03-01

Although child maltreatment medical research has benefited from several multi-center studies, the new specialty of child abuse pediatrics has not had a sustainable network capable of pursuing multiple, prospective, clinically-oriented studies. The Child Abuse Pediatrics Network (CAPNET) is a new multi-center research network dedicated to child maltreatment medical research. In order to establish a relevant, practical research agenda, we conducted a modified Delphi process to determine the topic areas with highest priority for such a network. Research questions were solicited from members of the Ray E. Helfer Society and study authors and were sorted into topic areas. These topic areas were rated for priority using iterative rounds of ratings and in-person meetings. The topics rated with the highest priority were missed diagnosis and selected/indicated prevention. This agenda can be used to target future multi-center child maltreatment medical research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pinning Control Strategy of Multicommunity Structure Networks

Directory of Open Access Journals (Sweden)

Chao Ding

2017-01-01

Full Text Available In order to investigate the effects of community structure on synchronization, a pinning control strategy is researched in a class of complex networks with community structure in this paper. A feedback control law is designed based on the network community structure information. The stability condition is given and proved by using Lyapunov stability theory. Our research shows that as to community structure networks, there being a threshold hT≈5, when coupling strength bellows this threshold, the stronger coupling strength corresponds to higher synchronizability; vice versa, the stronger coupling strength brings lower synchronizability. In addition the synchronizability of overlapping and nonoverlapping community structure networks was simulated and analyzed; while the nodes were controlled randomly and intensively, the results show that intensive control strategy is better than the random one. The network will reach synchronization easily when the node with largest betweenness was controlled. Furthermore, four difference networks’ synchronizability, such as Barabási-Albert network, Watts-Strogatz network, Erdös-Rényi network, and community structure network, are simulated; the research shows that the community structure network is more easily synchronized under the same control strength.

Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

KAUST Repository

Moubayed, Abdallah J.

2015-05-01

In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other\\'s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network\\'s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network\\'s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. © 2015 IEEE.

Integrated Strategic Planning of Global Production Networks and Financial Hedging under Uncertain Demands and Exchange Rates

Directory of Open Access Journals (Sweden)

Achim Koberstein

2013-11-01

Full Text Available In this paper, we present a multi-stage stochastic programming model that integrates financial hedging decisions into the planning of strategic production networks under uncertain exchange rates and product demands. This model considers the expenses of production plants and the revenues of markets in different currency areas. Financial portfolio planning decisions for two types of financial instruments, forward contracts and options, are represented explicitly by multi-period decision variables and a multi-stage scenario tree. Using an illustrative example, we analyze the impact of exchange-rate and demand volatility, the level of investment expenses and interest rate spreads on capacity location and dimensioning decisions. In particular, we show that, in the illustrative example, the exchange-rate uncertainty cannot be completely eliminated by financial hedging in the presence of demand uncertainty. In this situation, we find that the integrated model can result in better strategic planning decisions for a risk-averse decision maker compared to traditional modeling approaches.

Efficient Simulation of Compressible, Viscous Fluids using Multi-rate Time Integration

Science.gov (United States)

Mikida, Cory; Kloeckner, Andreas; Bodony, Daniel

2017-11-01

In the numerical simulation of problems of compressible, viscous fluids with single-rate time integrators, the global timestep used is limited to that of the finest mesh point or fastest physical process. This talk discusses the application of multi-rate Adams-Bashforth (MRAB) integrators to an overset mesh framework to solve compressible viscous fluid problems of varying scale with improved efficiency, with emphasis on the strategy of timescale separation and the application of the resulting numerical method to two sample problems: subsonic viscous flow over a cylinder and a viscous jet in crossflow. The results presented indicate the numerical efficacy of MRAB integrators, outline a number of outstanding code challenges, demonstrate the expected reduction in time enabled by MRAB, and emphasize the need for proper load balancing through spatial decomposition in order for parallel runs to achieve the predicted time-saving benefit. This material is based in part upon work supported by the Department of Energy, National Nuclear Security Administration, under Award Number DE-NA0002374.

Wireless multi-hop networks with stealing : large buffer asymptotics

NARCIS (Netherlands)

Guillemin, F.; Knessl, C.; Leeuwaarden, van J.S.H.

2010-01-01

Wireless networks equipped with CSMA are scheduled in a fully distributed manner. A disadvantage of such distributed control in multi-hop networks is the hidden node problem that causes the effect of stealing, in which a downstream node steals the channel from an upstream node with probability p.

Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

CERN Document Server

Hu, Fei

2012-01-01

Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

Global Prioritization of Disease Candidate Metabolites Based on a Multi-omics Composite Network

Science.gov (United States)

Yao, Qianlan; Xu, Yanjun; Yang, Haixiu; Shang, Desi; Zhang, Chunlong; Zhang, Yunpeng; Sun, Zeguo; Shi, Xinrui; Feng, Li; Han, Junwei; Su, Fei; Li, Chunquan; Li, Xia

2015-01-01

The identification of disease-related metabolites is important for a better understanding of metabolite pathological processes in order to improve human medicine. Metabolites, which are the terminal products of cellular regulatory process, can be affected by multi-omic processes. In this work, we propose a powerful method, MetPriCNet, to predict and prioritize disease candidate metabolites based on integrated multi-omics information. MetPriCNet prioritized candidate metabolites based on their global distance similarity with seed nodes in a composite network, which integrated multi-omics information from the genome, phenome, metabolome and interactome. After performing cross-validation on 87 phenotypes with a total of 602 metabolites, MetPriCNet achieved a high AUC value of up to 0.918. We also assessed the performance of MetPriCNet on 18 disease classes and found that 4 disease classes achieved an AUC value over 0.95. Notably, MetPriCNet can also predict disease metabolites without known disease metabolite knowledge. Some new high-risk metabolites of breast cancer were predicted, although there is a lack of known disease metabolite information. A predicted disease metabolic landscape was constructed and analyzed based on the results of MetPriCNet for 87 phenotypes to help us understand the genetic and metabolic mechanism of disease from a global view. PMID:26598063

A platform for rapid prototyping of synthetic gene networks in mammalian cells

Science.gov (United States)

Duportet, Xavier; Wroblewska, Liliana; Guye, Patrick; Li, Yinqing; Eyquem, Justin; Rieders, Julianne; Rimchala, Tharathorn; Batt, Gregory; Weiss, Ron

2014-01-01

Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines. PMID:25378321

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

Science.gov (United States)

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

2014-01-01

Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

Routing strategies in traffic network and phase transition in network ...

Indian Academy of Sciences (India)

3Department of Electronic Engineering, City University of Hong Kong, Hong Kong ... Routing strategy; network traffic flow; hysteretic loop; phase transition from ... ered from two aspects: modifying the underlying network structure or developing ... capacity corresponds to α = −1 in the case of identical nodes' delivering ability.

Development of automobile distribution networks on the basis of multi-criteria evaluation of distribution channels

Directory of Open Access Journals (Sweden)

A. Vasilis Vasiliauskas

2010-12-01

Full Text Available .The days when a buyer was forced to choose from what is being offered have passed. These days, buyers demand a product that would answer their exclusive expectations at a time of their preference and at an acceptable price. Therefore, manufacturers aiming to survive the competition battle have to rethink their operation strategies. Special importance is attached to the process of development and reconstruction of supply chains, and the process which may feature particularities, depending on the branch of industry. Automobile manufacturing is the biggest the fastest industry developing across the globe. New automobiles are listed as luxury commodities and are, therefore, subjected to very strict requirements with regard to various logistic operations and technologies, which are vital for ensuring efficient automobile delivery to the final users. Due to the growing demand for brand-new automobiles and the distance to the user, automobile manufacturers are constantly searching for solutions to the development and support of an efficient distribution network. Strategy shaping of distribution network requires evaluation of a number of criteria, which influence the distribution system. The article analyzes the development of automobile distribution networks on the basis of multi-criteria evaluation of distribution channels.

Optimal Software Strategies in the Presence of Network Externalities

Science.gov (United States)

Liu, Yipeng

2009-01-01

Network externalities or alternatively termed network effects are pervasive in computer software markets. While software vendors consider pricing strategies, they must also take into account the impact of network externalities on their sales. My main interest in this research is to describe a firm's strategies and behaviors in the presence of…

Optimal Real-time Dispatch for Integrated Energy Systems

DEFF Research Database (Denmark)

Anvari-Moghaddam, Amjad; Guerrero, Josep M.; Rahimi-Kian, Ashkan

2016-01-01

With the emerging of small-scale integrated energy systems (IESs), there are significant potentials to increase the functionality of a typical demand-side management (DSM) strategy and typical implementation of building-level distributed energy resources (DERs). By integrating DSM and DERs...... into a cohesive, networked package that fully utilizes smart energy-efficient end-use devices, advanced building control/automation systems, and integrated communications architectures, it is possible to efficiently manage energy and comfort at the end-use location. In this paper, an ontology-driven multi......-agent control system with intelligent optimizers is proposed for optimal real-time dispatch of an integrated building and microgrid system considering coordinated demand response (DR) and DERs management. The optimal dispatch problem is formulated as a mixed integer nonlinear programing problem (MINLP...

Future distributed generation: An operational multi-objective optimization model for integrated small scale urban electrical, thermal and gas grids

International Nuclear Information System (INIS)

Lo Cascio, Ermanno; Borelli, Davide; Devia, Francesco; Schenone, Corrado

2017-01-01

Highlights: • Multi-objective optimization model for retrofitted and integrated natural gas pressure regulation stations. • Comparison of different incentive mechanisms for recovered energy based on the characteristics of preheating process. • Control strategies comparison: performances achieved with optimal control vs. ones obtained by thermal load tracking. - Abstract: A multi-objective optimization model for urban integrated electrical, thermal and gas grids is presented. The main system consists of a retrofitted natural gas pressure regulation station where a turbo-expander allows to recover energy from the process. Here, the natural gas must be preheated in order to avoid methane hydrates. The preheating phase could be based on fossil fuels, renewable or on a thermal mix. Depending on the system configuration, the proposed optimization model enables a proper differentiation based on how the natural gas preheating process is expected to be accomplished. This differentiation is addressed by weighting the electricity produced by the turbo-expander and linking it to proper remuneration tariffs. The effectiveness of the model has been tested on an existing plant located in the city of Genoa. Here, the thermal energy is provided by means of two redundant gas-fired boilers and a cogeneration unit. Furthermore, the whole system is thermally integrated with a district heating network. Numerical simulation results, obtained with the commercial proprietary software Honeywell UniSim Design Suite, have been compared with the optimal solutions achieved. The effectiveness of the model, in terms of economic and environmental performances, is finally quantified. For specific conditions, the model allows achieving an operational costs reduction of about 17% with the respect to thermal-load-tracking control logic.

A multi-period distribution network design model under demand uncertainty

Science.gov (United States)

Tabrizi, Babak H.; Razmi, Jafar

2013-05-01

Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

Multi-objective optimal strategy for generating and bidding in the power market

International Nuclear Information System (INIS)

Peng Chunhua; Sun Huijuan; Guo Jianfeng; Liu Gang

2012-01-01

Highlights: ► A new benefit/risk/emission comprehensive generation optimization model is established. ► A hybrid multi-objective differential evolution optimization algorithm is designed. ► Fuzzy set theory and entropy weighting method are employed to extract the general best solution. ► The proposed approach of generating and bidding is efficient for maximizing profit and minimizing both risk and emissions. - Abstract: Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liu Yang

2015-12-01

Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

Real-time visual communication to aid disaster recovery in a multi-segment hybrid wireless networking system

Science.gov (United States)

Al Hadhrami, Tawfik; Wang, Qi; Grecos, Christos

2012-06-01

When natural disasters or other large-scale incidents occur, obtaining accurate and timely information on the developing situation is vital to effective disaster recovery operations. High-quality video streams and high-resolution images, if available in real time, would provide an invaluable source of current situation reports to the incident management team. Meanwhile, a disaster often causes significant damage to the communications infrastructure. Therefore, another essential requirement for disaster management is the ability to rapidly deploy a flexible incident area communication network. Such a network would facilitate the transmission of real-time video streams and still images from the disrupted area to remote command and control locations. In this paper, a comprehensive end-to-end video/image transmission system between an incident area and a remote control centre is proposed and implemented, and its performance is experimentally investigated. In this study a hybrid multi-segment communication network is designed that seamlessly integrates terrestrial wireless mesh networks (WMNs), distributed wireless visual sensor networks, an airborne platform with video camera balloons, and a Digital Video Broadcasting- Satellite (DVB-S) system. By carefully integrating all of these rapidly deployable, interworking and collaborative networking technologies, we can fully exploit the joint benefits provided by WMNs, WSNs, balloon camera networks and DVB-S for real-time video streaming and image delivery in emergency situations among the disaster hit area, the remote control centre and the rescue teams in the field. The whole proposed system is implemented in a proven simulator. Through extensive simulations, the real-time visual communication performance of this integrated system has been numerically evaluated, towards a more in-depth understanding in supporting high-quality visual communications in such a demanding context.

Cities, Europeanization and Multi-level Governance: Governing Climate Change through Transnational Municipal Networks

NARCIS (Netherlands)

Kern, K.; Bulkeley, H.

2009-01-01

This article focuses on a variant of multi-level governance and Europeanization, i.e. the transnational networking of local authorities. Focusing on local climate change policy, the article examines how transnational municipal networks (TMNs) govern in the context of multi-level European governance.

Cooperative and networking strategies in small business

CERN Document Server

Ferreira, João

2017-01-01

The book aims to collect the most recent research and best practices in the cooperative and networking small business field identifying new theoretical models and describing the relationship between cooperation and networks in the small business strategy context. It examines different concepts and analytical techniques better understand the links between cooperative strategies and networks in small business. It also studies the existing economic conditions of network and strategic implications to small business from the point of view of their internal and external consistency. Cooperation and networks is a fashionable topic. It is receiving increasing attention in popular management publications, as well as specialized academic journals. Cooperation between firms and industries is a means of leveraging and aggregating knowledge also generating direct benefits in terms of innovation, productivity and competitiveness. Various options and decisions made within the framework of strategic alliances may be identifi...

Priority Control Strategy of VSC-MTDC System for Integrating Wind Power

Directory of Open Access Journals (Sweden)

Wen-ning Yan

2015-01-01

Full Text Available For the obvious advantages in integrating wind power, multiterminal HVDC transmission system (VSC-MTDC is widely used. The priority control strategy is proposed in this paper considering the penetration rate of wind power for the AC grid. The strategy aims to solve the problems of power allocation and DC voltage control of the DC system. The main advantage of this strategy is that the demands for wind power of different areas can be satisfied and a power reference for the wind power trade can also be provided when wind farms transmit active power to several AC grids through the DC network. The objective is that power is well distributed according to the output power of wind farm with the demand of AC system and satisfactory control performance of DC voltage is obtained.

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

Directory of Open Access Journals (Sweden)

Chong Chen

2018-04-01

Full Text Available In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP, and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL, are still imperfect, which make it difficult for the active distribution network (ADN to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

Intercontinental Multi-Domain Monitoring for the LHC Optical Private Network

CERN Multimedia

CERN. Geneva

2012-01-01

The Large Hadron Collider (LHC) is currently running at CERN in Geneva, Switzerland. Physicists are using LHC to recreate the conditions just after the Big Bang, by colliding two beams of particles and heavy ions head-on at very high energy. The project is expected to generate 27 TB of raw data per day, plus 10 TB of "event summary data". This data is sent out from CERN to eleven Tier 1 academic institutions in Europe, Asia, and North America using a multi-gigabits Optical Private Network (OPN), the LHCOPN. Network monitoring on such complex network architecture to ensure robust and reliable operation is of crucial importance. The chosen approach for monitoring the OPN is based on the perfSONAR MDM framework (http://perfsonar.geant.net), which is designed for multi-domain monitoring environments. perfSONAR (www.perfsonar.net) is an infrastructure for performance monitoring data exchange between networks, making it easier to solve performance problems occurring between network measurement points interconne...

MIMO wireless networks channels, techniques and standards for multi-antenna, multi-user and multi-cell systems

CERN Document Server

Clerckx, Bruno

2013-01-01

This book is unique in presenting channels, techniques and standards for the next generation of MIMO wireless networks. Through a unified framework, it emphasizes how propagation mechanisms impact the system performance under realistic power constraints. Combining a solid mathematical analysis with a physical and intuitive approach to space-time signal processing, the book progressively derives innovative designs for space-time coding and precoding as well as multi-user and multi-cell techniques, taking into consideration that MIMO channels are often far from ideal. Reflecting developments

Coevolution of Cooperation and Layer Selection Strategy in Multiplex Networks

Directory of Open Access Journals (Sweden)

Katsuki Hayashi

2016-11-01

Full Text Available Recently, the emergent dynamics in multiplex networks, composed of layers of multiple networks, has been discussed extensively in network sciences. However, little is still known about whether and how the evolution of strategy for selecting a layer to participate in can contribute to the emergence of cooperative behaviors in multiplex networks of social interactions. To investigate these issues, we constructed a coevolutionary model of cooperation and layer selection strategies in which each an individual selects one layer from multiple layers of social networks and plays the Prisoner’s Dilemma with neighbors in the selected layer. We found that the proportion of cooperative strategies increased with increasing the number of layers regardless of the degree of dilemma, and this increase occurred due to a cyclic coevolution process of game strategies and layer selection strategies. We also showed that the heterogeneity of links among layers is a key factor for multiplex networks to facilitate the evolution of cooperation, and such positive effects on cooperation were observed regardless of the difference in the stochastic properties of network topologies.

Integrated real-time control strategy in multi-tank A2O process for biological nutrient removal treating real domestic wastewater

Directory of Open Access Journals (Sweden)

Saad Abualhail

2017-02-01

Full Text Available An integrated real-time anaerobic–anoxic/oxic (A2O operated with multi-tank called IMT–A2O process was designed and operated with fluctuating influent loads for biological nutrient removal for treating real domestic wastewater. IMT–A2O process, a “phased isolation tank” technology, varies both aeration pattern and flow path in a continuous flow multi-tank system to force fluctuation of organic and nutrient concentrations in process reactors. Using an eight-phase cycle, desired biochemical transformations, are accomplished at different times in the same tank. On-line sensors (pH, ORP, and DO were used as real-time control parameters to adjust the duration of each operational phase in the IMT–A2O process. The control system is an algorithm that automatically adjusts the cycle length to the influent wastewater characteristics according to the end points. It was found that on-line sensor values of pH, ORP, and DO were somehow related with the dynamic behaviors of nutrient concentrations in IMT–A2O. The algorithm acts in the reaction phases of the IMT–A2O cycle using ORP and pH break points of tank one to distinguish the end of denitrification and the beginning of phosphorus release, pH break point of tank two to control the end of denitrification and beginning of phosphorus release and a sudden increase in DO pattern, pH break point and ORP to control phosphorus uptake and the end of the nitrification process. Although the fluctuations in raw wastewater concentration are extreme; an influent with a low C/N ratio is deficient in organic carbon, and a low carbon source level can limit the overall biological denitrification process, the average removal efficiencies achieved for COD, ammonia–nitrogen, total nitrogen and total phosphorus were not less than 76.11%, 87.78%, 76.45% and 83.75%, respectively, using the integrated real-time control strategy. The integrated IMT–A2O exhibited a better performance in nutrient removal than the

Integrated service resource reservation using queueing networks theory

DEFF Research Database (Denmark)

Brewka, Lukasz Jerzy; Iversen, Villy Bæk; Kardaras, Georgios

2014-01-01

This study analyses multi-server multi-service queueing networks with service protection. To guarantee each service a certain quality-of-service and at the same time ensure high utilisation of servers, a minimum capacity is reserved each service. In addition, all services share the remaining non...

A multi-disciplinary approach for the integrated assessment of water alterations under climate change

Science.gov (United States)

Sperotto, Anna; Torresan, Silvia; Molina, Jose Luis; Pulido Velazquez, Manuel; Critto, Andrea; Marcomini, Antonio

2017-04-01

Understanding the co-evolution and interrelations between natural and human pressures on water systems is required to ensure a sustainable management of resources under uncertain climate change conditions. To pursue multi-disciplinary research is therefore necessary to consider the multiplicity of stressors affecting water resources, take into account alternative perspectives (i.e. social, economic and environmental objective and priorities) and deal with uncertainty which characterize climate change scenarios. However, approaches commonly adopted in water quality assessment are predominantly mono-disciplinary, single-stressors oriented and apply concepts and models specific of different academic disciplines (e.g. physics, hydrology, ecology, sociology, economy) which, in fact, seldom shed their conceptual blinders failing to provide truly integrated results. In this context, the paper discusses the benefits and limits of adopting a multi-disciplinary approach where different knowledge domains collaborate and quantitative and qualitative information, coming from multiple conceptual and model-based research, are integrated in a harmonic manner. Specifically, Bayesian Networks are used as meta-modelling tool for structuring and combining the probabilistic information available in existing hydrological models, climate change and land use projections, historical observations and expert opinion. The developed network allows to perform a stochastic multi-risk assessment considering the interlacing between climate (i.e. irregularities in water regime) and land use changes (i.e. agriculture, urbanization) and their cascading impacts on water quality parameters (i.e. nutrients loadings). Main objective of the model is the development of multi-risk scenarios to assess and communicate the probability of not meeting a "Good chemical water status" over future timeframe taking into account projected climatic and not climatic conditions. The outcomes are finally used to identify

Growth strategies and governance of horizontal business networks: the case of the biggest German cooperative food retail network

Directory of Open Access Journals (Sweden)

Douglas Wegner

2011-08-01

Full Text Available Several growth strategies may be adopted by cooperative retail networks, but these strategies create dilemmas about how to organize business networks with a large number of participants and the adjustments in the governance system that are necessary to facilitate growth. The article examines the relations between the growth strategies adopted by a horizontal business network and its governance system. We analyze the case of Edeka, a centennial cooperative network, leader in food retail in Germany, showing its growth strategies and implications for the network structure. The case study was based on various secondary data sources and focuses the whole network – and not the networked firms – as the unit of analysis. Results indicate that, in order to grow, the network changed its governance structure and the process of participation of members in decision making, creating a hierarchical structure with professional management. The paper contributes to the discussions on cooperative governance and demonstrates that governance systems are transient and adapt to the network strategies. From a management viewpoint, the results show the effects of the growth strategies adopted by business networks, regarding the role of network managers and entrepreneurs in network management.

AN OVERVIEW OF UMTS AND WIMAX NETWORKS INTEGRATION

Directory of Open Access Journals (Sweden)

Dewi Wirastuti

2010-12-01

Full Text Available This paper gives an overview of the network integration of UMTS (Universal Mobile TelecommunicationSystem with WiMAX (Wordwide Interoperability of Microwave Access. A few proposed interworking solutionsand seamless integration of both networks are explained. The best architecture and key procedures that will enablethe integration both networks and handover mechanism for the seamless mobility are presented. Considering thetrend of the current network evolution, which is the convergence between the telecommunications and broadcastworlds, an integration of mobile WiMAX with present 2G, 2.5G or 3G accesses into a homogeneous architecturegoes a long way to achieve the reality of mobile broadband networks. With the advent of mobile WiMAX, a mobilebroadband wireless access solution and based on all-IP (Internet Protocol based OFDMA (Orthogonal FrequencyDivision Multiple Access technology, an UMTS-WiMAX

Demonstration of glass-based photonic interposer for mid-board-optical engines and electrical-optical circuit board (EOCB) integration strategy

Science.gov (United States)

Schröder, H.; Neitz, M.; Schneider-Ramelow, M.

2018-02-01

Due to its optical transparency and superior dielectric properties glass is regarded as a promising candidate for advanced applications as active photonic interposer for mid-board-optics and optical PCB waveguide integration. The concepts for multi-mode and single-mode photonic system integration are discussed and related demonstration project results will be presented. A hybrid integrated photonic glass body interposer with integrated optical lenses for multi-mode data communication wavelength of 850 nm have been realized. The paper summarizes process developments which allow cost efficient metallization of TGV. Electro-optical elements like photodiodes and VCSELs can be directly flip-chip mounted on the glass substrate according to the desired lens positions. Furthermore results for a silicon photonic based single-mode active interposer integration onto a single mode glass made EOCB will be compared in terms of packaging challenges. The board level integration strategy for both of these technological approaches and general next generation board level integration concepts for photonic interposer will be introductorily discussed.

Influence network linkages across implementation strategy conditions in a randomized controlled trial of two strategies for scaling up evidence-based practices in public youth-serving systems.

Science.gov (United States)

Palinkas, Lawrence A; Holloway, Ian W; Rice, Eric; Brown, C Hendricks; Valente, Thomas W; Chamberlain, Patricia

2013-11-14

Given the importance of influence networks in the implementation of evidence-based practices and interventions, it is unclear whether such networks continue to operate as sources of information and advice when they are segmented and disrupted by randomization to different implementation strategy conditions. The present study examines the linkages across implementation strategy conditions of social influence networks of leaders of youth-serving systems in 12 California counties participating in a randomized controlled trial of community development teams (CDTs) to scale up use of an evidence-based practice. Semi-structured interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. A web-based survey collected additional quantitative data on information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) to examine linkages between treatment and standard conditions. Of those network members who were affiliated with a county (n = 137), only 6 (4.4%) were directly connected to a member of the opposite implementation strategy condition; 19 (13.9%) were connected by two steps or fewer to a member of the opposite implementation strategy condition; 64 (46.7%) were connected by three or fewer steps to a member of the opposite implementation strategy condition. Most of the indirect steps between individuals who were in different implementation strategy conditions were connections involving a third non-county organizational entity that had an important role in the trial in keeping the implementation strategy conditions separate. When these entities were excluded, the CDT network exhibited fewer components and significantly higher betweenness centralization than did the standard condition network. Although the integrity of the RCT in this instance was not compromised by study participant influence

Performance Analysis of RF-FSO Multi-Hop Networks

KAUST Repository

Makki, Behrooz

2017-05-12

We study the performance of multi-hop networks composed of millimeter wave (MMW)-based radio frequency (RF) and free-space optical (FSO) links. The results are obtained in the cases with and without hybrid automatic repeat request (HARQ). Taking the MMW characteristics of the RF links into account, we derive closed-form expressions for the network outage probability. We also evaluate the effect of various parameters such as power amplifiers efficiency, number of antennas as well as different coherence times of the RF and the FSO links on the system performance. Finally, we present mappings between the performance of RF- FSO multi-hop networks and the ones using only the RF- or the FSO-based communication, in the sense that with appropriate parameter settings the same outage probability is achieved in these setups. The results show the efficiency of the RF-FSO setups in different conditions. Moreover, the HARQ can effectively improve the outage probability/energy efficiency, and compensate the effect of hardware impairments in RF-FSO networks. For common parameter settings of the RF-FSO dual- hop networks, outage probability 10^{-4} and code rate 3 nats-per-channel-use, the implementation of HARQ with a maximum of 2 and 3 retransmissions reduces the required power, compared to the cases with no HARQ, by 13 and 17 dB, respectively.

Combined Heuristic Attack Strategy on Complex Networks

Directory of Open Access Journals (Sweden)

Marek Šimon

2017-01-01

Full Text Available Usually, the existence of a complex network is considered an advantage feature and efforts are made to increase its robustness against an attack. However, there exist also harmful and/or malicious networks, from social ones like spreading hoax, corruption, phishing, extremist ideology, and terrorist support up to computer networks spreading computer viruses or DDoS attack software or even biological networks of carriers or transport centers spreading disease among the population. New attack strategy can be therefore used against malicious networks, as well as in a worst-case scenario test for robustness of a useful network. A common measure of robustness of networks is their disintegration level after removal of a fraction of nodes. This robustness can be calculated as a ratio of the number of nodes of the greatest remaining network component against the number of nodes in the original network. Our paper presents a combination of heuristics optimized for an attack on a complex network to achieve its greatest disintegration. Nodes are deleted sequentially based on a heuristic criterion. Efficiency of classical attack approaches is compared to the proposed approach on Barabási-Albert, scale-free with tunable power-law exponent, and Erdős-Rényi models of complex networks and on real-world networks. Our attack strategy results in a faster disintegration, which is counterbalanced by its slightly increased computational demands.

Real-time Trading Strategies for Proactive Distribution Company with Distributed Generation and Demand Response

DEFF Research Database (Denmark)

Wang, Qi

Distributed energy resources (DERs), such as distributed generation (DG) and demand response (DR), have been recognized worldwide as valuable resources. High integration of DG and DR in the distribution network inspires a potential deregulated environment for the distribution company (DISCO...... in the presented DL market and transact with TL real-time market. A one-leader multi-follower-type bi-level model is proposed to indicate the PDISCO's trading strategies. To participate in the TL real-time market, a methodology is presented to derive continuous bidding/offering strategies for a PDISCO. A bi...

Integrated control platform for converged optical and wireless networks

DEFF Research Database (Denmark)

Yan, Ying

The next generation of broadband access networks is expected to be heterogeneous. Multiple wired and wireless systems can be integrated, in order to simultaneously provide seamless access with an appropriate Quality of Service (QoS). Wireless networks support ubiquitous connectivity yet low data...... rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... the complementary characteristics of the optical networks and the wireless networks, addresses motivations for their interworking, discusses the current progress in hybrid network architectures as well as the functionalities of a control system, and identifies the achieved research contributions in the integrated...

A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks

Science.gov (United States)

Sha, Chao; Qiu, Jian-mei; Li, Shu-yan; Qiang, Meng-ye; Wang, Ru-chuan

2016-01-01

To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs), a type of low-latency data gathering method with multi-Sink (LDGM for short) is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods. PMID:27338401

A Type of Low-Latency Data Gathering Method with Multi-Sink for Sensor Networks

Directory of Open Access Journals (Sweden)

Chao Sha

2016-06-01

Full Text Available To balance energy consumption and reduce latency on data transmission in Wireless Sensor Networks (WSNs, a type of low-latency data gathering method with multi-Sink (LDGM for short is proposed in this paper. The network is divided into several virtual regions consisting of three or less data gathering units and the leader of each region is selected according to its residual energy as well as distance to all of the other nodes. Only the leaders in each region need to communicate with the mobile Sinks which have effectively reduced energy consumption and the end-to-end delay. Moreover, with the help of the sleep scheduling and the sensing radius adjustment strategies, redundancy in network coverage could also be effectively reduced. Simulation results show that LDGM is energy efficient in comparison with MST as well as MWST and its time efficiency on data collection is higher than one Sink based data gathering methods.

Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks

KAUST Repository

Douik, Ahmed

2016-03-28

In the context of resource allocation in cloud- radio access networks, recent studies assume either signal-level or scheduling-level coordination. This paper, instead, considers a hybrid level of coordination for the scheduling problem in the downlink of a multi-cloud radio- access network, so as to benefit from both scheduling policies. Consider a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and therefore allows joint signal processing between them. Across the multiple clouds, however, only scheduling-level coordination is permitted, as it requires a lower level of backhaul communication. The frame structure of every BS is composed of various time/frequency blocks, called power- zones (PZs), and kept at fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled, at most, to a single cloud, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs\\' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The scheduling problem is, then, shown to be equivalent to a maximum- weight independent set problem in the constructed graph, in which each vertex symbolizes an association of cloud, user, BS and PZ, with a weight representing the utility of that association. Simulation results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

Evolution of quantum and classical strategies on networks by group interactions

International Nuclear Information System (INIS)

Li Qiang; Chen Minyou; Iqbal, Azhar; Abbott, Derek

2012-01-01

In this paper, quantum strategies are introduced within evolutionary games in order to investigate the evolution of quantum and classical strategies on networks in the public goods game. Comparing the results of evolution on a scale-free network and a square lattice, we find that a quantum strategy outperforms the classical strategies, regardless of the network. Moreover, a quantum strategy dominates the population earlier in group interactions than it does in pairwise interactions. In particular, if the hub node in a scale-free network is occupied by a cooperator initially, the strategy of cooperation will prevail in the population. However, in other situations, a quantum strategy can defeat the classical ones and finally becomes the dominant strategy in the population. (paper)

An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer

Directory of Open Access Journals (Sweden)

Lockwood William W

2010-05-01

Full Text Available Abstract Background Genomics has substantially changed our approach to cancer research. Gene expression profiling, for example, has been utilized to delineate subtypes of cancer, and facilitated derivation of predictive and prognostic signatures. The emergence of technologies for the high resolution and genome-wide description of genetic and epigenetic features has enabled the identification of a multitude of causal DNA events in tumors. This has afforded the potential for large scale integration of genome and transcriptome data generated from a variety of technology platforms to acquire a better understanding of cancer. Results Here we show how multi-dimensional genomics data analysis would enable the deciphering of mechanisms that disrupt regulatory/signaling cascades and downstream effects. Since not all gene expression changes observed in a tumor are causal to cancer development, we demonstrate an approach based on multiple concerted disruption (MCD analysis of genes that facilitates the rational deduction of aberrant genes and pathways, which otherwise would be overlooked in single genomic dimension investigations. Conclusions Notably, this is the first comprehensive study of breast cancer cells by parallel integrative genome wide analyses of DNA copy number, LOH, and DNA methylation status to interpret changes in gene expression pattern. Our findings demonstrate the power of a multi-dimensional approach to elucidate events which would escape conventional single dimensional analysis and as such, reduce the cohort sample size for cancer gene discovery.

Programmable multi-node quantum network design and simulation

Science.gov (United States)

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

2016-05-01

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

First field trial of Virtual Network Operator oriented network on demand (NoD) service provisioning over software defined multi-vendor OTN networks

Science.gov (United States)

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Chen, Haoran; Zhu, Ruijie; Zhou, Quanwei; Yu, Chenbei; Cui, Rui

2017-01-01

A Virtual Network Operator (VNO) is a provider and reseller of network services from other telecommunications suppliers. These network providers are categorized as virtual because they do not own the underlying telecommunication infrastructure. In terms of business operation, VNO can provide customers with personalized services by leasing network infrastructure from traditional network providers. The unique business modes of VNO lead to the emergence of network on demand (NoD) services. The conventional network provisioning involves a series of manual operation and configuration, which leads to high cost in time. Considering the advantages of Software Defined Networking (SDN), this paper proposes a novel NoD service provisioning solution to satisfy the private network need of VNOs. The solution is first verified in the real software defined multi-domain optical networks with multi-vendor OTN equipment. With the proposed solution, NoD service can be deployed via online web portals in near-real time. It reinvents the customer experience and redefines how network services are delivered to customers via an online self-service portal. Ultimately, this means a customer will be able to simply go online, click a few buttons and have new services almost instantaneously.

Computer-Supported Modelling of Multi modal Transportation Networks Rationalization

Directory of Open Access Journals (Sweden)

Ratko Zelenika

2007-09-01

Full Text Available This paper deals with issues of shaping and functioning ofcomputer programs in the modelling and solving of multimoda Itransportation network problems. A methodology of an integrateduse of a programming language for mathematical modellingis defined, as well as spreadsheets for the solving of complexmultimodal transportation network problems. The papercontains a comparison of the partial and integral methods ofsolving multimodal transportation networks. The basic hypothesisset forth in this paper is that the integral method results inbetter multimodal transportation network rationalization effects,whereas a multimodal transportation network modelbased on the integral method, once built, can be used as the basisfor all kinds of transportation problems within multimodaltransport. As opposed to linear transport problems, multimodaltransport network can assume very complex shapes. This papercontains a comparison of the partial and integral approach totransp01tation network solving. In the partial approach, astraightforward model of a transp01tation network, which canbe solved through the use of the Solver computer tool within theExcel spreadsheet inteiface, is quite sufficient. In the solving ofa multimodal transportation problem through the integralmethod, it is necessmy to apply sophisticated mathematicalmodelling programming languages which supp01t the use ofcomplex matrix functions and the processing of a vast amountof variables and limitations. The LINGO programming languageis more abstract than the Excel spreadsheet, and it requiresa certain programming knowledge. The definition andpresentation of a problem logic within Excel, in a manner whichis acceptable to computer software, is an ideal basis for modellingin the LINGO programming language, as well as a fasterand more effective implementation of the mathematical model.This paper provides proof for the fact that it is more rational tosolve the problem of multimodal transportation networks by

Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction

Directory of Open Access Journals (Sweden)

Magdalena Daniela NEMES

2013-01-01

Full Text Available Predicting future prices by using time series forecasting models has become a relevant trading strategy for most stock market players. Intuition and speculation are no longer reliable as many new trading strategies based on artificial intelligence emerge. Data mining represents a good source of information, as it ensures data processing in a convenient manner. Neural networks are considered useful prediction models when designing forecasting strategies. In this paper we present a series of neural networks designed for stock exchange rates forecasting applied on three Romanian stocks traded on the Bucharest Stock Exchange (BSE. A multistep ahead strategy was used in order to predict short-time price fluctuations. Later, the findings of our study can be integrated with an intelligent multi-agent system model which uses data mining and data stream processing techniques for helping users in the decision making process of buying or selling stocks.

Integrating non-animal test information into an adaptive testing strategy - skin sensitization proof of concept case.

Science.gov (United States)

Jaworska, Joanna; Harol, Artsiom; Kern, Petra S; Gerberick, G Frank

2011-01-01

There is an urgent need to develop data integration and testing strategy frameworks allowing interpretation of results from animal alternative test batteries. To this end, we developed a Bayesian Network Integrated Testing Strategy (BN ITS) with the goal to estimate skin sensitization hazard as a test case of previously developed concepts (Jaworska et al., 2010). The BN ITS combines in silico, in chemico, and in vitro data related to skin penetration, peptide reactivity, and dendritic cell activation, and guides testing strategy by Value of Information (VoI). The approach offers novel insights into testing strategies: there is no one best testing strategy, but the optimal sequence of tests depends on information at hand, and is chemical-specific. Thus, a single generic set of tests as a replacement strategy is unlikely to be most effective. BN ITS offers the possibility of evaluating the impact of generating additional data on the target information uncertainty reduction before testing is commenced.

Dynamic Routing and Coordination in Multi-Agent Networks

Science.gov (United States)

2016-06-10

epidemics spreading . Bibliography (J1) F. Pasqualetti, S. Zampieri, and F. Bullo. Controllability metrics, limitations and algorithms for complex networks ...controllability properties of the clusters and on their coupling strength. We validate our results with examples from power networks , social networks , and...SECURITY CLASSIFICATION OF: Supported by this project, we designed innovative routing, planning and coordination strategies for robotic networks and

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

Tactical Network Load Balancing in Multi-Gateway Wireless Sensor Networks

Science.gov (United States)

2013-12-01

communication technology ARPANET Advanced Research Projects Agency Network ASN autonomous sensor network CBR constant bit rate CDMA code...transmission energy NFC near field communication OV1 operational view xxii PA power amplifier RFC request for comment RFID radio frequency identification...fact that the integrated chip (IC) technology boom during the past 20+ years has miniaturized IC hardware while increasing computational capability

Wellbore Integrity Network

Energy Technology Data Exchange (ETDEWEB)

Carey, James W. [Los Alamos National Laboratory; Bachu, Stefan [Alberta Innovates

2012-06-21

In this presentation, we review the current state of knowledge on wellbore integrity as developed in the IEA Greenhouse Gas Programme's Wellbore Integrity Network. Wells are one of the primary risks to the successful implementation of CO{sub 2} storage programs. Experimental studies show that wellbore materials react with CO{sub 2} (carbonation of cement and corrosion of steel) but the impact on zonal isolation is unclear. Field studies of wells in CO{sub 2}-bearing fields show that CO{sub 2} does migrate external to casing. However, rates and amounts of CO{sub 2} have not been quantified. At the decade time scale, wellbore integrity is driven by construction quality and geomechanical processes. Over longer time-scales (> 100 years), chemical processes (cement degradation and corrosion) become more important, but competing geomechanical processes may preserve wellbore integrity.

Multi-digit handwritten sindhi numerals recognition using som neural network

International Nuclear Information System (INIS)

Chandio, A.A.; Jalbani, A.H.; Awan, S.A.

2017-01-01

In this research paper a multi-digit Sindhi handwritten numerals recognition system using SOM Neural Network is presented. Handwritten digits recognition is one of the challenging tasks and a lot of research is being carried out since many years. A remarkable work has been done for recognition of isolated handwritten characters as well as digits in many languages like English, Arabic, Devanagari, Chinese, Urdu and Pashto. However, the literature reviewed does not show any remarkable work done for Sindhi numerals recognition. The recognition of Sindhi digits is a difficult task due to the various writing styles and different font sizes. Therefore, SOM (Self-Organizing Map), a NN (Neural Network) method is used which can recognize digits with various writing styles and different font sizes. Only one sample is required to train the network for each pair of multi-digit numerals. A database consisting of 4000 samples of multi-digits consisting only two digits from 10-50 and other matching numerals have been collected by 50 users and the experimental results of proposed method show that an accuracy of 86.89% is achieved. (author)

Multi-Channel Multi-Radio Using 802.11 Based Media Access for Sink Nodes in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Kok-Keong Loo

2011-05-01

Full Text Available The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Multi-channel multi-radio using 802.11 based media access for sink nodes in wireless sensor networks.

Science.gov (United States)

Campbell, Carlene E-A; Khan, Shafiullah; Singh, Dhananjay; Loo, Kok-Keong

2011-01-01

The next generation surveillance and multimedia systems will become increasingly deployed as wireless sensor networks in order to monitor parks, public places and for business usage. The convergence of data and telecommunication over IP-based networks has paved the way for wireless networks. Functions are becoming more intertwined by the compelling force of innovation and technology. For example, many closed-circuit TV premises surveillance systems now rely on transmitting their images and data over IP networks instead of standalone video circuits. These systems will increase their reliability in the future on wireless networks and on IEEE 802.11 networks. However, due to limited non-overlapping channels, delay, and congestion there will be problems at sink nodes. In this paper we provide necessary conditions to verify the feasibility of round robin technique in these networks at the sink nodes by using a technique to regulate multi-radio multichannel assignment. We demonstrate through simulations that dynamic channel assignment scheme using multi-radio, and multichannel configuration at a single sink node can perform close to optimal on the average while multiple sink node assignment also performs well. The methods proposed in this paper can be a valuable tool for network designers in planning network deployment and for optimizing different performance objectives.

Geophysical monitoring of a complex geologic framework: the multi-disciplinary sensor networks in Sicily (Italy)

Science.gov (United States)

Cantarero, M.; Di Prima, S.; Mattia, M.; Patanè, D.; Rossi, M.

2012-04-01

Since 2004 the Osservatorio Etneo INGV has begun a new approach to the geophysical monitoring of volcanic and seismic areas of Sicily (Italy) where the core is a new type of remote infrastructure able to efficiently accommodate different kinds of sensor. In particular our multi-parametric network is mainly focused on the monitoring of different geophysical parameters (seismic ground velocity and acceleration, infrasound and ground deformation GPS).The whole seismic network consists of 66 broad band digital stations, 19 analog stations, 13 accelerometric stations and 12 infrasonic stations, for a total of 110 stations while the Continuous GPS network consist of 80 stations. Every station is equipped with solar panels in order to satisfy the power requirements of the instruments and with satellite-based communication systems. In this work we show both the technical solutions of this integrated network and its main advantages, if compared with older kinds of remote stations. Moreover we show some examples of the more interesting scientific results achieved thank to this technologically advanced network.

Multi-valued LSI/VLSI logic design

Science.gov (United States)

Santrakul, K.

A procedure for synthesizing any large complex logic system, such as LSI and VLSI integrated circuits is described. This scheme uses Multi-Valued Multi-plexers (MVMUX) as the basic building blocks and the tree as the structure of the circuit realization. Simple built-in test circuits included in the network (the main current), provide a thorough functional checking of the network at any time. In brief, four major contributions are made: (1) multi-valued Algorithmic State Machine (ASM) chart for describing an LSI/VLSI behavior; (2) a tree-structured multi-valued multiplexer network which can be obtained directly from an ASM chart; (3) a heuristic tree-structured synthesis method for realizing any combinational logic with minimal or nearly-minimal MVMUX; and (4) a hierarchical design of LSI/VLSI with built-in parallel testing capability.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

Science.gov (United States)

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for

Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

Directory of Open Access Journals (Sweden)

Klaus Moessner

2013-10-01

Full Text Available This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines.

Cross-layer optimization of wireless multi-hop networks

OpenAIRE

Soldati, Pablo

2007-01-01

The interest in wireless communications has grown constantly for the past decades, leading to an enormous number of applications and services embraced by billions of users. In order to meet the increasing demand for mobile Internet access, several high data-rate radio networking technologies have been proposed to offer wide area high-speed wireless communications, eventually replacing fixed (wired) networks for many applications. This thesis considers cross-layer optimization of multi-hop rad...

Cross-Dependency Inference in Multi-Layered Networks: A Collaborative Filtering Perspective.

Science.gov (United States)

Chen, Chen; Tong, Hanghang; Xie, Lei; Ying, Lei; He, Qing

2017-08-01

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network model-multi-layered networks. Examples of such kind of network systems include critical infrastructure networks, biological systems, organization-level collaborations, cross-platform e-commerce, and so forth. One crucial structure that distances multi-layered network from other network models is its cross-layer dependency, which describes the associations between the nodes from different layers. Needless to say, the cross-layer dependency in the network plays an essential role in many data mining applications like system robustness analysis and complex network control. However, it remains a daunting task to know the exact dependency relationships due to noise, limited accessibility, and so forth. In this article, we tackle the cross-layer dependency inference problem by modeling it as a collective collaborative filtering problem. Based on this idea, we propose an effective algorithm Fascinate that can reveal unobserved dependencies with linear complexity. Moreover, we derive Fascinate-ZERO, an online variant of Fascinate that can respond to a newly added node timely by checking its neighborhood dependencies. We perform extensive evaluations on real datasets to substantiate the superiority of our proposed approaches.

Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

DEFF Research Database (Denmark)

Zhang, Chunyu; Ding, Yi; Wu, Qiuwei

2013-01-01

This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO...... algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified...