CMon: Multi-Domain Circuit Monitoring System Based on GÉANT perfSONAR MDM

DEFF Research Database (Denmark)

Yu, Hao; Kulkarni, Trupti; Liu, Feng

2014-01-01

Global research collaborations today require robust, secure and dedicated network connections to facilitate data communication between collaborating partners. In order to manage and process such large amount of data, dedicated connections are required to transport data in a highly efficient manne...... to multi-domain VPNs, multicast networks etc....

Structural and functional analysis of multi-interface domains.

Directory of Open Access Journals (Sweden)

Liang Zhao

Full Text Available A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of proteins have the multi-interface property, however the involved multi-interface domains account for only a tiny fraction (1.8% of the total number of domains. The interfaces of these domains are distinguishable in terms of their fingerprints, indicating the functional specificity of the multiple interfaces in a domain. Furthermore, we observed that both cooperative and distinctive structural patterns, which will be useful for protein engineering, exist in the multiple interfaces of a domain.

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.

MUPBED - interworking challenges in a multi-domain and multi-technology network environment

DEFF Research Database (Denmark)

Foisel, Hans-Martin; Spaeth, Jan; Cavazzoni, Carlo

2007-01-01

Todays data transport networks are evolving continuously towards customer oriented and application aware networks. This evolution happens in Europe in a highly diverse network environment, covering multiple network domains, layers, technologies, control and management approaches. In this paper...

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.

Architecture of the Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet)

Energy Technology Data Exchange (ETDEWEB)

Aiken, R.J.; Carlson, R.A.; Foster, I.T. [and others

1997-01-01

The research and education (R&E) community requires persistent and scaleable network infrastructure to concurrently support production and research applications as well as network research. In the past, the R&E community has relied on supporting parallel network and end-node infrastructures, which can be very expensive and inefficient for network service managers and application programmers. The grand challenge in networking is to provide support for multiple, concurrent, multi-layer views of the network for the applications and the network researchers, and to satisfy the sometimes conflicting requirements of both while ensuring one type of traffic does not adversely affect the other. Internet and telecommunications service providers will also benefit from a multi-modal infrastructure, which can provide smoother transitions to new technologies and allow for testing of these technologies with real user traffic while they are still in the pre-production mode. The authors proposed approach requires the use of as much of the same network and end system infrastructure as possible to reduce the costs needed to support both classes of activities (i.e., production and research). Breaking the infrastructure into segments and objects (e.g., routers, switches, multiplexors, circuits, paths, etc.) gives the capability to dynamically construct and configure the virtual active networks to address these requirements. These capabilities must be supported at the campus, regional, and wide-area network levels to allow for collaboration by geographically dispersed groups. The Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet) described in this report is an initial architecture and framework designed to identify and support the capabilities needed for the proposed combined infrastructure and to address related research issues.

A distributed framework for inter-domain virtual network embedding

Science.gov (United States)

Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

2013-03-01

Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

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.

Network cyberinfrastructure as a shared platform to support multi-site research

Science.gov (United States)

Multi-site research across the Long-term Agroecosystem Research (LTAR) network requires access to data and information. We present some existing examples where you can get data from across the network and summarize the rich inventory of measurements taken across LTAR sites. But data management suppo...

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.

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

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

Science.gov (United States)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.

Path finding using the multi-layer network description language

NARCIS (Netherlands)

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

2008-01-01

Research networks are providing their users with dedicated network connections. Users want these connects to go through different domains, so the research networks are challenged to find valid network connections through multiple domains. The challenge arises if the different network domains use

Multi-hop routing in wireless sensor networks an overview, taxonomy, and research challenges

CERN Document Server

Rani, Shalli

2016-01-01

This brief provides an overview of recent developments in multi-hop routing protocols for Wireless Sensor Networks (WSNs). It introduces the various classifications of routing protocols and lists the pros and cons of each category, going beyond the conceptual overview of routing classifications offered in other books. Recently many researchers have proposed numerous multi-hop routing protocols and thereby created a need for a book that provides its readers with an up-to-date road map of this research paradigm.   The authors present some of the most relevant results achieved by applying an algorithmic approach to the research on multi-hop routing protocols. The book covers measurements, experiences and lessons learned from the implementation of multi-hop communication prototypes. Furthermore, it describes future research challenges and as such serves as a useful guide for students and researchers alike.

A Model of Inter and Multi Disciplinary Domains, and their Mutual Interactions

Directory of Open Access Journals (Sweden)

Ophir Dan

2014-02-01

Full Text Available The Melvil Dewey Decimal Classification system maps the human knowledge domains into a library classification decimal system, which means that the knowledge is discretized. The domains are countable similarly to how Cantor proved the countability of the fractions' domain. The debate about the "inter-" and "multi-" disciplinary domains may also be extended into "sub-domains" or from another point of view – into "super-domains". However, Science and Technology has rapidly developed after it was classified. If at the beginning, two decimal digits were enough to classify the world's knowledge into a knowledge domain, today we need more digits – about five. This means we are able to display about a million domains of knowledge. The decimal point indicates the sub-division in the zooming-in; the number of such decimal points is unlimited. Thus, the number of hierarchical levels in the knowledge-tree is unlimited. The maximal level is unreachable since it propagates in time. This intriguing issue raises doubts whether the tree is the most appropriate structure in the current state of the knowledge classification. However, I believe that the knowledge tree is a convenient way of expressing various connections between the knowledge domains. There are other models such as multi-level graph-networks that approximate closer to reality. These models can be further visualized by graph diagrams. The knowledge diagram is more complicated, considering the interaction between science and industry relative to each domain. The model of reality might be compared to the object-oriented programming languages approximating reality in order to construct more naturally computer programs that can model the world. The mutual correspondence of the knowledge domains is dynamic. Some examples of relatively new domains are as follows: biotechnology, bioinformatics, nanotechnology, integro-differential equations, data warehouse, data mining, requirements engineering, micro

A Multi-Hop Advertising Discovery and Delivering Protocol for Multi Administrative Domain MANET

Directory of Open Access Journals (Sweden)

Federico Mari

2013-01-01

Full Text Available A Mobile Ad-hoc NETwork (MANET is Multi Administrative Domain (MAD if each network node belongs to an independent authority, that is each node owns its resources and there is no central authority owning all network nodes. One of the main obstructions in designing Service Advertising, Discovery and Delivery (SADD protocol for MAD MANETs is the fact that, in an attempt to increase their own visibility, network nodes tend to flood the network with their advertisements. In this paper, we present a SADD protocol for MAD MANET, based on Bloom filters, that effectively prevents advertising floods due to such misbehaving nodes. Our results with the ns-2 simulator show that our SADD protocol is effective in counteracting advertising floods, it keeps low the collision rate as well as the energy consumption while ensuring that each peer receives all messages broadcasted by other peers.

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...

Effective Domain Partitioning for Multi-Clock Domain IP Core Wrapper Design under Power Constraints

Science.gov (United States)

Yu, Thomas Edison; Yoneda, Tomokazu; Zhao, Danella; Fujiwara, Hideo

The rapid advancement of VLSI technology has made it possible for chip designers and manufacturers to embed the components of a whole system onto a single chip, called System-on-Chip or SoC. SoCs make use of pre-designed modules, called IP-cores, which provide faster design time and quicker time-to-market. Furthermore, SoCs that operate at multiple clock domains and very low power requirements are being utilized in the latest communications, networking and signal processing devices. As a result, the testing of SoCs and multi-clock domain embedded cores under power constraints has been rapidly gaining importance. In this research, a novel method for designing power-aware test wrappers for embedded cores with multiple clock domains is presented. By effectively partitioning the various clock domains, we are able to increase the solution space of possible test schedules for the core. Since previous methods were limited to concurrently testing all the clock domains, we effectively remove this limitation by making use of bandwidth conversion, multiple shift frequencies and properly gating the clock signals to control the shift activity of various core logic elements. The combination of the above techniques gains us greater flexibility when determining an optimal test schedule under very tight power constraints. Furthermore, since it is computationally intensive to search the entire expanded solution space for the possible test schedules, we propose a heuristic 3-D bin packing algorithm to determine the optimal wrapper architecture and test schedule while minimizing the test time under power and bandwidth constraints.

Building a Multi-centre Clinical Research Facilitation Network: The ARC Experience

Directory of Open Access Journals (Sweden)

Ian Nicholson

2017-06-01

Full Text Available Introduction: In order to practice evidence-based veterinary medicine, good quality clinical evidence needs to be produced, in order that it can be apprasied systematically by the EBVM network, and used by vets. There is very little good-quality veterinary evidence for most of the veterinary procedures carried out every day across the world. Very few, if any, individuals have all the necessary qualities (case-load, time, research expertise, financial support to be able to systematically produce good-quality, and relevant, clinical research on their own, in a timely manner. The Association for Veterinary Soft Tissue Surgery (AVSTS www.avsts.org.uk is an affiliate group with the British Small Animal Veterinary Association (BSAVA, and functions as a clinical network of like-minded individuals. In 2013 AVSTS sought to create a role for itself in facilitating the production (by its members of multi-centre clinical research of relevance to its members.Materials and methods: Members of AVSTS were asked to join the AVSTS Research Cooperative (ARC, with a veterinary epidemiologist and an experienced multi-centre veterinary clinical researcher (to help with study design and statistical planning, and the Animal Health Trust clinical research ethics committee. An email list was established, and a page was set up on the AVSTS website, to allow information to be disseminated. The AVSTS spring and autumn meetings were used as a regular forum by ARC, to discuss its direction, to generate interest, to create and promote specific studies (in order to widen participation amongst different centres, and to update members about previous studies.Results: Membership of ARC has grown to 224 people, although the epidemiologist left. One multi-centre study has been published, two have been presented and await publication, one has been accepted for presentation, two other studies are gathering data at present, and further studies are in the pipeline. There has been

Multi-Domain Modeling Based on Modelica

Directory of Open Access Journals (Sweden)

Liu Jun

2016-01-01

Full Text Available With the application of simulation technology in large-scale and multi-field problems, multi-domain unified modeling become an effective way to solve these problems. This paper introduces several basic methods and advantages of the multidisciplinary model, and focuses on the simulation based on Modelica language. The Modelica/Mworks is a newly developed simulation software with features of an object-oriented and non-casual language for modeling of the large, multi-domain system, which makes the model easier to grasp, develop and maintain.It This article shows the single degree of freedom mechanical vibration system based on Modelica language special connection mechanism in Mworks. This method that multi-domain modeling has simple and feasible, high reusability. it closer to the physical system, and many other advantages.

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.

A Logic for Inclusion of Administrative Domains and Administrators in Multi-domain Authorization

Science.gov (United States)

Iranmanesh, Zeinab; Amini, Morteza; Jalili, Rasool

Authorization policies for an administrative domain or a composition of multiple domains in multi-domain environments are determined by either one administrator or multiple administrators' cooperation. Several logic-based models for multi-domain environments' authorization have been proposed; however, they have not considered administrators and administrative domains in policies' representation. In this paper, we propose the syntax, proof theory, and semantics of a logic for multi-domain authorization policies including administrators and administrative domains. Considering administrators in policies provides the possibility of presenting composite administration having applicability in many collaborative applications. Indeed, administrators and administrative domains stated in policies can be used in authorization. The presented logic is based on modal logic and utilizes two calculi named the calculus of administrative domains and the calculus of administrators. It is also proved that the logic is sound. A case study is presented signifying the logic application in practical projects.

Domain wall networks on solitons

International Nuclear Information System (INIS)

Sutcliffe, Paul

2003-01-01

Domain wall networks on the surface of a soliton are studied in a simple theory. It consists of two complex scalar fields, in 3+1 dimensions, with a global U(1)xZ n symmetry, where n>2. Solutions are computed numerically in which one of the fields forms a Q ball and the other field forms a network of domain walls localized on the surface of the Q ball. Examples are presented in which the domain walls lie along the edges of a spherical polyhedron, forming junctions at its vertices. It is explained why only a small restricted class of polyhedra can arise as domain wall networks

Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains.

Science.gov (United States)

Vishwanath, Sneha; de Brevern, Alexandre G; Srinivasan, Narayanaswamy

2018-02-01

The majority of the proteins encoded in the genomes of eukaryotes contain more than one domain. Reasons for high prevalence of multi-domain proteins in various organisms have been attributed to higher stability and functional and folding advantages over single-domain proteins. Despite these advantages, many proteins are composed of only one domain while their homologous domains are part of multi-domain proteins. In the study presented here, differences in the properties of protein domains in single-domain and multi-domain systems and their influence on functions are discussed. We studied 20 pairs of identical protein domains, which were crystallized in two forms (a) tethered to other proteins domains and (b) tethered to fewer protein domains than (a) or not tethered to any protein domain. Results suggest that tethering of domains in multi-domain proteins influences the structural, dynamic and energetic properties of the constituent protein domains. 50% of the protein domain pairs show significant structural deviations while 90% of the protein domain pairs show differences in dynamics and 12% of the residues show differences in the energetics. To gain further insights on the influence of tethering on the function of the domains, 4 pairs of homologous protein domains, where one of them is a full-length single-domain protein and the other protein domain is a part of a multi-domain protein, were studied. Analyses showed that identical and structurally equivalent functional residues show differential dynamics in homologous protein domains; though comparable dynamics between in-silico generated chimera protein and multi-domain proteins were observed. From these observations, the differences observed in the functions of homologous proteins could be attributed to the presence of tethered domain. Overall, we conclude that tethered domains in multi-domain proteins not only provide stability or folding advantages but also influence pathways resulting in differences in

An Optimal Path Computation Architecture for the Cloud-Network on Software-Defined Networking

Directory of Open Access Journals (Sweden)

Hyunhun Cho

2015-05-01

Full Text Available Legacy networks do not open the precise information of the network domain because of scalability, management and commercial reasons, and it is very hard to compute an optimal path to the destination. According to today’s ICT environment change, in order to meet the new network requirements, the concept of software-defined networking (SDN has been developed as a technological alternative to overcome the limitations of the legacy network structure and to introduce innovative concepts. The purpose of this paper is to propose the application that calculates the optimal paths for general data transmission and real-time audio/video transmission, which consist of the major services of the National Research & Education Network (NREN in the SDN environment. The proposed SDN routing computation (SRC application is designed and applied in a multi-domain network for the efficient use of resources, selection of the optimal path between the multi-domains and optimal establishment of end-to-end connections.

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...

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

Acquisition of a Multi-Domain Advanced Real-Time Simulator to Support DoD-focused Interdisciplinary Research at CSUB

Science.gov (United States)

2017-10-17

SECURITY CLASSIFICATION OF: 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES 12. DISTRIBUTION AVAILIBILITY STATEMENT 6...0704-0188 3. DATES COVERED (From - To) - Approved for public release; distribution is unlimited. UU UU UU UU 17-10-2017 25-Jul-2016 24-Jul-2017 Final...Report: Acquisition of a Multi-Domain Advanced Real- Time Simulator to Support DoD-focused Interdisciplinary Research at CSUB The views, opinions and

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

OSiRIS: a distributed Ceph deployment using software defined networking for multi-institutional research

Science.gov (United States)

McKee, Shawn; Kissel, Ezra; Meekhof, Benjeman; Swany, Martin; Miller, Charles; Gregorowicz, Michael

2017-10-01

We report on the first year of the OSiRIS project (NSF Award #1541335, UM, IU, MSU and WSU) which is targeting the creation of a distributed Ceph storage infrastructure coupled together with software-defined networking to provide high-performance access for well-connected locations on any participating campus. The projects goal is to provide a single scalable, distributed storage infrastructure that allows researchers at each campus to read, write, manage and share data directly from their own computing locations. The NSF CC*DNI DIBBS program which funded OSiRIS is seeking solutions to the challenges of multi-institutional collaborations involving large amounts of data and we are exploring the creative use of Ceph and networking to address those challenges. While OSiRIS will eventually be serving a broad range of science domains, its first adopter will be the LHC ATLAS detector project via the ATLAS Great Lakes Tier-2 (AGLT2) jointly located at the University of Michigan and Michigan State University. Part of our presentation will cover how ATLAS is using the OSiRIS infrastructure and our experiences integrating our first user community. The presentation will also review the motivations for and goals of the project, the technical details of the OSiRIS infrastructure, the challenges in providing such an infrastructure, and the technical choices made to address those challenges. We will conclude with our plans for the remaining 4 years of the project and our vision for what we hope to deliver by the projects end.

Final Report - Cloud-Based Management Platform for Distributed, Multi-Domain Networks

Energy Technology Data Exchange (ETDEWEB)

Chowdhury, Pulak [Ennetix Inc.; Mukherjee, Biswanath [Ennetix Inc.

2017-11-03

In this Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase II project final report, Ennetix presents the development of a solution for end-to-end monitoring, analysis, and visualization of network performance for distributed networks. This solution benefits enterprises of all sizes, operators of distributed and federated networks, and service providers.

MiDas: automatic extraction of a common domain of discourse in sleep medicine for multi-center data integration.

Science.gov (United States)

Sahoo, Satya S; Ogbuji, Chimezie; Luo, Lingyun; Dong, Xiao; Cui, Licong; Redline, Susan S; Zhang, Guo-Qiang

2011-01-01

Clinical studies often use data dictionaries with controlled sets of terms to facilitate data collection, limited interoperability and sharing at a local site. Multi-center retrospective clinical studies require that these data dictionaries, originating from individual participating centers, be harmonized in preparation for the integration of the corresponding clinical research data. Domain ontologies are often used to facilitate multi-center data integration by modeling terms from data dictionaries in a logic-based language, but interoperability among domain ontologies (using automated techniques) is an unresolved issue. Although many upper-level reference ontologies have been proposed to address this challenge, our experience in integrating multi-center sleep medicine data highlights the need for an upper level ontology that models a common set of terms at multiple-levels of abstraction, which is not covered by the existing upper-level ontologies. We introduce a methodology underpinned by a Minimal Domain of Discourse (MiDas) algorithm to automatically extract a minimal common domain of discourse (upper-domain ontology) from an existing domain ontology. Using the Multi-Modality, Multi-Resource Environment for Physiological and Clinical Research (Physio-MIMI) multi-center project in sleep medicine as a use case, we demonstrate the use of MiDas in extracting a minimal domain of discourse for sleep medicine, from Physio-MIMI's Sleep Domain Ontology (SDO). We then extend the resulting domain of discourse with terms from the data dictionary of the Sleep Heart and Health Study (SHHS) to validate MiDas. To illustrate the wider applicability of MiDas, we automatically extract the respective domains of discourse from 6 sample domain ontologies from the National Center for Biomedical Ontologies (NCBO) and the OBO Foundry.

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.

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

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.

Buffer sizing for multi-hop networks

KAUST Repository

Shihada, Basem

2014-01-28

A cumulative buffer may be defined for an interference domain in a wireless mesh network and distributed among nodes in the network to maintain or improve capacity utilization of network resources in the interference domain without increasing packet queuing delay times. When an interference domain having communications links sharing resources in a network is identified, a cumulative buffer size is calculated. The cumulative buffer may be distributed among buffers in each node of the interference domain according to a simple division or according to a cost function taking into account a distance of the communications link from the source and destination. The network may be monitored and the cumulative buffer size recalculated and redistributed when the network conditions change.

International research networks in pharmaceuticals

DEFF Research Database (Denmark)

Cantner, Uwe; Rake, Bastian

2014-01-01

of scientific publications related to pharmaceutical research and applying social network analysis, we find that both the number of countries and their connectivity increase in almost all disease group specific networks. The cores of the networks consist of high income OECD countries and remain rather stable......Knowledge production and scientific research have become increasingly more collaborative and international, particularly in pharmaceuticals. We analyze this tendency in general and tie formation in international research networks on the country level in particular. Based on a unique dataset...... over time. Using network regression techniques to analyze the network dynamics our results indicate that accumulative advantages based on connectedness and multi-connectivity are positively related to changes in the countries' collaboration intensity whereas various indicators on similarity between...

A child abuse research network: Now what?

Science.gov (United States)

Lindberg, Daniel M; Scribano, Philip V

2017-08-01

As foundational work in preparation for a sustainable, multi-center network devoted to child abuse medical research, we recently used a combination of survey and modified Delphi methodologies to determine research priorities for future multi-center studies. Avoiding missed diagnoses, and improving selected/indicated prevention were the topics rated most highly in terms of research priority. Several constructive commentaries in this issue identify the key challenges which must be overcome to ensure a successful network. Indeed, as with the clinical work of child abuse pediatrics, a scientific network will also require constant collaboration within and outside the community of child abuse pediatricians, the wider medical community, and even non-medical professions. Copyright © 2017 Elsevier Ltd. All rights reserved.

An improved multi-domain convolution tracking algorithm

Science.gov (United States)

Sun, Xin; Wang, Haiying; Zeng, Yingsen

2018-04-01

Along with the wide application of the Deep Learning in the field of Computer vision, Deep learning has become a mainstream direction in the field of object tracking. The tracking algorithm in this paper is based on the improved multidomain convolution neural network, and the VOT video set is pre-trained on the network by multi-domain training strategy. In the process of online tracking, the network evaluates candidate targets sampled from vicinity of the prediction target in the previous with Gaussian distribution, and the candidate target with the highest score is recognized as the prediction target of this frame. The Bounding Box Regression model is introduced to make the prediction target closer to the ground-truths target box of the test set. Grouping-update strategy is involved to extract and select useful update samples in each frame, which can effectively prevent over fitting. And adapt to changes in both target and environment. To improve the speed of the algorithm while maintaining the performance, the number of candidate target succeed in adjusting dynamically with the help of Self-adaption parameter Strategy. Finally, the algorithm is tested by OTB set, compared with other high-performance tracking algorithms, and the plot of success rate and the accuracy are drawn. which illustrates outstanding performance of the tracking algorithm in this paper.

Dynamic configuration management of a multi-standard and multi-mode reconfigurable multi-ASIP architecture for turbo decoding

Science.gov (United States)

Lapotre, Vianney; Gogniat, Guy; Baghdadi, Amer; Diguet, Jean-Philippe

2017-12-01

The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.

Drug-domain interaction networks in myocardial infarction.

Science.gov (United States)

Wang, Haiying; Zheng, Huiru; Azuaje, Francisco; Zhao, Xing-Ming

2013-09-01

It has been well recognized that the pace of the development of new drugs and therapeutic interventions lags far behind biological knowledge discovery. Network-based approaches have emerged as a promising alternative to accelerate the discovery of new safe and effective drugs. Based on the integration of several biological resources including two recently published datasets i.e., Drug-target interactions in myocardial infarction (My-DTome) and drug-domain interaction network, this paper reports the association between drugs and protein domains in the context of myocardial infarction (MI). A MI drug-domain interaction network, My-DDome, was firstly constructed, followed by topological analysis and functional characterization of the network. The results show that My-DDome has a very clear modular structure, where drugs interacting with the same domain(s) within each module tend to have similar therapeutic effects. Moreover it has been found that drugs acting on blood and blood forming organs (ATC code B) and sensory organs (ATC code S) are significantly enriched in My-DDome (p drugs, their known targets, and seemingly unrelated proteins can be revealed.

The architectural design of networks of protein domain architectures.

Science.gov (United States)

Hsu, Chia-Hsin; Chen, Chien-Kuo; Hwang, Ming-Jing

2013-08-23

Protein domain architectures (PDAs), in which single domains are linked to form multiple-domain proteins, are a major molecular form used by evolution for the diversification of protein functions. However, the design principles of PDAs remain largely uninvestigated. In this study, we constructed networks to connect domain architectures that had grown out from the same single domain for every single domain in the Pfam-A database and found that there are three main distinctive types of these networks, which suggests that evolution can exploit PDAs in three different ways. Further analysis showed that these three different types of PDA networks are each adopted by different types of protein domains, although many networks exhibit the characteristics of more than one of the three types. Our results shed light on nature's blueprint for protein architecture and provide a framework for understanding architectural design from a network perspective.

Frailty Assessment in Heart Failure: an Overview of the Multi-domain Approach.

Science.gov (United States)

McDonagh, Julee; Ferguson, Caleb; Newton, Phillip J

2018-02-01

The study aims (1) to provide a contemporary description of frailty assessment in heart failure and (2) to provide an overview of multi-domain frailty assessment in heart failure. Frailty assessment is an important predictive measure for mortality and hospitalisation in individuals with heart failure. To date, there are no frailty assessment instruments validated for use in heart failure. This has resulted in significant heterogeneity between studies regarding the assessment of frailty. The most common frailty assessment instrument used in heart failure is the Frailty Phenotype which focuses on five physical domains of frailty; the appropriateness a purely physical measure of frailty in individuals with heart failure who frequently experience decreased exercise tolerance and shortness of breath is yet to be determined. A limited number of studies have approached frailty assessment using a multi-domain view which may be more clinically relevant in heart failure. There remains a lack of consensus regarding frailty assessment and an absence of a validated instrument in heart failure. Despite this, frailty continues to be assessed frequently, primarily for research purposes, using predominantly physical frailty measures. A more multidimensional view of frailty assessment using a multi-domain approach will likely be more sensitive to identifying at risk patients.

Comprehensive Oncologic Emergencies Research Network (CONCERN)

Science.gov (United States)

The Comprehensive Oncologic Emergencies Research Network (CONCERN) was established in March 2015 with the goal to accelerate knowledge generation, synthesis and translation of oncologic emergency medicine research through multi-center collaborations.

A multi-scale network method for two-phase flow in porous media

Energy Technology Data Exchange (ETDEWEB)

Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

2017-08-01

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

A multi-scale network method for two-phase flow in porous media

International Nuclear Information System (INIS)

Khayrat, Karim; Jenny, Patrick

2017-01-01

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

Evolution of a protein domain interaction network

International Nuclear Information System (INIS)

Li-Feng, Gao; Jian-Jun, Shi; Shan, Guan

2010-01-01

In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)

The DIMA web resource--exploring the protein domain network.

Science.gov (United States)

Pagel, Philipp; Oesterheld, Matthias; Stümpflen, Volker; Frishman, Dmitrij

2006-04-15

Conserved domains represent essential building blocks of most known proteins. Owing to their role as modular components carrying out specific functions they form a network based both on functional relations and direct physical interactions. We have previously shown that domain interaction networks provide substantially novel information with respect to networks built on full-length protein chains. In this work we present a comprehensive web resource for exploring the Domain Interaction MAp (DIMA), interactively. The tool aims at integration of multiple data sources and prediction techniques, two of which have been implemented so far: domain phylogenetic profiling and experimentally demonstrated domain contacts from known three-dimensional structures. A powerful yet simple user interface enables the user to compute, visualize, navigate and download domain networks based on specific search criteria. http://mips.gsf.de/genre/proj/dima

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

Directory of Open Access Journals (Sweden)

McDermott Drew

2009-08-01

Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale

Science.gov (United States)

Schut, Marc; Hermans, Frans; van Asten, Piet; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs–local-level actors–left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts. PMID:29870559

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale.

Science.gov (United States)

Sartas, Murat; Schut, Marc; Hermans, Frans; Asten, Piet van; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs-local-level actors-left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts.

Multi-PAS domain-mediated protein oligomerization of PpsR from Rhodobacter sphaeroides

International Nuclear Information System (INIS)

Heintz, Udo; Meinhart, Anton; Winkler, Andreas

2014-01-01

Crystal structures of two truncated variants of the transcription factor PpsR from R. sphaeroides are presented that enabled the phasing of a triple PAS domain construct. Together, these structures reveal the importance of α-helical PAS extensions for multi-PAS domain-mediated protein oligomerization and function. Per–ARNT–Sim (PAS) domains are essential modules of many multi-domain signalling proteins that mediate protein interaction and/or sense environmental stimuli. Frequently, multiple PAS domains are present within single polypeptide chains, where their interplay is required for protein function. Although many isolated PAS domain structures have been reported over the last decades, only a few structures of multi-PAS proteins are known. Therefore, the molecular mechanism of multi-PAS domain-mediated protein oligomerization and function is poorly understood. The transcription factor PpsR from Rhodobacter sphaeroides is such a multi-PAS domain protein that, in addition to its three PAS domains, contains a glutamine-rich linker and a C-terminal helix–turn–helix DNA-binding motif. Here, crystal structures of two N-terminally and C-terminally truncated PpsR variants that comprise a single (PpsR Q-PAS1 ) and two (PpsR N-Q-PAS1 ) PAS domains, respectively, are presented and the multi-step strategy required for the phasing of a triple PAS domain construct (PpsR ΔHTH ) is illustrated. While parts of the biologically relevant dimerization interface can already be observed in the two shorter constructs, the PpsR ΔHTH structure reveals how three PAS domains enable the formation of multiple oligomeric states (dimer, tetramer and octamer), highlighting that not only the PAS cores but also their α-helical extensions are essential for protein oligomerization. The results demonstrate that the long helical glutamine-rich linker of PpsR results from a direct fusion of the N-cap of the PAS1 domain with the C-terminal extension of the N-domain that plays an important

A multi-domain trust management model for supporting RFID applications of IoT.

Directory of Open Access Journals (Sweden)

Xu Wu

Full Text Available The use of RFID technology in complex and distributed environments often leads to a multi-domain RFID system, in which trust establishment among entities from heterogeneous domains without past interaction or prior agreed policy, is a challenge. The current trust management mechanisms in the literature do not meet the specific requirements in multi-domain RFID systems. Therefore, this paper analyzes the special challenges on trust management in multi-domain RFID systems, and identifies the implications and the requirements of the challenges on the solutions to the trust management of multi-domain RFID systems. A multi-domain trust management model is proposed, which provides a hierarchical trust management framework include a diversity of trust evaluation and establishment approaches. The simulation results and analysis show that the proposed method has excellent ability to deal with the trust relationships, better security, and higher accuracy rate.

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...

Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach.

Science.gov (United States)

Zou, Cunlu; Ladroue, Christophe; Guo, Shuixia; Feng, Jianfeng

2010-06-21

Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs) and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE), Bayesian networks, information theory and Granger Causality. Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins). For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.

Identifying interactions in the time and frequency domains in local and global networks - A Granger Causality Approach

Directory of Open Access Journals (Sweden)

Guo Shuixia

2010-06-01

Full Text Available Abstract Background Reverse-engineering approaches such as Bayesian network inference, ordinary differential equations (ODEs and information theory are widely applied to deriving causal relationships among different elements such as genes, proteins, metabolites, neurons, brain areas and so on, based upon multi-dimensional spatial and temporal data. There are several well-established reverse-engineering approaches to explore causal relationships in a dynamic network, such as ordinary differential equations (ODE, Bayesian networks, information theory and Granger Causality. Results Here we focused on Granger causality both in the time and frequency domain and in local and global networks, and applied our approach to experimental data (genes and proteins. For a small gene network, Granger causality outperformed all the other three approaches mentioned above. A global protein network of 812 proteins was reconstructed, using a novel approach. The obtained results fitted well with known experimental findings and predicted many experimentally testable results. In addition to interactions in the time domain, interactions in the frequency domain were also recovered. Conclusions The results on the proteomic data and gene data confirm that Granger causality is a simple and accurate approach to recover the network structure. Our approach is general and can be easily applied to other types of temporal data.

An automatic method to generate domain-specific investigator networks using PubMed abstracts

Directory of Open Access Journals (Sweden)

Gwinn Marta

2007-06-01

Full Text Available Abstract Background Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. Results We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8% and from 94.2% of HuGE PubMed records (accuracy 87.0. We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit, indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. Conclusion We successfully created a

An automatic method to generate domain-specific investigator networks using PubMed abstracts

Science.gov (United States)

Yu, Wei; Yesupriya, Ajay; Wulf, Anja; Qu, Junfeng; Gwinn, Marta; Khoury, Muin J

2007-01-01

Background Collaboration among investigators has become critical to scientific research. This includes ad hoc collaboration established through personal contacts as well as formal consortia established by funding agencies. Continued growth in online resources for scientific research and communication has promoted the development of highly networked research communities. Extending these networks globally requires identifying additional investigators in a given domain, profiling their research interests, and collecting current contact information. We present a novel strategy for building investigator networks dynamically and producing detailed investigator profiles using data available in PubMed abstracts. Results We developed a novel strategy to obtain detailed investigator information by automatically parsing the affiliation string in PubMed records. We illustrated the results by using a published literature database in human genome epidemiology (HuGE Pub Lit) as a test case. Our parsing strategy extracted country information from 92.1% of the affiliation strings in a random sample of PubMed records and in 97.0% of HuGE records, with accuracies of 94.0% and 91.0%, respectively. Institution information was parsed from 91.3% of the general PubMed records (accuracy 86.8%) and from 94.2% of HuGE PubMed records (accuracy 87.0). We demonstrated the application of our approach to dynamic creation of investigator networks by creating a prototype information system containing a large database of PubMed abstracts relevant to human genome epidemiology (HuGE Pub Lit), indexed using PubMed medical subject headings converted to Unified Medical Language System concepts. Our method was able to identify 70–90% of the investigators/collaborators in three different human genetics fields; it also successfully identified 9 of 10 genetics investigators within the PREBIC network, an existing preterm birth research network. Conclusion We successfully created a web-based prototype

A Service-Oriented Approach for Dynamic Chaining of Virtual Network Functions over Multi-Provider Software-Defined Networks

Directory of Open Access Journals (Sweden)

Barbara Martini

2016-06-01

Full Text Available Emerging technologies such as Software-Defined Networks (SDN and Network Function Virtualization (NFV promise to address cost reduction and flexibility in network operation while enabling innovative network service delivery models. However, operational network service delivery solutions still need to be developed that actually exploit these technologies, especially at the multi-provider level. Indeed, the implementation of network functions as software running over a virtualized infrastructure and provisioned on a service basis let one envisage an ecosystem of network services that are dynamically and flexibly assembled by orchestrating Virtual Network Functions even across different provider domains, thereby coping with changeable user and service requirements and context conditions. In this paper we propose an approach that adopts Service-Oriented Architecture (SOA technology-agnostic architectural guidelines in the design of a solution for orchestrating and dynamically chaining Virtual Network Functions. We discuss how SOA, NFV, and SDN may complement each other in realizing dynamic network function chaining through service composition specification, service selection, service delivery, and placement tasks. Then, we describe the architecture of a SOA-inspired NFV orchestrator, which leverages SDN-based network control capabilities to address an effective delivery of elastic chains of Virtual Network Functions. Preliminary results of prototype implementation and testing activities are also presented. The benefits for Network Service Providers are also described that derive from the adaptive network service provisioning in a multi-provider environment through the orchestration of computing and networking services to provide end users with an enhanced service experience.

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.

Using domain-specific basic functions for the analysis of supervised artificial neural networks

NARCIS (Netherlands)

van der Zwaag, B.J.

2003-01-01

Since the early development of artificial neural networks, researchers have tried to analyze trained neural networks in order to gain insight into their behavior. For certain applications and in certain problem domains this has been successful, for example by the development of so-called rule

Cross-Domain Analogies as Relating Derived Relations among Two Separate Relational Networks

Science.gov (United States)

Ruiz, Francisco J; Luciano, Carmen

2011-01-01

Contemporary behavior analytic research is making headway in analyzing analogy as the establishment of a relation of coordination among common types of trained or derived relations. Previous studies have been focused on within-domain analogy. The current study expands previous research by analyzing cross-domain analogy as relating relations among separate relational networks and by correlating participants' performance with a standard measure of analogical reasoning. In two experiments, adult participants first completed general intelligence and analogical reasoning tests. Subsequently, they were exposed to a computerized conditional discrimination training procedure designed to create two relational networks, each consisting of two 3-member equivalence classes. The critical test was a two-part analogical test in which participants had to relate combinatorial relations of coordination and distinction between the two relational networks. In Experiment 1, combinatorial relations for each network were individually tested prior to analogical testing, but in Experiment 2 they were not. Across both experiments, 65% of participants passed the analogical test on the first attempt. Moreover, results from the training procedure were strongly correlated with the standard measure of analogical reasoning. PMID:21547072

Evolution of SH2 domains and phosphotyrosine signalling networks

Science.gov (United States)

Liu, Bernard A.; Nash, Piers D.

2012-01-01

Src homology 2 (SH2) domains mediate selective protein–protein interactions with tyrosine phosphorylated proteins, and in doing so define specificity of phosphotyrosine (pTyr) signalling networks. SH2 domains and protein-tyrosine phosphatases expand alongside protein-tyrosine kinases (PTKs) to coordinate cellular and organismal complexity in the evolution of the unikont branch of the eukaryotes. Examination of conserved families of PTKs and SH2 domain proteins provides fiduciary marks that trace the evolutionary landscape for the development of complex cellular systems in the proto-metazoan and metazoan lineages. The evolutionary provenance of conserved SH2 and PTK families reveals the mechanisms by which diversity is achieved through adaptations in tissue-specific gene transcription, altered ligand binding, insertions of linear motifs and the gain or loss of domains following gene duplication. We discuss mechanisms by which pTyr-mediated signalling networks evolve through the development of novel and expanded families of SH2 domain proteins and the elaboration of connections between pTyr-signalling proteins. These changes underlie the variety of general and specific signalling networks that give rise to tissue-specific functions and increasingly complex developmental programmes. Examination of SH2 domains from an evolutionary perspective provides insight into the process by which evolutionary expansion and modification of molecular protein interaction domain proteins permits the development of novel protein-interaction networks and accommodates adaptation of signalling networks. PMID:22889907

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)

The effects of multi-domain versus single-domain cognitive training in non-demented older people: a randomized controlled trial

Directory of Open Access Journals (Sweden)

Cheng Yan

2012-03-01

Full Text Available Abstract Background Whether healthy older people can benefit from cognitive training (CogTr remains controversial. This study explored the benefits of CogTr in community dwelling, healthy, older adults and compared the effects of single-domain with multi-domain CogTr interventions. Methods A randomized, controlled, 3-month trial of CogTr with double-blind assessments at baseline and immediate, 6-month and 12-month follow-up after training completion was conducted. A total of 270 healthy Chinese older people, 65 to 75 years old, were recruited from the Ganquan-area community in Shanghai. Participants were randomly assigned to three groups: multi-domain CogTr, single-domain CogTr, and a wait-list control group. Twenty-four sessions of CogTr were administrated to the intervention groups over a three-month period. Six months later, three booster training sessions were offered to 60% of the initial training participants. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS, Form A, the Color Word Stroop test (CWST, the Visual Reasoning test and the Trail Making test (TMT were used to assess cognitive function. Results Multi-domain CogTr produced statistically significant training effects on RBANS, visual reasoning, and immediate and delayed memory, while single-domain CogTr showed training effects on RBANS, visual reasoning, word interference, and visuospatial/constructional score (all P Conclusions Cognitive training can improve memory, visual reasoning, visuospatial construction, attention and neuropsychological status in community-living older people and can help maintain their functioning over time. Multi-domain CogTr enhanced memory proficiency, while single-domain CogTr augmented visuospatial/constructional and attention abilities. Multi-domain CogTr had more advantages in training effect maintenance. Clinical Trial Registration Chinese Clinical Trial Registry. Registration number: ChiCTR-TRC-09000732.

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

Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

Directory of Open Access Journals (Sweden)

Sheng Wang

2007-10-01

Full Text Available The recent availability of low cost and miniaturized hardware has allowedwireless sensor networks (WSNs to retrieve audio and video data in real worldapplications, which has fostered the development of wireless multimedia sensor networks(WMSNs. Resource constraints and challenging multimedia data volume makedevelopment of efficient algorithms to perform in-network processing of multimediacontents imperative. This paper proposes solving problems in the domain of WMSNs fromthe perspective of multi-agent systems. The multi-agent framework enables flexible networkconfiguration and efficient collaborative in-network processing. The focus is placed ontarget classification in WMSNs where audio information is retrieved by microphones. Todeal with the uncertainties related to audio information retrieval, the statistical approachesof power spectral density estimates, principal component analysis and Gaussian processclassification are employed. A multi-agent negotiation mechanism is specially developed toefficiently utilize limited resources and simultaneously enhance classification accuracy andreliability. The negotiation is composed of two phases, where an auction based approach isfirst exploited to allocate the classification task among the agents and then individual agentdecisions are combined by the committee decision mechanism. Simulation experiments withreal world data are conducted and the results show that the proposed statistical approachesand negotiation mechanism not only reduce memory and computation requi

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

Multi-agent Negotiation Mechanisms for Statistical Target Classification in Wireless Multimedia Sensor Networks

Science.gov (United States)

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

The recent availability of low cost and miniaturized hardware has allowed wireless sensor networks (WSNs) to retrieve audio and video data in real world applications, which has fostered the development of wireless multimedia sensor networks (WMSNs). Resource constraints and challenging multimedia data volume make development of efficient algorithms to perform in-network processing of multimedia contents imperative. This paper proposes solving problems in the domain of WMSNs from the perspective of multi-agent systems. The multi-agent framework enables flexible network configuration and efficient collaborative in-network processing. The focus is placed on target classification in WMSNs where audio information is retrieved by microphones. To deal with the uncertainties related to audio information retrieval, the statistical approaches of power spectral density estimates, principal component analysis and Gaussian process classification are employed. A multi-agent negotiation mechanism is specially developed to efficiently utilize limited resources and simultaneously enhance classification accuracy and reliability. The negotiation is composed of two phases, where an auction based approach is first exploited to allocate the classification task among the agents and then individual agent decisions are combined by the committee decision mechanism. Simulation experiments with real world data are conducted and the results show that the proposed statistical approaches and negotiation mechanism not only reduce memory and computation requirements in WMSNs but also significantly enhance classification accuracy and reliability. PMID:28903223

Enhanced Inter-Cell Interference Coordination in Co-Channel Multi-Layer LTE-Advanced Networks

DEFF Research Database (Denmark)

Pedersen, Klaus I.; Wang, Yuanye; Strzyz, Stanislav

2013-01-01

Different technical solutions and innovations are enabling the move from macro-only scenarios towards heterogeneous networks with a mixture of different base station types. In this article we focus on multi-layer LTE-Advanced networks, and especially address aspects related to interference...... management. The network controlled time-domain enhanced inter-cell interference coordination (eICIC) concept is outlined by explaining the benefits and characteristics of this solution. The benefits of using advanced terminal device receiver architectures with interference suppression capabilities...... are motivated. Extensive system level performance results are presented with bursty traffic to demonstrate the eICIC concepts ability to dynamically adapt according to the traffic conditions....

Scaling properties of domain wall networks

International Nuclear Information System (INIS)

Leite, A. M. M.; Martins, C. J. A. P.

2011-01-01

We revisit the cosmological evolution of domain wall networks, taking advantage of recent improvements in computing power. We carry out high-resolution field theory simulations in two, three and four spatial dimensions to study the effects of dimensionality and damping on the evolution of the network. Our results are consistent with the expected scale-invariant evolution of the network, which suggests that previous hints of deviations from this behavior may have been due to the limited dynamical range of those simulations. We also use the results of very large (1024 3 ) simulations in three cosmological epochs to provide a calibration for the velocity-dependent one-scale model for domain walls: we numerically determine the two free model parameters to have the values c w =0.5±0.2 and k w =1.1±0.3.

Modeling Network Traffic in Wavelet Domain

Directory of Open Access Journals (Sweden)

Sheng Ma

2004-12-01

Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

Nonlinear analysis of sequence repeats of multi-domain proteins

Energy Technology Data Exchange (ETDEWEB)

Huang Yanzhao [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Li Mingfeng [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China); Xiao Yi [Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei (China)]. E-mail: lmf_bill@sina.com

2007-11-15

Many multi-domain proteins have repetitive three-dimensional structures but nearly-random amino acid sequences. In the present paper, by using a modified recurrence plot proposed by us previously, we show that these amino acid sequences have hidden repetitions in fact. These results indicate that the repetitive domain structures are encoded by the repetitive sequences. This also gives a method to detect the repetitive domain structures directly from amino acid sequences.

RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration.

Science.gov (United States)

Luo, Jake; Apperson-Hansen, Carolyn; Pelfrey, Clara M; Zhang, Guo-Qiang

2014-11-30

Cross-institutional cross-disciplinary collaboration has become a trend as researchers move toward building more productive and innovative teams for scientific research. Research collaboration is significantly changing the organizational structure and strategies used in the clinical and translational science domain. However, due to the obstacles of diverse administrative structures, differences in area of expertise, and communication barriers, establishing and managing a cross-institutional research project is still a challenging task. We address these challenges by creating an integrated informatics platform to reduce the barriers to biomedical research collaboration. The Request Management System (RMS) is an informatics infrastructure designed to transform a patchwork of expertise and resources into an integrated support network. The RMS facilitates investigators' initiation of new collaborative projects and supports the management of the collaboration process. In RMS, experts and their knowledge areas are categorized and managed structurally to provide consistent service. A role-based collaborative workflow is tightly integrated with domain experts and services to streamline and monitor the life-cycle of a research project. The RMS has so far tracked over 1,500 investigators with over 4,800 tasks. The research network based on the data collected in RMS illustrated that the investigators' collaborative projects increased close to 3 times from 2009 to 2012. Our experience with RMS indicates that the platform reduces barriers for cross-institutional collaboration of biomedical research projects. Building a new generation of infrastructure to enhance cross-disciplinary and multi-institutional collaboration has become an important yet challenging task. In this paper, we share the experience of developing and utilizing a collaborative project management system. The results of this study demonstrate that a web-based integrated informatics platform can facilitate and

The ICOS Experience: Integration of Multi-disciplinary Data and Beyond Its Domains Into a Network of Networks

Science.gov (United States)

Vermeulen, A. T.; Hellström, M.; Mirzov, O.; Juurola, E.; Lavric, J. V.; Kutsch, W. L.

2016-12-01

ICOS as long-term observational system for the carbon cycle has a long history in Europe, but has only recently been established formally as one of the first European Research Infrastructure Consortia (ERIC). ICOS data will be provided through the ICOS Carbon Portal and data usage will be absolutely unrestricted under the Creative Commons Attribution 4.0 International (CC4.0BY) license. ICOS strives to further integrate its data streams internally across the domains and externally, building on scalable open access tools and open data technologies. Through the ENVRIplus project, led by ICOS, and the EUDAT2020 project, the work on interoperability and scalability is now progressing quickly in the European environmental Research Infrastructures domain. In this presentation we will demonstrate the recent progress in ICOS in implementing the Carbon Portal as the one stop shop for ICOS data.

Measurement of multi-bunch transfer functions using time-domain data and Fourier analysis

International Nuclear Information System (INIS)

Hindi, H.; Sapozhnikov, L.; Fox, J.; Prabhakar, S.; Oxoby, G.; Linscott, I.; Drago, A.

1993-12-01

Multi-bunch transfer functions are principal ingredients in understanding both the behavior of high-current storage rings as well as control of their instabilities. The measurement of transfer functions on a bunch-by-bunch basis is particularly important in the design of active feedback systems. Traditional methods of network analysis that work well in the single bunch case become difficult to implement for many bunches. We have developed a method for obtaining empirical estimates of the multi-bunch longitudinal transfer functions from the time-domain measurements of the bunches' phase oscillations. This method involves recording the response of the bunch of interest to a white-noise excitation. The transfer function can then be computed as the ratio of the fast Fourier transforms (FFTs) of the response and excitation sequences, averaged over several excitations. The calculation is performed off-line on bunch-phase data and is well-suited to the multi-bunch case. A description of this method and an analysis of its performance is presented with results obtained using the longitudinal quick prototype feedback system developed at SLAC

Broadening microwave absorption via a multi-domain structure

Directory of Open Access Journals (Sweden)

Zhengwang Liu

2017-04-01

Full Text Available Materials with a high saturation magnetization have gained increasing attention in the field of microwave absorption; therefore, the magnetization value depends on the magnetic configuration inside them. However, the broad-band absorption in the range of microwave frequency (2-18 GHz is a great challenge. Herein, the three-dimensional (3D Fe/C hollow microspheres are constructed by iron nanocrystals permeating inside carbon matrix with a saturation magnetization of 340 emu/g, which is 1.55 times as that of bulk Fe, unexpectedly. Electron tomography, electron holography, and Lorentz transmission electron microscopy imaging provide the powerful testimony about Fe/C interpenetration and multi-domain state constructed by vortex and stripe domains. Benefiting from the unique chemical and magnetic microstructures, the microwave minimum absorption is as strong as −55 dB and the bandwidth (<−10 dB spans 12.5 GHz ranging from 5.5 to 18 GHz. Morphology and distribution of magnetic nano-domains can be facilely regulated by a controllable reduction sintering under H2/Ar gas and an optimized temperature over 450–850 °C. The findings might shed new light on the synthesis strategies of the materials with the broad-band frequency and understanding the association between multi-domain coupling and microwave absorption performance.

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

Science.gov (United States)

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain

Research Networks, Mentorship and Sustainability Knowledge

Science.gov (United States)

Kafle, A.; Mukhopadhyay, P.; Nepal, M.; Shyamsundar, P.

2015-12-01

In South Asia, a majority of institutions are ill-equipped to undertake research on multi-disciplinary environmental problems, though these problems are increasing at a fast rate and connected to the region's poverty and growth objectives. In this context, the South Asian Network for Development and Environmental Economics (SANDEE) tries to fill a research, training and knowledge gap by building skills in the area of Environment and Development Economics. In this paper, the authors argue that research networks contribute to the growth of sustainability knowledge through (a) knowledge creation, (b) knowledge transfer and (c) knowledge deepening. The paper tries to show the relationship between capacity building, mentorship and research scholarship. It demonstrates that researchers, by associating with the network and its multiple training and mentoring processes, are able to build skills, change curricula and deliver useful knowledge products. The paper discusses the need for interdisciplinary research and the challenges of bridging the gap between research outputs and policy reforms.

Spatial reuse of wireless medium in multi-hop wireless sensor networks

NARCIS (Netherlands)

Geerlings, J.; Geerlings, J.; van Hoesel, L.F.W.; Hoeksema, F.W.; Slump, Cornelis H.; Havinga, Paul J.M.

2007-01-01

The idea of multi-hop communication originates from the 1990’s and is eagerly incorporated in the wireless sensor network research field, since a tremendous amount of energy can be saved by letting —often battery powered– nodes in the network assist each other in forwarding packets. In such systems

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...

DRO: domain-based route optimization scheme for nested mobile networks

Directory of Open Access Journals (Sweden)

Chuang Ming-Chin

2011-01-01

Full Text Available Abstract The network mobility (NEMO basic support protocol is designed to support NEMO management, and to ensure communication continuity between nodes in mobile networks. However, in nested mobile networks, NEMO suffers from the pinball routing problem, which results in long packet transmission delays. To solve the problem, we propose a domain-based route optimization (DRO scheme that incorporates a domain-based network architecture and ad hoc routing protocols for route optimization. DRO also improves the intra-domain handoff performance, reduces the convergence time during route optimization, and avoids the out-of-sequence packet problem. A detailed performance analysis and simulations were conducted to evaluate the scheme. The results demonstrate that DRO outperforms existing mechanisms in terms of packet transmission delay (i.e., better route-optimization, intra-domain handoff latency, convergence time, and packet tunneling overhead.

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.

Orthogonal Multi-Carrier DS-CDMA with Frequency-Domain Equalization

Science.gov (United States)

Tanaka, Ken; Tomeba, Hiromichi; Adachi, Fumiyuki

Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of orthogonal frequency division multiplexing (OFDM) and time-domain spreading, while multi-carrier code division multiple access (MC-CDMA) is a combination of OFDM and frequency-domain spreading. In MC-CDMA, a good bit error rate (BER) performance can be achieved by using frequency-domain equalization (FDE), since the frequency diversity gain is obtained. On the other hand, the conventional orthogonal MC DS-CDMA fails to achieve any frequency diversity gain. In this paper, we propose a new orthogonal MC DS-CDMA that can obtain the frequency diversity gain by applying FDE. The conditional BER analysis is presented. The theoretical average BER performance in a frequency-selective Rayleigh fading channel is evaluated by the Monte-Carlo numerical computation method using the derived conditional BER and is confirmed by computer simulation of the orthogonal MC DS-CDMA signal transmission.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

Science.gov (United States)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

Identification of Non-Linear Structures using Recurrent Neural Networks

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Nielsen, Søren R. K.; Hansen, H. I.

Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure.......Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure....

Identification of Non-Linear Structures using Recurrent Neural Networks

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Nielsen, Søren R. K.; Hansen, H. I.

1995-01-01

Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure.......Two different partially recurrent neural networks structured as Multi Layer Perceptrons (MLP) are investigated for time domain identification of a non-linear structure....

Efficient segmental isotope labeling of multi-domain proteins using Sortase A

Energy Technology Data Exchange (ETDEWEB)

Freiburger, Lee, E-mail: lee.freiburger@tum.de; Sonntag, Miriam, E-mail: miriam.sonntag@mytum.de; Hennig, Janosch, E-mail: janosch.hennig@helmholtz-muenchen.de [Helmholtz Zentrum München, Institute of Structural Biology (Germany); Li, Jian, E-mail: lijianzhongbei@163.com [Chinese Academy of Sciences, Tianjin Institute of Industrial Biotechnology (China); Zou, Peijian, E-mail: peijian.zou@helmholtz-muenchen.de; Sattler, Michael, E-mail: sattler@helmholtz-muenchen.de [Helmholtz Zentrum München, Institute of Structural Biology (Germany)

2015-09-15

NMR studies of multi-domain protein complexes provide unique insight into their molecular interactions and dynamics in solution. For large proteins domain-selective isotope labeling is desired to reduce signal overlap, but available methods require extensive optimization and often give poor ligation yields. We present an optimized strategy for segmental labeling of multi-domain proteins using the S. aureus transpeptidase Sortase A. Critical improvements compared to existing protocols are (1) the efficient removal of cleaved peptide fragments by centrifugal filtration and (2) a strategic design of cleavable and non-cleavable affinity tags for purification. Our approach enables routine production of milligram amounts of purified segmentally labeled protein for NMR and other biophysical studies.

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...

Multi-material micro-electromechanical fibers with bendable functional domains

Science.gov (United States)

Nguyen-Dang, Tung; Page, Alexis G.; Qu, Yunpeng; Volpi, Marco; Yan, Wei; Sorin, Fabien

2017-04-01

The integration of increasingly complex functionalities within thermally drawn multi-material fibers is heralding a novel path towards advanced soft electronics and smart fabrics. Fibers capable of electronic, optoelectronic, piezoelectric or energy harvesting functions are created by assembling new materials in intimate contact within increasingly complex architectures. Thus far, however, the opportunities associated with the integration of cantilever-like structures with freely moving functional domains within multi-material fibers have not been explored. Used extensively in the micro-electromechanical system (MEMS) technology, electro-mechanical transductance from moving and bendable domains is used in a myriad of applications. In this article we demonstrate the thermal drawing of micro-electromechanical fibers (MEMF) that can detect and localize pressure with high accuracy along their entire length. This ability results from an original cantilever-like design where a freestanding electrically conductive polymer composite film bends under an applied pressure. As it comes into contact with another conducting domain, placed at a prescribed position in the fiber cross-section, an electrical signal is generated. We show that by a judicious choice of materials and electrical connectivity, this signal can be uniquely related to a position along the fiber axis. We establish a model that predicts the position of a local touch from the measurement of currents generated in the 1D MEMF device, and demonstrate an excellent agreement with the experimental data. This ability to detect and localize touch over large areas, curved surfaces and textiles holds significant opportunities in robotics and prosthetics, flexible electronic interfaces, and medical textiles. , which features invited work from the best early-career researchers working within the scope of J. Phys. D. This project is part of the Journal of Physics series’ 50th anniversary celebrations in 2017. Fabien Sorin

THE DOMAINS FOR THE MULTI-CRITERIA DECISIONS ABOUT E-LEARNING SYSTEMS

Directory of Open Access Journals (Sweden)

Murat Pasa UYSAL

2012-04-01

Full Text Available Developments in computer and information technologies continue to give opportunities for designing advanced E-learning systems while entailing objective and technical evaluation methodologies. Design and development of E-learning systems require time-consuming and labor-intensive processes; therefore any decision about these systems and their analysis needs systematic and structured guidance to lead to better decisions. Multi-Criteria Decision Analysis (MCDA techniques are applicable in instructional technology-related research areas as well as in other academic disciplines. In this study, a conceptual domain model and a decision activity framework is proposed for E-learning systems. Instructional, technological, and administrative decision domains are included in this model. Finally, an illustrative example is given to show that AHP is an effective MCDA method for E-learning-related decisions.

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.

Contribution of domain wall networks to the CMB power spectrum

International Nuclear Information System (INIS)

Lazanu, A.; Martins, C.J.A.P.; Shellard, E.P.S.

2015-01-01

We use three domain wall simulations from the radiation era to the late-time dark energy domination era based on the PRS algorithm to calculate the energy–momentum tensor components of domain wall networks in an expanding universe. Unequal time correlators in the radiation, matter and cosmological constant epochs are calculated using the scaling regime of each of the simulations. The CMB power spectrum of a network of domain walls is determined. The first ever quantitative constraint for the domain wall surface tension is obtained using a Markov chain Monte Carlo method; an energy scale of domain walls of 0.93 MeV, which is close but below the Zel'dovich bound, is determined

Contribution of domain wall networks to the CMB power spectrum

Energy Technology Data Exchange (ETDEWEB)

Lazanu, A., E-mail: A.Lazanu@damtp.cam.ac.uk [Centre for Theoretical Cosmology, Department of Applied Mathematics and Theoretical Physics, Wilberforce Road, Cambridge CB3 0WA (United Kingdom); Martins, C.J.A.P., E-mail: Carlos.Martins@astro.up.pt [Centro de Astrofísica, Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Instituto de Astrofísica e Ciências do Espaço, CAUP, Rua das Estrelas, 4150-762 Porto (Portugal); Shellard, E.P.S., E-mail: E.P.S.Shellard@damtp.cam.ac.uk [Centre for Theoretical Cosmology, Department of Applied Mathematics and Theoretical Physics, Wilberforce Road, Cambridge CB3 0WA (United Kingdom)

2015-07-30

We use three domain wall simulations from the radiation era to the late-time dark energy domination era based on the PRS algorithm to calculate the energy–momentum tensor components of domain wall networks in an expanding universe. Unequal time correlators in the radiation, matter and cosmological constant epochs are calculated using the scaling regime of each of the simulations. The CMB power spectrum of a network of domain walls is determined. The first ever quantitative constraint for the domain wall surface tension is obtained using a Markov chain Monte Carlo method; an energy scale of domain walls of 0.93 MeV, which is close but below the Zel'dovich bound, is determined.

Contribution of domain wall networks to the CMB power spectrum

Directory of Open Access Journals (Sweden)

A. Lazanu

2015-07-01

Full Text Available We use three domain wall simulations from the radiation era to the late-time dark energy domination era based on the PRS algorithm to calculate the energy–momentum tensor components of domain wall networks in an expanding universe. Unequal time correlators in the radiation, matter and cosmological constant epochs are calculated using the scaling regime of each of the simulations. The CMB power spectrum of a network of domain walls is determined. The first ever quantitative constraint for the domain wall surface tension is obtained using a Markov chain Monte Carlo method; an energy scale of domain walls of 0.93 MeV, which is close but below the Zel'dovich bound, is determined.

Multi-target drugs: the trend of drug research and development.

Science.gov (United States)

Lu, Jin-Jian; Pan, Wei; Hu, Yuan-Jia; Wang, Yi-Tao

2012-01-01

Summarizing the status of drugs in the market and examining the trend of drug research and development is important in drug discovery. In this study, we compared the drug targets and the market sales of the new molecular entities approved by the U.S. Food and Drug Administration from January 2000 to December 2009. Two networks, namely, the target-target and drug-drug networks, have been set up using the network analysis tools. The multi-target drugs have much more potential, as shown by the network visualization and the market trends. We discussed the possible reasons and proposed the rational strategies for drug research and development in the future.

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.

A domain-decomposed multi-model plasma simulation of collisionless magnetic reconnection

Science.gov (United States)

Datta, I. A. M.; Shumlak, U.; Ho, A.; Miller, S. T.

2017-10-01

Collisionless magnetic reconnection is a process relevant to many areas of plasma physics in which energy stored in magnetic fields within highly conductive plasmas is rapidly converted into kinetic and thermal energy. Both in natural phenomena such as solar flares and terrestrial aurora as well as in magnetic confinement fusion experiments, the reconnection process is observed on timescales much shorter than those predicted by a resistive MHD model. As a result, this topic is an active area of research in which plasma models with varying fidelity have been tested in order to understand the proper physics explaining the reconnection process. In this research, a hybrid multi-model simulation employing the Hall-MHD and two-fluid plasma models on a decomposed domain is used to study this problem. The simulation is set up using the WARPXM code developed at the University of Washington, which uses a discontinuous Galerkin Runge-Kutta finite element algorithm and implements boundary conditions between models in the domain to couple their variable sets. The goal of the current work is to determine the parameter regimes most appropriate for each model to maintain sufficient physical fidelity over the whole domain while minimizing computational expense. This work is supported by a Grant from US AFOSR.

Automated road network extraction from high spatial resolution multi-spectral imagery

Science.gov (United States)

Zhang, Qiaoping

For the last three decades, the Geomatics Engineering and Computer Science communities have considered automated road network extraction from remotely-sensed imagery to be a challenging and important research topic. The main objective of this research is to investigate the theory and methodology of automated feature extraction for image-based road database creation, refinement or updating, and to develop a series of algorithms for road network extraction from high resolution multi-spectral imagery. The proposed framework for road network extraction from multi-spectral imagery begins with an image segmentation using the k-means algorithm. This step mainly concerns the exploitation of the spectral information for feature extraction. The road cluster is automatically identified using a fuzzy classifier based on a set of predefined road surface membership functions. These membership functions are established based on the general spectral signature of road pavement materials and the corresponding normalized digital numbers on each multi-spectral band. Shape descriptors of the Angular Texture Signature are defined and used to reduce the misclassifications between roads and other spectrally similar objects (e.g., crop fields, parking lots, and buildings). An iterative and localized Radon transform is developed for the extraction of road centerlines from the classified images. The purpose of the transform is to accurately and completely detect the road centerlines. It is able to find short, long, and even curvilinear lines. The input image is partitioned into a set of subset images called road component images. An iterative Radon transform is locally applied to each road component image. At each iteration, road centerline segments are detected based on an accurate estimation of the line parameters and line widths. Three localization approaches are implemented and compared using qualitative and quantitative methods. Finally, the road centerline segments are grouped into a

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.

A multi-domain spectral method for time-fractional differential equations

Science.gov (United States)

Chen, Feng; Xu, Qinwu; Hesthaven, Jan S.

2015-07-01

This paper proposes an approach for high-order time integration within a multi-domain setting for time-fractional differential equations. Since the kernel is singular or nearly singular, two main difficulties arise after the domain decomposition: how to properly account for the history/memory part and how to perform the integration accurately. To address these issues, we propose a novel hybrid approach for the numerical integration based on the combination of three-term-recurrence relations of Jacobi polynomials and high-order Gauss quadrature. The different approximations used in the hybrid approach are justified theoretically and through numerical examples. Based on this, we propose a new multi-domain spectral method for high-order accurate time integrations and study its stability properties by identifying the method as a generalized linear method. Numerical experiments confirm hp-convergence for both time-fractional differential equations and time-fractional partial differential equations.

Energy-Aware Routing in Multiple Domains Software-Defined Networks

Directory of Open Access Journals (Sweden)

Adriana FERNÁNDEZ-FERNÁNDEZ

2016-12-01

Full Text Available The growing energy consumption of communication networks has attracted the attention of the networking researchers in the last decade. In this context, the new architecture of Software-Defined Networks (SDN allows a flexible programmability, suitable for the power-consumption optimization problem. In this paper we address the issue of designing a novel distributed routing algorithm that optimizes the power consumption in large scale SDN with multiple domains. The solution proposed, called DEAR (Distributed Energy-Aware Routing, tackles the problem of minimizing the number of links that can be used to satisfy a given data traffic demand under performance constraints such as control traffic delay and link utilization. To this end, we present a complete formulation of the optimization problem that considers routing requirements for control and data plane communications. Simulation results confirm that the proposed solution enables the achievement of significant energy savings.

Multi-Scale Residual Convolutional Neural Network for Haze Removal of Remote Sensing Images

Directory of Open Access Journals (Sweden)

Hou Jiang

2018-06-01

Full Text Available Haze removal is a pre-processing step that operates on at-sensor radiance data prior to the physically based image correction step to enhance hazy imagery visually. Most current haze removal methods focus on point-to-point operations and utilize information in the spectral domain, without taking consideration of the multi-scale spatial information of haze. In this paper, we propose a multi-scale residual convolutional neural network (MRCNN for haze removal of remote sensing images. MRCNN utilizes 3D convolutional kernels to extract spatial–spectral correlation information and abstract features from surrounding neighborhoods for haze transmission estimation. It takes advantage of dilated convolution to aggregate multi-scale contextual information for the purpose of improving its prediction accuracy. Meanwhile, residual learning is utilized to avoid the loss of weak information while deepening the network. Our experiments indicate that MRCNN performs accurately, achieving an extremely low validation error and testing error. The haze removal results of several scenes of Landsat 8 Operational Land Imager (OLI data show that the visibility of the dehazed images is significantly improved, and the color of recovered surface is consistent with the actual scene. Quantitative analysis proves that the dehazed results of MRCNN are superior to the traditional methods and other networks. Additionally, a comparison to haze-free data illustrates the spectral consistency after haze removal and reveals the changes in the vegetation index.

Transform- and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging.

Science.gov (United States)

Jiang, Shaowei; Liao, Jun; Bian, Zichao; Guo, Kaikai; Zhang, Yongbing; Zheng, Guoan

2018-04-01

A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination. We acquire ~130,000 images with different defocus distances as the training data set. Different defocus distances lead to different spatial features of the captured images. However, solely relying on the spatial information leads to a relatively bad performance of the autofocusing process. It is better to extract defocus features from transform domains of the acquired image. For incoherent illumination, the Fourier cutoff frequency is directly related to the defocus distance. Similarly, autocorrelation peaks are directly related to the defocus distance for two-plane-wave illumination. In our implementation, we use the spatial image, the Fourier spectrum, the autocorrelation of the spatial image, and combinations thereof as the inputs for the CNNs. We show that the information from the transform domains can improve the performance and robustness of the autofocusing process. The resulting focusing error is ~0.5 µm, which is within the 0.8-µm depth-of-field range. The reported approach requires little hardware modification for conventional WSI systems and the images can be captured on the fly without focus map surveying. It may find applications in WSI and time-lapse microscopy. The transform- and multi-domain approaches may also provide new insights for developing microscopy-related deep-learning networks. We have made

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.

Stable multi-domain spectral penalty methods for fractional partial differential equations

Science.gov (United States)

Xu, Qinwu; Hesthaven, Jan S.

2014-01-01

We propose stable multi-domain spectral penalty methods suitable for solving fractional partial differential equations with fractional derivatives of any order. First, a high order discretization is proposed to approximate fractional derivatives of any order on any given grids based on orthogonal polynomials. The approximation order is analyzed and verified through numerical examples. Based on the discrete fractional derivative, we introduce stable multi-domain spectral penalty methods for solving fractional advection and diffusion equations. The equations are discretized in each sub-domain separately and the global schemes are obtained by weakly imposed boundary and interface conditions through a penalty term. Stability of the schemes are analyzed and numerical examples based on both uniform and nonuniform grids are considered to highlight the flexibility and high accuracy of the proposed schemes.

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.

Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

Science.gov (United States)

Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

2008-10-01

Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

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.).

Flexible Transport Network Expansion via Open WDM Interfaces

DEFF Research Database (Denmark)

Fagertun, Anna Manolova; Skjoldstrup, Bjarke

2013-01-01

This paper presents a successful test-bed implementation of a multi-vendor transport network interconnection via open WDM interfaces. The concept of applying Alien Wavelengths (AWs) for network expansion was successfully illustrated via deployment of multi-domain/multi-vendor end-to-end OTN servi...

Enhancing network performance under single link failure with AS-disjoint BGP extension

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Romeral, S.; Ruepp, Sarah Renée

2009-01-01

In this paper we propose an enhancement of the BGP protocol for obtaining AS-disjoint paths in GMPLS multi-domain networks. We evaluate the benefits of having AS-disjoint paths under single inter-domain link failure for two main applications: routing of future connection requests during routing...... protocol re-convergence and applying multi-domain restoration as survivability mechanism in case of a single link failure. The proposed BGP modification is a simple and effective solution for disjoint path selection in connection-oriented multi-domain networks. Our results show that applying the proper...

Theoretical multi-tier trust framework for the geospatial domain

CSIR Research Space (South Africa)

Umuhoza, D

2010-01-01

Full Text Available chain or workflow from data acquisition to knowledge discovery. The author’s present work in progress of a theoretical multi-tier trust framework for processing chain from data acquisition to knowledge discovery in geospatial domain. Holistic trust...

Spectrum-efficient multi-channel design for coexisting IEEE 802.15.4 networks: A stochastic geometry approach

KAUST Repository

Elsawy, Hesham

2014-07-01

For networks with random topologies (e.g., wireless ad-hoc and sensor networks) and dynamically varying channel gains, choosing the long term operating parameters that optimize the network performance metrics is very challenging. In this paper, we use stochastic geometry analysis to develop a novel framework to design spectrum-efficient multi-channel random wireless networks based on the IEEE 802.15.4 standard. The proposed framework maximizes both spatial and time domain frequency utilization under channel gain uncertainties to minimize the number of frequency channels required to accommodate a certain population of coexisting IEEE 802.15.4 networks. The performance metrics are the outage probability and the self admission failure probability. We relax the single channel assumption that has been used traditionally in the stochastic geometry analysis. We show that the intensity of the admitted networks does not increase linearly with the number of channels and the rate of increase of the intensity of the admitted networks decreases with the number of channels. By using graph theory, we obtain the minimum required number of channels to accommodate a certain intensity of coexisting networks under a self admission failure probability constraint. To this end, we design a superframe structure for the coexisting IEEE 802.15.4 networks and a method for time-domain interference alignment. © 2002-2012 IEEE.

Design of Networks-on-Chip for Real-Time Multi-Processor Systems-on-Chip

DEFF Research Database (Denmark)

Sparsø, Jens

2012-01-01

This paper addresses the design of networks-on-chips for use in multi-processor systems-on-chips - the hardware platforms used in embedded systems. These platforms typically have to guarantee real-time properties, and as the network is a shared resource, it has to provide service guarantees...... (bandwidth and/or latency) to different communication flows. The paper reviews some past work in this field and the lessons learned, and the paper discusses ongoing research conducted as part of the project "Time-predictable Multi-Core Architecture for Embedded Systems" (T-CREST), supported by the European...

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...

Multi-Cluster Network on a Chip Reconfigurable Radiation Hardened Radio, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The objective of the Phase-I research is to architect, model and simulate a multi-cluster Network on a Chip (NoC) reconfigurable Radio in SystemC RTL, with...

Multi-domain training in healthy old age: Hotel Plastisse as an iPad-based serious game to systematically compare multi-domain and single-domain training

Science.gov (United States)

Binder, Julia C.; Zöllig, Jacqueline; Eschen, Anne; Mérillat, Susan; Röcke, Christina; Schoch, Sarah F.; Jäncke, Lutz; Martin, Mike

2015-01-01

Finding effective training interventions for declining cognitive abilities in healthy aging is of great relevance, especially in view of the demographic development. Since it is assumed that transfer from the trained to untrained domains is more likely to occur when training conditions and transfer measures share a common underlying process, multi-domain training of several cognitive functions should increase the likelihood of such an overlap. In the first part, we give an overview of the literature showing that cognitive training using complex tasks, such as video games, leisure activities, or practicing a series of cognitive tasks, has shown promising results regarding transfer to a number of cognitive functions. These studies, however, do not allow direct inference about the underlying functions targeted by these training regimes. Custom-designed serious games allow to design training regimes according to specific cognitive functions and a target population's need. In the second part, we introduce the serious game Hotel Plastisse as an iPad-based training tool for older adults that allows the comparison of the simultaneous training of spatial navigation, visuomotor function, and inhibition to the training of each of these functions separately. Hotel Plastisse not only defines the cognitive functions of the multi-domain training clearly, but also implements training in an interesting learning environment including adaptive difficulty and feedback. We propose this novel training tool with the goal of furthering our understanding of how training regimes should be designed in order to affect cognitive functioning of older adults most broadly. PMID:26257643

Multi-domain training in healthy old age: Hotel Plastisse as an iPad-based serious game to systematically compare multi-domain and single-domain training.

Science.gov (United States)

Binder, Julia C; Zöllig, Jacqueline; Eschen, Anne; Mérillat, Susan; Röcke, Christina; Schoch, Sarah F; Jäncke, Lutz; Martin, Mike

2015-01-01

Finding effective training interventions for declining cognitive abilities in healthy aging is of great relevance, especially in view of the demographic development. Since it is assumed that transfer from the trained to untrained domains is more likely to occur when training conditions and transfer measures share a common underlying process, multi-domain training of several cognitive functions should increase the likelihood of such an overlap. In the first part, we give an overview of the literature showing that cognitive training using complex tasks, such as video games, leisure activities, or practicing a series of cognitive tasks, has shown promising results regarding transfer to a number of cognitive functions. These studies, however, do not allow direct inference about the underlying functions targeted by these training regimes. Custom-designed serious games allow to design training regimes according to specific cognitive functions and a target population's need. In the second part, we introduce the serious game Hotel Plastisse as an iPad-based training tool for older adults that allows the comparison of the simultaneous training of spatial navigation, visuomotor function, and inhibition to the training of each of these functions separately. Hotel Plastisse not only defines the cognitive functions of the multi-domain training clearly, but also implements training in an interesting learning environment including adaptive difficulty and feedback. We propose this novel training tool with the goal of furthering our understanding of how training regimes should be designed in order to affect cognitive functioning of older adults most broadly.

Research on the model of home networking

Science.gov (United States)

Yun, Xiang; Feng, Xiancheng

2007-11-01

It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

A fuzzy multi-objective optimization model for sustainable reverse logistics network design

DEFF Research Database (Denmark)

Govindan, Kannan; Paam, Parichehr; Abtahi, Amir Reza

2016-01-01

Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider...... a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order...... these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design...

A Cross-Layer Routing Design for Multi-Interface Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Tzu-Chieh Tsai

2009-01-01

Full Text Available In recent years, Wireless Mesh Networks (WMNs technologies have received significant attentions. WMNs not only accede to the advantages of ad hoc networks but also provide hierarchical multi-interface architecture. Transmission power control and routing path selections are critical issues in the past researches of multihop networks. Variable transmission power levels lead to different network connectivity and interference. Further, routing path selections among different radio interfaces will also produce different intra-/interflow interference. These features tightly affect the network performance. Most of the related works on the routing protocol design do not consider transmission power control and multi-interface environment simultaneously. In this paper, we proposed a cross-layer routing protocol called M2iRi2 which coordinates transmission power control and intra-/interflow interference considerations as routing metrics. Each radio interface calculates the potential tolerable-added transmission interference in the physical layer. When the route discovery starts, the M2iRi2 will adopt the appropriate power level to evaluate each interface quality along paths. The simulation results demonstrate that our design can enhance both network throughput and end-to-end delay.

Delay Bounded Multi-Source Multicast in Software-Defined Networking

Directory of Open Access Journals (Sweden)

Thabo Semong

2018-01-01

Full Text Available Software-Defined Networking (SDN is the next generation network architecture with exciting application prospects. The control function in SDN is decoupled from the data forwarding plane, hence it provides a new centralized architecture with flexible network resource management. Although SDN is attracting much attention from both industry and research, its advantage over the traditional networks has not been fully utilized. Multicast is designed to deliver content to multiple destinations. The current traffic engineering in SDN focuses mainly on unicast, however, multicast can effectively reduce network resource consumption by serving multiple clients. This paper studies a novel delay-bounded multi-source multicast SDN problem, in which among the set of potential sources, we select a source to build the multicast-tree, under the constraint that the transmission delay for every destination is bounded. This problem is more difficult than the traditional Steiner minimum tree (SMT problem, since it needs to find a source from the set of all potential sources. We model the problem as a mixed-integer linear programming (MILP and prove its NP-Hardness. To solve the problem, a delay bounded multi-source (DBMS scheme is proposed, which includes a DBMS algorithm to build a minimum delay cost DBMS-Forest. Through a MATLAB experiment, we demonstrate that DBMS is significantly more efficient and outperforms other existing algorithms in the literature.

Research of Ad Hoc Networks Access Algorithm

Science.gov (United States)

Xiang, Ma

With the continuous development of mobile communication technology, Ad Hoc access network has become a hot research, Ad Hoc access network nodes can be used to expand capacity of multi-hop communication range of mobile communication system, even business adjacent to the community, improve edge data rates. When the ad hoc network is the access network of the internet, the gateway discovery protocol is very important to choose the most appropriate gateway to guarantee the connectivity between ad hoc network and IP based fixed networks. The paper proposes a QoS gateway discovery protocol which uses the time delay and stable route to the gateway selection conditions. And according to the gateway discovery protocol, it also proposes a fast handover scheme which can decrease the handover time and improve the handover efficiency.

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

The Gigantium Smart City Living Lab: A Multi-Arena LoRa-based Testbed

DEFF Research Database (Denmark)

Rodriguez Larrad, Ignacio; Lauridsen, Mads; Vasluianu, Gabriel

2018-01-01

The Wireless Communications Networks Section, from the Department of Electronic Systems at Aalborg University, Denmark, has successfully deployed, in collaboration with a number of Danish local industrial partners, a LoRa network in the Gigantium multi-arena center. The initial aim of this network......, which provide macroscopic diversity to the wireless system, ensuring a correct level of reliability. The setup is already operational, but still open for optimization. The deployed network should also serve as a tested for research in the wireless and indoor climate domains....

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.

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...

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.

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

Hybrid Multi-Layer Network Control for Emerging Cyber-Infrastructures

Energy Technology Data Exchange (ETDEWEB)

Summerhill, Richard [Internet2, Washington, DC (United States); Lehman, Tom [Univ. of Southern California, Los Angeles, CA (United States). Information Sciences Inst. (ISI); Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical & Computer Engineering; Boyd, Eric [Univ. Corporation for Advanced Internet Development (UCAID), Washington, DC (United States)

2009-08-14

There were four basic task areas identified for the Hybrid-MLN project. They are: Multi-Layer, Multi-Domain, Control Plane Architecture and Implementation; Heterogeneous DataPlane Testing; Simulation; Project Publications, Reports, and Presentations.

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

Multi-domain training in healthy old age – Hotel Plastisse as an iPad-based serious game to systematically compare multi-domain and single-domain training

Directory of Open Access Journals (Sweden)

Julia Claudia Binder

2015-07-01

Full Text Available Finding effective training interventions for declining cognitive abilities in healthy aging is of great relevance, especially in view of the demographic development. Since it is assumed that transfer from the trained to untrained domains is more likely to occur when training conditions and transfer measures share a common underlying process, multi-domain training of several cognitive functions should increase the likelihood of such an overlap. In the first part, we give an overview of the literature showing that cognitive training using complex tasks such as video games, leisure activities, or practicing a series of cognitive tasks has shown promising results regarding transfer to a number of cognitive functions. These studies, however, do not allow direct inference about the underlying functions targeted by these training regimes. Custom-designed serious games allow to design training regimes according to specific cognitive functions and a target population’s need. In the second part, we introduce the serious game Hotel Plastisse as an iPad-based training tool for older adults that allows the comparison of the simultaneous training of spatial navigation, visuomotor function and inhibition to the training of each of these functions separately. Hotel Plastisse not only defines the cognitive functions of the multi-domain training clearly, but also implements training in an interesting learning environment including adaptive difficulty and feedback. We propose this novel training tool with the goal of furthering our understanding of how training regimes should be designed in order to affect cognitive functioning of older adults most broadly.

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...

Bio-inspired energy and channel management in distributed wireless multi-radio networks

CSIR Research Space (South Africa)

Olwal, TO

2014-06-01

Full Text Available In the recent past, research in the next generation wireless heterogeneous broadband networks has favoured the design of multi-radio interface over the single radio interface architectures in order to support desirable features such as a self...

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...

Frequency-domain and time-domain methods for feedback nonlinear systems and applications to chaos control

International Nuclear Information System (INIS)

Duan Zhisheng; Wang Jinzhi; Yang Ying; Huang Lin

2009-01-01

This paper surveys frequency-domain and time-domain methods for feedback nonlinear systems and their possible applications to chaos control, coupled systems and complex dynamical networks. The absolute stability of Lur'e systems with single equilibrium and global properties of a class of pendulum-like systems with multi-equilibria are discussed. Time-domain and frequency-domain criteria for the convergence of solutions are presented. Some latest results on analysis and control of nonlinear systems with multiple equilibria and applications to chaos control are reviewed. Finally, new chaotic oscillating phenomena are shown in a pendulum-like system and a new nonlinear system with an attraction/repulsion function.

Integrated topology optimisation of multi-energy networks

NARCIS (Netherlands)

Mazairac, L.A.J.; Salenbien, R.; Vanhoudt, D.; Desmedt, J.; Vries, de B.

2015-01-01

Multi-carrier hybrid energy distribution net- works provide flexibility in case of network malfunctions, energy shortages and price fluctuations through energy conversion and storage. Therefore hybrid networks can cope with large-scale integration of distributed and intermittent renewable energy

Multi-domain/multi-method numerical approach for neutron transport equation; Couplage de methodes et decomposition de domaine pour la resolution de l'equation du transport des neutrons

Energy Technology Data Exchange (ETDEWEB)

Girardi, E

2004-12-15

A new methodology for the solution of the neutron transport equation, based on domain decomposition has been developed. This approach allows us to employ different numerical methods together for a whole core calculation: a variational nodal method, a discrete ordinate nodal method and a method of characteristics. These new developments authorize the use of independent spatial and angular expansion, non-conformal Cartesian and unstructured meshes for each sub-domain, introducing a flexibility of modeling which is not allowed in today available codes. The effectiveness of our multi-domain/multi-method approach has been tested on several configurations. Among them, one particular application: the benchmark model of the Phebus experimental facility at Cea-Cadarache, shows why this new methodology is relevant to problems with strong local heterogeneities. This comparison has showed that the decomposition method brings more accuracy all along with an important reduction of the computer time.

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.

Biological and Environmental Research Network Requirements

Energy Technology Data Exchange (ETDEWEB)

Balaji, V. [Princeton Univ., NJ (United States). Earth Science Grid Federation (ESGF); Boden, Tom [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Cowley, Dave [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Dart, Eli [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Dattoria, Vince [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Desai, Narayan [Argonne National Lab. (ANL), Argonne, IL (United States); Egan, Rob [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Foster, Ian [Argonne National Lab. (ANL), Argonne, IL (United States); Goldstone, Robin [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Gregurick, Susan [U.S. Dept. of Energy, Washington, DC (United States). Biological Systems Science Division; Houghton, John [U.S. Dept. of Energy, Washington, DC (United States). Biological and Environmental Research (BER) Program; Izaurralde, Cesar [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Johnston, Bill [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Joseph, Renu [U.S. Dept. of Energy, Washington, DC (United States). Climate and Environmental Sciences Division; Kleese-van Dam, Kerstin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lipton, Mary [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Monga, Inder [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Pritchard, Matt [British Atmospheric Data Centre (BADC), Oxon (United Kingdom); Rotman, Lauren [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Strand, Gary [National Center for Atmospheric Research (NCAR), Boulder, CO (United States); Stuart, Cory [Argonne National Lab. (ANL), Argonne, IL (United States); Tatusova, Tatiana [National Inst. of Health (NIH), Bethesda, MD (United States); Tierney, Brian [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). ESNet; Thomas, Brian [Univ. of California, Berkeley, CA (United States); Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Zurawski, Jason [Internet2, Washington, DC (United States)

2013-09-01

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.

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

Multi-focus image fusion with the all convolutional neural network

Science.gov (United States)

Du, Chao-ben; Gao, She-sheng

2018-01-01

A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network (CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN (ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.

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

Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner

OpenAIRE

Chen, Tseng-Hung; Liao, Yuan-Hong; Chuang, Ching-Yao; Hsu, Wan-Ting; Fu, Jianlong; Sun, Min

2017-01-01

Impressive image captioning results are achieved in domains with plenty of training image and sentence pairs (e.g., MSCOCO). However, transferring to a target domain with significant domain shifts but no paired training data (referred to as cross-domain image captioning) remains largely unexplored. We propose a novel adversarial training procedure to leverage unpaired data in the target domain. Two critic networks are introduced to guide the captioner, namely domain critic and multi-modal cri...

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.

The Mind Research Network - Mental Illness Neuroscience Discovery Grant

Energy Technology Data Exchange (ETDEWEB)

Roberts, J. [The Mind Research Network, Albuquerque, NM (United States); Calhoun, V. [The Mind Research Network, Albuquerque, NM (United States)

2013-12-17

The scientific and technological programs of the Mind Research Network (MRN), reflect DOE missions in basic science and associated instrumentation, computational modeling, and experimental techniques. MRN's technical goals over the course of this project have been to develop and apply integrated, multi-modality functional imaging techniques derived from a decade of DOE-support research and technology development.

Multi-level deep supervised networks for retinal vessel segmentation.

Science.gov (United States)

Mo, Juan; Zhang, Lei

2017-12-01

Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

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.

Community-Based Research Networks: Development and Lessons Learned in an Emerging Field.

Science.gov (United States)

Stoecker, Randy; Ambler, Susan H.; Cutforth, Nick; Donohue, Patrick; Dougherty, Dan; Marullo, Sam; Nelson, Kris S.; Stutts, Nancy B.

2003-01-01

Compares seven multi-institutional community-based research networks in Appalachia; Colorado; District of Columbia; Minneapolis-St. Paul; Philadelphia; Richmond, Virginia; and Trenton, New Jersey. After reviewing the histories of the networks, conducts a comparative SWOT analysis, showing their common and unique strengths, weaknesses,…

Conformational dynamics and ligand binding in the multi-domain protein PDC109.

Directory of Open Access Journals (Sweden)

Hyun Jin Kim

2010-02-01

Full Text Available PDC109 is a modular multi-domain protein with two fibronectin type II (Fn2 repeats joined by a linker. It plays a major role in bull sperm binding to the oviductal epithelium through its interactions with phosphorylcholines (PhCs, a head group of sperm cell membrane lipids. The crystal structure of the PDC109-PhC complex shows that each PhC binds to the corresponding Fn2 domain, while the two domains are on the same face of the protein. Long timescale explicit solvent molecular dynamics (MD simulations of PDC109, in the presence and absence of PhC, suggest that PhC binding strongly correlates with the relative orientation of choline-phospholipid binding sites of the two Fn2 domains; unless the two domains tightly bind PhCs, they tend to change their relative orientation by deforming the flexible linker. The effective PDC109-PhC association constant of 28 M(-1, estimated from their potential of mean force is consistent with the experimental result. Principal component analysis of the long timescale MD simulations was compared to the significantly less expensive normal mode analysis of minimized structures. The comparison indicates that difference between relative domain motions of PDC109 with bound and unbound PhC is captured by the first principal component in the principal component analysis as well as the three lowest normal modes in the normal mode analysis. The present study illustrates the use of detailed MD simulations to clarify the energetics of specific ligand-domain interactions revealed by a static crystallographic model, as well as their influence on relative domain motions in a multi-domain protein.

Magnetoresistance of microstructured permalloy ellipses having multi-domain configurations

International Nuclear Information System (INIS)

Kuo, C.Y.; Chung, W.S.; Wu, J.C.; Horng, Lance; Wei, Z.-H.; Lai, M.-F.; Chang, C.-R.

2007-01-01

Mirostructured permalloy ellipses having purposely designed multi-domain configurations were investigated. The samples were fabricated using e-beam lithography through a lift-off process. The magnetoresistance measurements were carried out with a constant dc sensing current under the external magnetic field applied along the short axis. The magnetoresistance curves manifest characteristic features in accordance with the specific domain configurations. Step-like/kink features were observed on the ellipses with cross-tie wall/two-vortex configuration and step-like plus kink magnetorsistance curve was found on the ellipse with cross-tie wall combining with two-vortex structure. A magnetic force microscopy and a micromagnetic simulation were employed to support these results

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...

Domain wall network as QCD vacuum and the chromomagnetic trap formation under extreme conditions

International Nuclear Information System (INIS)

Nedelko, Sergei N.; Voronin, Vladimir E.

2015-01-01

The ensemble of Euclidean gluon field configurations represented by the domain wall network is considered. A single domain wall is given by the sine-Gordon kink for the angle between chromomagnetic and chromoelectric components of the gauge field. The domain wall separates the regions with Abelian self-dual and anti-self-dual fields. The network of the domain wall defects is introduced as a combination of multiplicative and additive superpositions of kinks. The character of the spectrum and eigenmodes of color-charged fluctuations in the presence of the domain wall network is discussed. Conditions for the formation of a stable thick domain wall junction (the chromomagnetic trap) during heavy-ion collisions are discussed, and the spectrum of color-charged quasi-particles inside the trap is evaluated. An important observation is the existence of the critical size L c of a single trap stable against gluon tachyonic modes. The size L c is related to the value of gluon condensate left angle g 2 F 2 right angle. The growth of large lumps of merged chromomagnetic traps and the concept of the confinement-deconfinement transition in terms of the ensemble of domain wall networks are outlined. (orig.)

Principles and Policies for International Coordination of Research Data Networks

Science.gov (United States)

Parsons, M. A.; Mokrane, M.; Sorvari, S.; Treloar, A.; Smith, C.

2017-12-01

International data networks enable the sharing of data within and between scientific disciplines and countries and thus provide the foundation for Open Science. Developing effective and sustainable international research data networks is critical for progress in many areas of research and for science to address complex global societal challenges. However, the development and maintenance of effective networks is not always easy, particularly in a context where public resources for science are limited and international cooperation is not a priority for many countries. The global landscape for data sharing in science is complex; many international data networks already exist and have highly variable structures. Some are linked to large intergovernmental research infrastructures, have highly developed centralized services and deal mainly with the data needs of single disciplines. Some are highly distributed, have much less rigid governance structures and provide access to data from many different domains. Most are somewhere between these two extremes and they cover different geographic regions, from regional to global. All provide a mix of data and associated data services which meets the needs of the research community to various extents and this provision depends on a mix of hardware, software, standards and protocols and human skills. These come together, working across national boundaries, in technical and social networks. In all of this, what makes a network function effectively or not is unclear. This means that there is also no simple answer to what can usefully be done at the policy level to promote the development of effective and sustainable data networks. Hence the rational for the present project - to study a variety of currently successful networks, explore the challenges that they are facing and the lessons that can be learned from confronting these challenges, and, where applicable, to translate this analysis into potential policy actions. Detailed

3D multi-view convolutional neural networks for lung nodule classification

Science.gov (United States)

Kang, Guixia; Hou, Beibei; Zhang, Ningbo

2017-01-01

The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In this paper, we explore the classification of lung nodules using the 3D multi-view convolutional neural networks (MV-CNN) with both chain architecture and directed acyclic graph architecture, including 3D Inception and 3D Inception-ResNet. All networks employ the multi-view-one-network strategy. We conduct a binary classification (benign and malignant) and a ternary classification (benign, primary malignant and metastatic malignant) on Computed Tomography (CT) images from Lung Image Database Consortium and Image Database Resource Initiative database (LIDC-IDRI). All results are obtained via 10-fold cross validation. As regards the MV-CNN with chain architecture, results show that the performance of 3D MV-CNN surpasses that of 2D MV-CNN by a significant margin. Finally, a 3D Inception network achieved an error rate of 4.59% for the binary classification and 7.70% for the ternary classification, both of which represent superior results for the corresponding task. We compare the multi-view-one-network strategy with the one-view-one-network strategy. The results reveal that the multi-view-one-network strategy can achieve a lower error rate than the one-view-one-network strategy. PMID:29145492

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

Directory of Open Access Journals (Sweden)

Junha Shin

Full Text Available Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co

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

Conceptualizing the e-Learning Assessment Domain using an Ontology Network

Directory of Open Access Journals (Sweden)

Lucía Romero

2012-09-01

Full Text Available During the last year, approaches that use ontologies, the backbone of the Semantic Web technologies, for different purposes in the assessment domain of e-Learning have emerged. One of these purposes is the use of ontologies as a mean of providing a structure to guide the automated design of assessments. The most of the approaches that deal with this problem have proposed individual ontologies that model only a part of the assessment domain. The main contribution of this paper is an ontology network, called AONet, that conceptualizes the e-assessment domain with the aim of supporting the semi-automatic generation of it. The main advantage of this network is that it is enriched with rules for considering not only technical aspects of an assessment but also pedagogic

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...

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.

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-scale computational model of three-dimensional hemodynamics within a deformable full-body arterial network

Energy Technology Data Exchange (ETDEWEB)

Xiao, Nan [Department of Bioengineering, Stanford University, Stanford, CA 94305 (United States); Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom); Humphrey, Jay D. [Department of Biomedical Engineering, Yale University, New Haven, CT 06520 (United States); Figueroa, C. Alberto, E-mail: alberto.figueroa@kcl.ac.uk [Department of Biomedical Engineering, King’s College London, London SE1 7EH (United Kingdom)

2013-07-01

In this article, we present a computational multi-scale model of fully three-dimensional and unsteady hemodynamics within the primary large arteries in the human. Computed tomography image data from two different patients were used to reconstruct a nearly complete network of the major arteries from head to foot. A linearized coupled-momentum method for fluid–structure-interaction was used to describe vessel wall deformability and a multi-domain method for outflow boundary condition specification was used to account for the distal circulation. We demonstrated that physiologically realistic results can be obtained from the model by comparing simulated quantities such as regional blood flow, pressure and flow waveforms, and pulse wave velocities to known values in the literature. We also simulated the impact of age-related arterial stiffening on wave propagation phenomena by progressively increasing the stiffness of the central arteries and found that the predicted effects on pressure amplification and pulse wave velocity are in agreement with findings in the clinical literature. This work demonstrates the feasibility of three-dimensional techniques for simulating hemodynamics in a full-body compliant arterial network.

Building an international network for a primary care research program: reflections on challenges and solutions in the set-up and delivery of a prospective observational study of acute cough in 13 European countries

Directory of Open Access Journals (Sweden)

Veen Robert ER

2011-07-01

Full Text Available Abstract Background Implementing a primary care clinical research study in several countries can make it possible to recruit sufficient patients in a short period of time that allows important clinical questions to be answered. Large multi-country studies in primary care are unusual and are typically associated with challenges requiring innovative solutions. We conducted a multi-country study and through this paper, we share reflections on the challenges we faced and some of the solutions we developed with a special focus on the study set up, structure and development of Primary Care Networks (PCNs. Method GRACE-01 was a multi-European country, investigator-driven prospective observational study implemented by 14 Primary Care Networks (PCNs within 13 European Countries. General Practitioners (GPs recruited consecutive patients with an acute cough. GPs completed a case report form (CRF and the patient completed a daily symptom diary. After study completion, the coordinating team discussed the phases of the study and identified challenges and solutions that they considered might be interesting and helpful to researchers setting up a comparable study. Results The main challenges fell within three domains as follows: i selecting, setting up and maintaining PCNs; ii designing local context-appropriate data collection tools and efficient data management systems; and iii gaining commitment and trust from all involved and maintaining enthusiasm. The main solutions for each domain were: i appointing key individuals (National Network Facilitator and Coordinator with clearly defined tasks, involving PCNs early in the development of study materials and procedures. ii rigorous back translations of all study materials and the use of information systems to closely monitor each PCNs progress; iii providing strong central leadership with high level commitment to the value of the study, frequent multi-method communication, establishing a coherent ethos

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...

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.

Regulatory Compliance in Multi-Tier Supplier Networks

Science.gov (United States)

Goossen, Emray R.; Buster, Duke A.

2014-01-01

Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses.

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.

Effects of multi-domain interventions in (prefrail elderly on frailty, functional, and cognitive status: a systematic review

Directory of Open Access Journals (Sweden)

Dedeyne L

2017-05-01

Full Text Available Lenore Dedeyne,1 Mieke Deschodt,2–4 Sabine Verschueren,5 Jos Tournoy,1,3 Evelien Gielen1,3 1Department of Clinical and Experimental Medicine, 2Department of Public Health and Primary Care, KU Leuven – University of Leuven, Leuven, Belgium; 3Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium; 4Department of Public Health, Institute of Nursing Science, University of Basel, Basel, Switzerland; 5Department of Rehabilitation Sciences, KU Leuven – University of Leuven, Heverlee, Belgium Background: Frailty is an aging syndrome caused by exceeding a threshold of decline across multiple organ systems leading to a decreased resistance to stressors. Treatment for frailty focuses on multi-domain interventions to target multiple affected functions in order to decrease the adverse outcomes of frailty. No systematic reviews on the effectiveness of multi-domain interventions exist in a well-defined frail population. Objectives: This systematic review aimed to determine the effect of multi-domain compared to mono-domain interventions on frailty status and score, cognition, muscle mass, strength and power, functional and social outcomes in (prefrail elderly (≥65 years. It included interventions targeting two or more domains (physical exercise, nutritional, pharmacological, psychological, or social interventions in participants defined as (prefrail by an operationalized frailty definition. Methods: The databases PubMed, EMBASE, CINAHL, PEDro, CENTRAL, and the Cochrane Central register of Controlled Trials were searched from inception until September 14, 2016. Additional articles were searched by citation search, author search, and reference lists of relevant articles. The protocol for this review was registered on PROSPERO (CRD42016032905. Results: Twelve studies were included, reporting a large diversity of interventions in terms of content, duration, and follow-up period. Overall, multi-domain interventions tended to be more

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.

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

Proteins containing the UBA domain are able to bind to multi-ubiquitin chains

DEFF Research Database (Denmark)

Wilkinson, C R; Seeger, M; Hartmann-Petersen, R

2001-01-01

The UBA domain is a motif found in a variety of proteins, some of which are associated with the ubiquitin-proteasome system. We describe the isolation of a fission-yeast gene, mud1+, which encodes a UBA domain containing protein that is able to bind multi-ubiquitin chains. We show that the UBA do...

Buffer sizing for multi-hop networks

KAUST Repository

Shihada, Basem; Jamshaid, Kamran

2014-01-01

domain according to a simple division or according to a cost function taking into account a distance of the communications link from the source and destination. The network may be monitored and the cumulative buffer size recalculated and redistributed

Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks.

Science.gov (United States)

Lin, Na; Chen, Hanning; Jing, Shikai; Liu, Fang; Liang, Xiaodan

2017-03-01

In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS 2 Os, which extend the single population particle swarm optimization (PSO) algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS 2 O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS 2 O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm's performance. Then PS 2 O is used for solving the radio frequency identification (RFID) network planning (RNP) problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.

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...

Analytical transmissibility based transfer path analysis for multi-energy-domain systems using four-pole parameter theory

Science.gov (United States)

Mashayekhi, Mohammad Jalali; Behdinan, Kamran

2017-10-01

The increasing demand to minimize undesired vibration and noise levels in several high-tech industries has generated a renewed interest in vibration transfer path analysis. Analyzing vibration transfer paths within a system is of crucial importance in designing an effective vibration isolation strategy. Most of the existing vibration transfer path analysis techniques are empirical which are suitable for diagnosis and troubleshooting purpose. The lack of an analytical transfer path analysis to be used in the design stage is the main motivation behind this research. In this paper an analytical transfer path analysis based on the four-pole theory is proposed for multi-energy-domain systems. Bond graph modeling technique which is an effective approach to model multi-energy-domain systems is used to develop the system model. In this paper an electro-mechanical system is used as a benchmark example to elucidate the effectiveness of the proposed technique. An algorithm to obtain the equivalent four-pole representation of a dynamical systems based on the corresponding bond graph model is also presented in this paper.

Sentiment classification technology based on Markov logic networks

Science.gov (United States)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

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.

Association between quality domains and health care spending across physician networks

Science.gov (United States)

Rahman, Farah; Guan, Jun; Glazier, Richard H.; Brown, Adalsteinn; Bierman, Arlene S.; Croxford, Ruth; Stukel, Therese A.

2018-01-01

One of the more fundamental health policy questions is the relationship between health care quality and spending. A better understanding of these relationships is needed to inform health systems interventions aimed at increasing quality and efficiency of care. We measured 65 validated quality indicators (QI) across Ontario physician networks. QIs were aggregated into domains representing six dimensions of care: screening and prevention, evidence-based medications, hospital-community transitions (7-day post-discharge visit with a primary care physician; 30-day post-discharge visit with a primary care physician and specialist), potentially avoidable hospitalizations and emergency department (ED) visits, potentially avoidable readmissions and unplanned returns to the ED, and poor cancer end of life care. Each domain rate was computed as a weighted average of QI rates, weighting by network population at risk. We also measured overall and sector-specific per capita healthcare network spending. We evaluated the associations between domain rates, and between domain rates and spending using weighted correlations, weighting by network population at risk, using an ecological design. All indicators were measured using Ontario health administrative databases. Large variations were seen in timely hospital-community transitions and potentially avoidable hospitalizations. Networks with timely hospital-community transitions had lower rates of avoidable admissions and readmissions (r = -0.89, -0.58, respectively). Higher physician spending, especially outpatient primary care spending, was associated with lower rates of avoidable hospitalizations (r = -0.83) and higher rates of timely hospital-community transitions (r = 0.81) and moderately associated with lower readmission rates (r = -0.46). Investment in effective primary care services may help reduce burden on the acute care sector and associated expenditures. PMID:29614131

Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling.

Science.gov (United States)

Hermans, Frans; Sartas, Murat; van Schagen, Boudy; van Asten, Piet; Schut, Marc

2017-01-01

Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their 'capacity to innovate' and contribute to the 'scaling of innovations'. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts.

Social network analysis of multi-stakeholder platforms in agricultural research for development: Opportunities and constraints for innovation and scaling.

Directory of Open Access Journals (Sweden)

Frans Hermans

Full Text Available Multi-stakeholder platforms (MSPs are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their 'capacity to innovate' and contribute to the 'scaling of innovations'. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC. In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts.

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.)

A guideline to study the feasibility domain of multi-trophic and changing ecological communities.

Science.gov (United States)

Song, Chuliang; Rohr, Rudolf P; Saavedra, Serguei

2018-04-24

The feasibility domain of an ecological community can be described by the set of environmental abiotic and biotic conditions under which all co-occurring and interacting species in a given site and time can have positive abundances. Mathematically, the feasibility domain corresponds to the parameter space compatible with positive (feasible) solutions at equilibrium for all the state variables in a system under a given model of population dynamics. Under specific dynamics, the existence of a feasible equilibrium is a necessary condition for species persistence regardless of whether the feasible equilibrium is dynamically stable or not. Thus, the size of the feasibility domain can also be used as an indicator of the tolerance of a community to random environmental variations. This has motivated a rich research agenda to estimate the feasibility domain of ecological communities. However, these methodologies typically assume that species interactions are static, or that input and output energy flows on each trophic level are unconstrained. Yet, this is different to how communities behave in nature. Here, we present a step-by-step quantitative guideline providing illustrative examples, computational code, and mathematical proofs to study systematically the feasibility domain of ecological communities under changes of interspecific interactions and subject to different constraints on the trophic energy flows. This guideline covers multi-trophic communities that can be formed by any type of interspecific interactions. Importantly, we show that the relative size of the feasibility domain can significantly change as a function of the biological information taken into consideration. We believe that the availability of these methods can allow us to increase our understanding about the limits at which ecological communities may no longer tolerate further environmental perturbations, and can facilitate a stronger integration of theoretical and empirical research. Copyright �

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

Cross-Layer Framework for Fine-Grained Channel Access in Next Generation High-Density WiFi Networks

Institute of Scientific and Technical Information of China (English)

ZHAO Haitao; ZHANG Shaojie; Emiliano Garcia-Palacios

2016-01-01

Densely deployed WiFi networks will play a crucial role in providing the capacity for next generation mobile internet.However,due to increasing interference,overlapped channels in WiFi networks and throughput efficiency degradation,densely deployed WiFi networks is not a guarantee to obtain higher throughput.An emergent challenge is how to efficiently utilize scarce spectrum resources,by matching physical layer resources to traffic demand.In this aspect,access control allocation strategies play a pivotal role but remain too coarse-grained.As a solution,this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in WiFi networks.This approach,named SFCA (Subcarrier Fine-grained Channel Access),adopts DOFDM (Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer.It allocates the frequency resource with a subcarrier granularity,which facilitates the channel width adaptation for multi-channel access and thus brings more flexibility and higher frequency efficiency.The MAC layer uses a frequencytime domain backoff scheme,which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision,resulting in higher access probability for the contending nodes.SFCA is compared with FICA (an established access scheme) showing significant outperformance.Finally we present results for next generation 802.11 ac WiFi networks.

Improving collaboration between primary care research networks using Access Grid technology

Directory of Open Access Journals (Sweden)

Zsolt Nagykaldi

2008-05-01

Full Text Available Access Grid (AG is an Internet2-driven, high performance audio_visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN that is part of the National Institutes of Health (NIH Roadmap initiative to improve primary care research and collaboration among practice- based research networks (PBRNs in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.

Collaborative Networks for biodiversity domain organizations

NARCIS (Netherlands)

Ermilova, E.; Afsarmanesh, H.

2010-01-01

European scientific research and development organizations, operating in the domains of biology, ecology, and biodiversity, strongly need to cooperate/collaborate with other centers. Unavailability of interoperation infrastructure as well as the needed collaboration environment among research

Decomposing social and semantic networks in emerging "big data" research

NARCIS (Netherlands)

Park, H.W.; Leydesdorff, L.

2013-01-01

This paper examines the structural patterns of networks of internationally co-authored SCI papers in the domain of research driven by big data and provides an empirical analysis of semantic patterns of paper titles. The results based on data collected from the DVD version of the 2011 SCI database

Riemannian multi-manifold modeling and clustering in brain networks

Science.gov (United States)

Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

Science.gov (United States)

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

NHERI: Advancing the Research Infrastructure of the Multi-Hazard Community

Science.gov (United States)

Blain, C. A.; Ramirez, J. A.; Bobet, A.; Browning, J.; Edge, B.; Holmes, W.; Johnson, D.; Robertson, I.; Smith, T.; Zuo, D.

2017-12-01

The Natural Hazards Engineering Research Infrastructure (NHERI), supported by the National Science Foundation (NSF), is a distributed, multi-user national facility that provides the natural hazards research community with access to an advanced research infrastructure. Components of NHERI are comprised of a Network Coordination Office (NCO), a cloud-based cyberinfrastructure (DesignSafe-CI), a computational modeling and simulation center (SimCenter), and eight Experimental Facilities (EFs), including a post-disaster, rapid response research facility (RAPID). Utimately NHERI enables researchers to explore and test ground-breaking concepts to protect homes, businesses and infrastructure lifelines from earthquakes, windstorms, tsunamis, and surge enabling innovations to help prevent natural hazards from becoming societal disasters. When coupled with education and community outreach, NHERI will facilitate research and educational advances that contribute knowledge and innovation toward improving the resiliency of the nation's civil infrastructure to withstand natural hazards. The unique capabilities and coordinating activities over Year 1 between NHERI's DesignSafe-CI, the SimCenter, and individual EFs will be presented. Basic descriptions of each component are also found at https://www.designsafe-ci.org/facilities/. Additionally to be discussed are the various roles of the NCO in leading development of a 5-year multi-hazard science plan, coordinating facility scheduling and fostering the sharing of technical knowledge and best practices, leading education and outreach programs such as the recent Summer Institute and multi-facility REU program, ensuring a platform for technology transfer to practicing engineers, and developing strategic national and international partnerships to support a diverse multi-hazard research and user community.

Survivable integrated grooming in multi-granularity optical networks

Science.gov (United States)

Wu, Jingjing; Guo, Lei; Wei, Xuetao; Liu, Yejun

2012-05-01

Survivability is an important issue to ensure the service continuity in optical network. At the same time, with the granularity of traffic demands ranging from sub-wavelength-level to wavelength-level, traffic demands need to be aggregated and carried over the network in order to utilize resources effectively. Therefore, multi-granularity grooming is proposed to save the cost and reduce the number of switching ports in Optical-Cross Connects (OXCs). However, current works mostly addressed the survivable wavelength or waveband grooming. Therefore, in this paper, we propose three heuristic algorithms called Multi-granularity Dedicated Protection Grooming (MDPG), Multi-granularity Shared Protection Grooming (MSPG) and Multi-granularity Mixed Protection Grooming (MMPG), respectively. All of them are performed based on the Survivable Multi-granularity Integrated Auxiliary Graph (SMIAG) that includes one Wavelength Integrated Auxiliary Graph (WIAG) for wavelength protection and one waveBand Integrated Auxiliary Graph (BIAG) for waveband protection. Numerical results show that MMPG has the lowest average port-cost, the best resource utilization ratio and the lowest blocking probability among these three algorithms. Compared with MDPG, MSPG has lower average port-cost, better resource utilization ratio and lower blocking probability.

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.

Next Generation Network Routing and Control Plane

DEFF Research Database (Denmark)

Fu, Rong

proved, the dominating Border Gateway Protocol (BGP) cannot address all the issues that in inter-domain QoS routing. Thus a new protocol or network architecture has to be developed to be able to carry the inter-domain traffic with the QoS and TE consideration. Moreover, the current network control also...... lacks the ability to cooperate between different domains and operators. The emergence of label switching transport technology such as of Multi-Protocol Label Switching (MPLS) or Generalized MPLS (GMPLS) supports the traffic transport in a finer granularity and more dedicated end-to-end Quality...... (RACF) provides the platform that enables cooperation and ubiquitous integration between networks. In this paper, we investigate in the network architecture, protocols and algorithms for inter-domain QoS routing and traffic engineering. The PCE based inter-domain routing architecture is enhanced...

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

Science.gov (United States)

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Dynamics of domain wall networks with junctions

International Nuclear Information System (INIS)

Avelino, P. P.; Oliveira, J. C. R. E.; Martins, C. J. A. P.; Menezes, J.; Menezes, R.

2008-01-01

We use a combination of analytic tools and an extensive set of the largest and most accurate three-dimensional field theory numerical simulations to study the dynamics of domain wall networks with junctions. We build upon our previous work and consider a class of models which, in the limit of large number N of coupled scalar fields, approaches the so-called ''ideal'' model (in terms of its potential to lead to network frustration). We consider values of N between N=2 and N=20, and a range of cosmological epochs, and we also compare this class of models with other toy models used in the past. In all cases we find compelling evidence for a gradual approach to scaling, strongly supporting our no-frustration conjecture. We also discuss the various possible types of junctions (including cases where there is a hierarchy of them) and their roles in the dynamics of the network. Finally, we provide a cosmological Zel'dovich-type bound on the energy scale of this kind of defect network: it must be lower than 10 keV.

PS1-29: Resources to Facilitate Multi-site Collaboration: the PRIMER Research Toolkit

Science.gov (United States)

Greene, Sarah; Thompson, Ella; Baldwin, Laura-Mae; Neale, Anne Victoria; Dolor, Rowena

2010-01-01

Background and Aims: The national research enterprise has typically functioned in a decentralized fashion, resulting in duplicative or undocumented processes, impeding not only the pace of research, but diffusion of established best practices. To remedy this, many long-standing networks have begun capturing and documenting proven strategies to streamline and standardize various aspects of the research process. The project, “Partnership-driven Resources to IMprove and Enhance Research” (PRIMER), was funded through the Clinical and Translational Science Awards (CTSA) initiative to leverage the collective expertise from two networks: the HMO Research Network and Practice Based Research Networks (PBRNs). Each network has a shared goal of propagating research resources and best practices. Methods: We created and distributed an online survey to 92 CTSA and PBRN representatives in March, 2009 to define critical needs and existing resources that could inform a resource repository. The survey identified barriers and benefits to forming research partnerships, and assessed the perceived utility of various tools that could accelerate the research process. The study team identified, reviewed and organized tools based on the typical research trajectory from design to dissemination. Results: Fifty-five of 92 invitees (59%) completed the survey. Respondents rated the ability to conduct community-relevant research through true academic-community partnerships as the top-rated benefit of multi-site research, followed by the opportunity to accelerate translation of research into practice. The top two perceived barriers to multi-site research were ‘funding opportunities are not adequate (e.g., too few, not enough to support true collaborations), and ‘lack of research infrastructure to support [all] partners (e.g., no IT support, IRB, dedicated research staff). Respondents’ ratings of the utility of various tools and templates was used to guide development of an online

MrTADFinder: A network modularity based approach to identify topologically associating domains in multiple resolutions.

Directory of Open Access Journals (Sweden)

Koon-Kiu Yan

2017-07-01

Full Text Available Genome-wide proximity ligation based assays such as Hi-C have revealed that eukaryotic genomes are organized into structural units called topologically associating domains (TADs. From a visual examination of the chromosomal contact map, however, it is clear that the organization of the domains is not simple or obvious. Instead, TADs exhibit various length scales and, in many cases, a nested arrangement. Here, by exploiting the resemblance between TADs in a chromosomal contact map and densely connected modules in a network, we formulate TAD identification as a network optimization problem and propose an algorithm, MrTADFinder, to identify TADs from intra-chromosomal contact maps. MrTADFinder is based on the network-science concept of modularity. A key component of it is deriving an appropriate background model for contacts in a random chain, by numerically solving a set of matrix equations. The background model preserves the observed coverage of each genomic bin as well as the distance dependence of the contact frequency for any pair of bins exhibited by the empirical map. Also, by introducing a tunable resolution parameter, MrTADFinder provides a self-consistent approach for identifying TADs at different length scales, hence the acronym "Mr" standing for Multiple Resolutions. We then apply MrTADFinder to various Hi-C datasets. The identified domain boundaries are marked by characteristic signatures in chromatin marks and transcription factors (TF that are consistent with earlier work. Moreover, by calling TADs at different length scales, we observe that boundary signatures change with resolution, with different chromatin features having different characteristic length scales. Furthermore, we report an enrichment of HOT (high-occupancy target regions near TAD boundaries and investigate the role of different TFs in determining boundaries at various resolutions. To further explore the interplay between TADs and epigenetic marks, as tumor mutational

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%.

Scientometrical approach of the definition of a research domain using scientific journals

International Nuclear Information System (INIS)

Signogneau, A.

1995-01-01

The goal of this thesis is to analyse how the academic domain of a research entity can be defined by a panel of scientific journals. The aim of this work is to contribute to the creation of information tools as a help in research management. The first part gives an analysis of the scientific journals as markers of the scientific development: the production and diffusion of scientific journals and their ''scientometrical'' analysis (references, citation reports, citation indexes etc..). In the second part, a research unit is analyzed according to its related scientific journals and to its research domain. The SPAM (Photons, Atoms and Molecules Service) of the CEA was chosen for this task (main journals and co-publications network, specialization, main topics, collaborations and competition). The OST (Observatory of Sciences and Techniques) has in charge the production of scientific and technical indicators for research operators. The third part evaluates the methods used by the OST (analyses of reviews and journals) to provide a documentary corpus, taking the topic of the environment as an example. Finally the relevance of the information products obtained is evaluated. (J.S.)

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.

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...

Biomimicry of symbiotic multi-species coevolution for discrete and continuous optimization in RFID networks

Directory of Open Access Journals (Sweden)

Na Lin

2017-03-01

Full Text Available In recent years, symbiosis as a rich source of potential engineering applications and computational model has attracted more and more attentions in the adaptive complex systems and evolution computing domains. Inspired by different symbiotic coevolution forms in nature, this paper proposed a series of multi-swarm particle swarm optimizers called PS2Os, which extend the single population particle swarm optimization (PSO algorithm to interacting multi-swarms model by constructing hierarchical interaction topologies and enhanced dynamical update equations. According to different symbiotic interrelationships, four versions of PS2O are initiated to mimic mutualism, commensalism, predation, and competition mechanism, respectively. In the experiments, with five benchmark problems, the proposed algorithms are proved to have considerable potential for solving complex optimization problems. The coevolutionary dynamics of symbiotic species in each PS2O version are also studied respectively to demonstrate the heterogeneity of different symbiotic interrelationships that effect on the algorithm’s performance. Then PS2O is used for solving the radio frequency identification (RFID network planning (RNP problem with a mixture of discrete and continuous variables. Simulation results show that the proposed algorithm outperforms the reference algorithms for planning RFID networks, in terms of optimization accuracy and computation robustness.

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.

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...

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

Science.gov (United States)

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

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...

Magnetic hysteresis at the domain scale of a multi-scale material model for magneto-elastic behaviour

Energy Technology Data Exchange (ETDEWEB)

Vanoost, D., E-mail: dries.vanoost@kuleuven-kulak.be [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); Steentjes, S. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany); Peuteman, J. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Electrical Energy and Computer Architecture, Heverlee B-3001 (Belgium); Gielen, G. [KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); De Gersem, H. [KU Leuven Kulak, Wave Propagation and Signal Processing Research Group, Kortrijk B-8500 (Belgium); TU Darmstadt, Institut für Theorie Elektromagnetischer Felder, Darmstadt D-64289 (Germany); Pissoort, D. [KU Leuven Technology Campus Ostend, ReMI Research Group, Oostende B-8400 (Belgium); KU Leuven, Department of Electrical Engineering, Microelectronics and Sensors, Heverlee B-3001 (Belgium); Hameyer, K. [Institute of Electrical Machines, RWTH Aachen University, Aachen D-52062 (Germany)

2016-09-15

This paper proposes a multi-scale energy-based material model for poly-crystalline materials. Describing the behaviour of poly-crystalline materials at three spatial scales of dominating physical mechanisms allows accounting for the heterogeneity and multi-axiality of the material behaviour. The three spatial scales are the poly-crystalline, grain and domain scale. Together with appropriate scale transitions rules and models for local magnetic behaviour at each scale, the model is able to describe the magneto-elastic behaviour (magnetostriction and hysteresis) at the macroscale, although the data input is merely based on a set of physical constants. Introducing a new energy density function that describes the demagnetisation field, the anhysteretic multi-scale energy-based material model is extended to the hysteretic case. The hysteresis behaviour is included at the domain scale according to the micro-magnetic domain theory while preserving a valid description for the magneto-elastic coupling. The model is verified using existing measurement data for different mechanical stress levels. - Highlights: • A ferromagnetic hysteretic energy-based multi-scale material model is proposed. • The hysteresis is obtained by new proposed hysteresis energy density function. • Avoids tedious parameter identification.

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.

Structural basis of antifreeze activity of a bacterial multi-domain antifreeze protein.

Directory of Open Access Journals (Sweden)

Chen Wang

Full Text Available Antifreeze proteins (AFPs enhance the survival of organisms inhabiting cold environments by affecting the formation and/or structure of ice. We report the crystal structure of the first multi-domain AFP that has been characterized. The two ice binding domains are structurally similar. Each consists of an irregular β-helix with a triangular cross-section and a long α-helix that runs parallel on one side of the β-helix. Both domains are stabilized by hydrophobic interactions. A flat plane on the same face of each domain's β-helix was identified as the ice binding site. Mutating any of the smaller residues on the ice binding site to bulkier ones decreased the antifreeze activity. The bulky side chain of Leu174 in domain A sterically hinders the binding of water molecules to the protein backbone, partially explaining why antifreeze activity by domain A is inferior to that of domain B. Our data provide a molecular basis for understanding differences in antifreeze activity between the two domains of this protein and general insight on how structural differences in the ice-binding sites affect the activity of AFPs.

The Homogeneity Research of Urban Rail Transit Network Performance

Directory of Open Access Journals (Sweden)

Wang Fu-jian

2016-01-01

Full Text Available Urban Rail Transit is an important part of the public transit, it is necessary to carry out the corresponding network function analysis. Previous studies mainly about network performance analysis of a single city rail transit, lacking of horizontal comparison between the multi-city, it is difficult to find inner unity of different Urban Rail Transit network functions. Taking into account the Urban Rail Transit network is a typical complex networks, so this paper proposes the application of complex network theory to research the homogeneity of Urban Rail Transit network performance. This paper selects rail networks of Beijing, Shanghai, Guangzhou as calculation case, gave them a complex network mapping through the L, P Space method and had a static topological analysis using complex network theory, Network characteristics in three cities were calculated and analyzed form node degree distribution and node connection preference. Finally, this paper studied the network efficiency changes of Urban Rail Transit system under different attack mode. The results showed that, although rail transport network size, model construction and construction planning of the three cities are different, but their network performance in many aspects showed high homogeneity.

A feature dictionary supporting a multi-domain medical knowledge base.

Science.gov (United States)

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Multipath Routing in Wireless Sensor Networks: Survey and Research Challenges

Science.gov (United States)

Radi, Marjan; Dezfouli, Behnam; Bakar, Kamalrulnizam Abu; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks. PMID:22368490

Multipath routing in wireless sensor networks: survey and research challenges.

Science.gov (United States)

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Lee, Malrey

2012-01-01

A wireless sensor network is a large collection of sensor nodes with limited power supply and constrained computational capability. Due to the restricted communication range and high density of sensor nodes, packet forwarding in sensor networks is usually performed through multi-hop data transmission. Therefore, routing in wireless sensor networks has been considered an important field of research over the past decade. Nowadays, multipath routing approach is widely used in wireless sensor networks to improve network performance through efficient utilization of available network resources. Accordingly, the main aim of this survey is to present the concept of the multipath routing approach and its fundamental challenges, as well as the basic motivations for utilizing this technique in wireless sensor networks. In addition, we present a comprehensive taxonomy on the existing multipath routing protocols, which are especially designed for wireless sensor networks. We highlight the primary motivation behind the development of each protocol category and explain the operation of different protocols in detail, with emphasis on their advantages and disadvantages. Furthermore, this paper compares and summarizes the state-of-the-art multipath routing techniques from the network application point of view. Finally, we identify open issues for further research in the development of multipath routing protocols for wireless sensor networks.

Wifi, WiMax and LTE multi-hop mesh networks basic communication protocols and application areas

CERN Document Server

Wei, Hung-Yu; Dixit, Sudhir

2013-01-01

Wifi, WiMAX, and Cellular Multihop Networks presents an overview of WiFi-based and WiMAX-based multihop relay networks. As the first text to cover IEEE 802.16j multihop hop relay technology, this revolutionary resource explores the latest advances in multi-hop and ad-hoc networking. Not only does this reference provide the technological aspects, but also the applications for the emerging technology and architectural issues. Ranging from introductory material to advanced topics, this guidebook, plus PowerPoint slides, is essential for engineers, researchers, and students interested in

A domain-based approach to predict protein-protein interactions

Directory of Open Access Journals (Sweden)

Resat Haluk

2007-06-01

Full Text Available Abstract Background Knowing which proteins exist in a certain organism or cell type and how these proteins interact with each other are necessary for the understanding of biological processes at the whole cell level. The determination of the protein-protein interaction (PPI networks has been the subject of extensive research. Despite the development of reasonably successful methods, serious technical difficulties still exist. In this paper we present DomainGA, a quantitative computational approach that uses the information about the domain-domain interactions to predict the interactions between proteins. Results DomainGA is a multi-parameter optimization method in which the available PPI information is used to derive a quantitative scoring scheme for the domain-domain pairs. Obtained domain interaction scores are then used to predict whether a pair of proteins interacts. Using the yeast PPI data and a series of tests, we show the robustness and insensitivity of the DomainGA method to the selection of the parameter sets, score ranges, and detection rules. Our DomainGA method achieves very high explanation ratios for the positive and negative PPIs in yeast. Based on our cross-verification tests on human PPIs, comparison of the optimized scores with the structurally observed domain interactions obtained from the iPFAM database, and sensitivity and specificity analysis; we conclude that our DomainGA method shows great promise to be applicable across multiple organisms. Conclusion We envision the DomainGA as a first step of a multiple tier approach to constructing organism specific PPIs. As it is based on fundamental structural information, the DomainGA approach can be used to create potential PPIs and the accuracy of the constructed interaction template can be further improved using complementary methods. Explanation ratios obtained in the reported test case studies clearly show that the false prediction rates of the template networks constructed

Modeling GMPLS and Optical MPLS Networks

DEFF Research Database (Denmark)

Christiansen, Henrik Lehrmann; Wessing, Henrik

2003-01-01

. The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...

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.

Fastest learning in small-world neural networks

International Nuclear Information System (INIS)

Simard, D.; Nadeau, L.; Kroeger, H.

2005-01-01

We investigate supervised learning in neural networks. We consider a multi-layered feed-forward network with back propagation. We find that the network of small-world connectivity reduces the learning error and learning time when compared to the networks of regular or random connectivity. Our study has potential applications in the domain of data-mining, image processing, speech recognition, and pattern recognition

Information rich mapping requirement to product architecture through functional system deployment: The multi entity domain approach

DEFF Research Database (Denmark)

Hauksdóttir, Dagný; Mortensen, Niels Henrik

2017-01-01

may impede the ability to evolve, maintain or reuse systems. In this paper the Multi Entity Domain Approach (MEDA) is presented. The approach combines different design information within the domain views, incorporates both Software and Hardware design and supports iterative requirements definition...

On the efficiency of BGP-TE extensions for GMPLS multi-domain routing

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Ruepp, Sarah Renée; Buron, Jakob Due

2009-01-01

This paper evaluates the efficiency of set of modifications to the border gateway protocol (BGP) which aim at providing flexible traffic engineering (TE) across multiple GMPLS domains. A short overview and analysis of existing proposals for BGP-TE extensions is presented. Based on that, three...... modifications are proposed for support of multi-domain TE: an end-to-end path-specific TE attribute, a border node attribute and a behavioral modification of the protocol. Via analysis and extensive simulations we show that the proposed enhancements successfully improve the most significant BGP drawbacks...

Networks of networks – An introduction

International Nuclear Information System (INIS)

Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

2015-01-01

Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

Routing protocol for wireless quantum multi-hop mesh backbone network based on partially entangled GHZ state

Science.gov (United States)

Xiong, Pei-Ying; Yu, Xu-Tao; Zhang, Zai-Chen; Zhan, Hai-Tao; Hua, Jing-Yu

2017-08-01

Quantum multi-hop teleportation is important in the field of quantum communication. In this study, we propose a quantum multi-hop communication model and a quantum routing protocol with multihop teleportation for wireless mesh backbone networks. Based on an analysis of quantum multi-hop protocols, a partially entangled Greenberger-Horne-Zeilinger (GHZ) state is selected as the quantum channel for the proposed protocol. Both quantum and classical wireless channels exist between two neighboring nodes along the route. With the proposed routing protocol, quantum information can be transmitted hop by hop from the source node to the destination node. Based on multi-hop teleportation based on the partially entangled GHZ state, a quantum route established with the minimum number of hops. The difference between our routing protocol and the classical one is that in the former, the processes used to find a quantum route and establish quantum channel entanglement occur simultaneously. The Bell state measurement results of each hop are piggybacked to quantum route finding information. This method reduces the total number of packets and the magnitude of air interface delay. The deduction of the establishment of a quantum channel between source and destination is also presented here. The final success probability of quantum multi-hop teleportation in wireless mesh backbone networks was simulated and analyzed. Our research shows that quantum multi-hop teleportation in wireless mesh backbone networks through a partially entangled GHZ state is feasible.

An Asynchronous Multi-Sensor Micro Control Unit for Wireless Body Sensor Networks (WBSNs

Directory of Open Access Journals (Sweden)

Ching-Hsing Luo

2011-07-01

Full Text Available In this work, an asynchronous multi-sensor micro control unit (MCU core is proposed for wireless body sensor networks (WBSNs. It consists of asynchronous interfaces, a power management unit, a multi-sensor controller, a data encoder (DE, and an error correct coder (ECC. To improve the system performance and expansion abilities, the asynchronous interface is created for handshaking different clock domains between ADC and RF with MCU. To increase the use time of the WBSN system, a power management technique is developed for reducing power consumption. In addition, the multi-sensor controller is designed for detecting various biomedical signals. To prevent loss error from wireless transmission, use of an error correct coding technique is important in biomedical applications. The data encoder is added for lossless compression of various biomedical signals with a compression ratio of almost three. This design is successfully tested on a FPGA board. The VLSI architecture of this work contains 2.68-K gate counts and consumes power 496-μW at 133-MHz processing rate by using TSMC 0.13-μm CMOS process. Compared with the previous techniques, this work offers higher performance, more functions, and lower hardware cost than other micro controller designs.

An investigation into multi-domain simulation for a pantographcatenary system

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Zdziebko Paweł

2017-01-01

Full Text Available There is a need for modelling various phenomena present in a pantograph-catenary structure, (e.g. wave propagation and its reflections, friction, aerodynamic and electromagnetic forces, which allows for a more reliable study on the dynamic behaviours of a railway pantograph, particularly in the case of high-speed trains. Hence, the creation a complex pantograph-catenary multi-domain model should help to effectively meet the above-mentioned requirements. The work presents a co-simulation approach to investigate the pantograph-catenary dynamic interaction. The elaborated co-simulation algorithm assumes data exchange between multibody models of a pantograph and finite element model of a catenary. The presented approach explores multi-domain phenomena that have an influence on the pantograph-catenary interaction. The nonlinear finite element catenary model takes into account the slackening of droppers, relatively large displacements and contact with the pantograph’s slider, while the multibody model of the pantograph considers friction forces and suspension springs. Additionally, aerodynamic forces caused by wind acting on the pantograph were computed using the fluid structure interaction method and implemented in the dynamic simulation. The influence on the pantograph-catenary interaction caused by electromagnetic force acting on the pantograph was investigated, along with the influence of the locomotive’s vertical vibrations and tilt.

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.

Follow the link: Digital Tracings of a Multi-Sited Space of Research

DEFF Research Database (Denmark)

Munk, Anders Kristian

The paper discusses the use of digital methods as an alternative way of generating what George Marcus calls 'posited logics of association' for use in multi-sited fieldwork. I draw on cases from an ongoing research project on the new nordic food movement and its on- and off-line assemblages. I do...... doing so I demonstrate how methods which are native to the digital domain - such as the link or the like as a valuation metric - may be re-appropriated as strategies in more ethnographic styles of work.......The paper discusses the use of digital methods as an alternative way of generating what George Marcus calls 'posited logics of association' for use in multi-sited fieldwork. I draw on cases from an ongoing research project on the new nordic food movement and its on- and off-line assemblages. I...

Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios

Science.gov (United States)

Sui, Guo; Li, Huajiao; Feng, Sida; Liu, Xueyong; Jiang, Meihui

2018-01-01

The multi-scale method is widely used in analyzing time series of financial markets and it can provide market information for different economic entities who focus on different periods. Through constructing multi-scale networks of price fluctuation correlation in the stock market, we can detect the topological relationship between each time series. Previous research has not addressed the problem that the original fluctuation correlation networks are fully connected networks and more information exists within these networks that is currently being utilized. Here we use listed coal companies as a case study. First, we decompose the original stock price fluctuation series into different time scales. Second, we construct the stock price fluctuation correlation networks at different time scales. Third, we delete the edges of the network based on thresholds and analyze the network indicators. Through combining the multi-scale method with the multi-threshold method, we bring to light the implicit information of fully connected networks.

Analysis of Trends in Cooperative Network Patterns for KAERI Researchers

International Nuclear Information System (INIS)

Chun, Young Choon; Lee, Hyun Soo

2016-01-01

There has been a trend toward faster results of research and accelerating inter-disciplinary convergence, under constraints in available resources. Under such reality, national and international cooperation with inter-sectoral research on science-technology-industry is becoming inevitable as a strategic approach for enhancing competitive edge on global dimension. This study gives an analysis on the cooperative network in nuclear research which bears multi-disciplinary technical feature. The study aims to visualize the cooperative network of KAERI(Korea Atomic Energy Research Institute) researchers, as the hub of the network, including academics and industry, with a view to provide insight on strengthening the cooperative network in nuclear research. This study accounted for the paper entries in SCI(E) in 2013 (538 papers) and 2015 (551 papers) with a view to identify cooperative research activities centered for KAERI. On international cooperation, the analysis showed a trend toward, first of all, diversification of partner countries. There were 118 entries of co-authorship with 22 countries in 2013 (41 with USA, 12 with Japan, 9 with India), which evolved to 121 entries in 2015 (34 for USA, 11 with China, 10 each with Japan and India). Secondly, there was a trend toward more number of countries evenly spread in 2015 compared to 2013, except a few major countries like USA, Japan, and India

Analysis of Trends in Cooperative Network Patterns for KAERI Researchers

Energy Technology Data Exchange (ETDEWEB)

Chun, Young Choon; Lee, Hyun Soo [KAERI, Daejeon (Korea, Republic of)

2016-05-15

There has been a trend toward faster results of research and accelerating inter-disciplinary convergence, under constraints in available resources. Under such reality, national and international cooperation with inter-sectoral research on science-technology-industry is becoming inevitable as a strategic approach for enhancing competitive edge on global dimension. This study gives an analysis on the cooperative network in nuclear research which bears multi-disciplinary technical feature. The study aims to visualize the cooperative network of KAERI(Korea Atomic Energy Research Institute) researchers, as the hub of the network, including academics and industry, with a view to provide insight on strengthening the cooperative network in nuclear research. This study accounted for the paper entries in SCI(E) in 2013 (538 papers) and 2015 (551 papers) with a view to identify cooperative research activities centered for KAERI. On international cooperation, the analysis showed a trend toward, first of all, diversification of partner countries. There were 118 entries of co-authorship with 22 countries in 2013 (41 with USA, 12 with Japan, 9 with India), which evolved to 121 entries in 2015 (34 for USA, 11 with China, 10 each with Japan and India). Secondly, there was a trend toward more number of countries evenly spread in 2015 compared to 2013, except a few major countries like USA, Japan, and India.

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.

A 170kDa multi-domain cystatin of Fasciola gigantica is active in the male reproductive system.

Science.gov (United States)

Geadkaew, Amornrat; Kosa, Nanthawat; Siricoon, Sinee; Grams, Suksiri Vichasri; Grams, Rudi

2014-09-01

Cystatins are functional as intra- and extracellular inhibitors of cysteine proteases and are expressed as single or multi-domain proteins. We have previously described two single domain type 1 cystatins in the trematode Fasciola gigantica that are released into the parasite's intestinal tract and exhibit inhibitory activity against endogenous and host cathepsin L and B proteases. In contrast, the here presented 170kDa multi-domain cystatin (FgMDC) comprises signal peptide and 12 tandem repeated cystatin-like domains with similarity to type 2 single domain cystatins. The domains show high sequence divergence with identity values often 120kDa molecular mass in immunoblots of parasite crude extracts and ES product with different banding patterns for each antiserum demonstrating complex processing of the proprotein. The four domains with the highest conserved QVVAG motifs were expressed in Escherichia coli and the refolded recombinant proteins blocked cysteine protease activity in the parasite's ES product. Strikingly, immunohistochemical analysis using seven domain-specific antisera localized FgMDC in testis lobes and sperm. It is speculated that the processed cystatin-like domains have function analogous to the mammalian group of male reproductive tissue-specific type 2 cystatins and are functional in spermiogenesis and fertilization. Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization of Multiple Related Negotiation through Multi-Negotiation Network

Science.gov (United States)

Ren, Fenghui; Zhang, Minjie; Miao, Chunyan; Shen, Zhiqi

In this paper, a Multi-Negotiation Network (MNN) and a Multi- Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome of MRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.

AN INITIATIVE FOR CONSTRUCTION OF NEW-GENERATION LUNAR GLOBAL CONTROL NETWORK USING MULTI-MISSION DATA

Directory of Open Access Journals (Sweden)

K. Di

2017-07-01

Full Text Available A lunar global control network provides geodetic datum and control points for mapping of the lunar surface. The widely used Unified Lunar Control Network 2005 (ULCN2005 was built based on a combined photogrammetric solution of Clementine images acquired in 1994 and earlier photographic data. In this research, we propose an initiative for construction of a new-generation lunar global control network using multi-mission data newly acquired in the 21st century, which have much better resolution and precision than the old data acquired in the last century. The new control network will be based on a combined photogrammetric solution of an extended global image and laser altimetry network. The five lunar laser ranging retro-reflectors, which can be identified in LROC NAC images and have cm level 3D position accuracy, will be used as absolute control points in the least squares photogrammetric adjustment. Recently, a new radio total phase ranging method has been developed and used for high-precision positioning of Chang’e-3 lander; this shall offer a new absolute control point. Systematic methods and key techniques will be developed or enhanced, including rigorous and generic geometric modeling of orbital images, multi-scale feature extraction and matching among heterogeneous multi-mission remote sensing data, optimal selection of images at areas of multiple image coverages, and large-scale adjustment computation, etc. Based on the high-resolution new datasets and developed new techniques, the new generation of global control network is expected to have much higher accuracy and point density than the ULCN2005.

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.

Architecture for an advanced biomedical collaboration domain for the European paediatric cancer research community (ABCD-4-E).

Science.gov (United States)

Nitzlnader, Michael; Falgenhauer, Markus; Gossy, Christian; Schreier, Günter

2015-01-01

Today, progress in biomedical research often depends on large, interdisciplinary research projects and tailored information and communication technology (ICT) support. In the context of the European Network for Cancer Research in Children and Adolescents (ENCCA) project the exchange of data between data source (Source Domain) and data consumer (Consumer Domain) systems in a distributed computing environment needs to be facilitated. This work presents the requirements and the corresponding solution architecture of the Advanced Biomedical Collaboration Domain for Europe (ABCD-4-E). The proposed concept utilises public as well as private cloud systems, the Integrating the Healthcare Enterprise (IHE) framework and web-based applications to provide the core capabilities in accordance with privacy and security needs. The utility of crucial parts of the concept was evaluated by prototypic implementation. A discussion of the design indicates that the requirements of ENCCA are fully met. A whole system demonstration is currently being prepared to verify that ABCD-4-E has the potential to evolve into a domain-bridging collaboration platform in the future.

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A [European Commission, Bruxelles (Belgium). DG XII/JRC

1996-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

European network for research in global change (ENRICH)

Energy Technology Data Exchange (ETDEWEB)

Ghazi, A. [European Commission, Bruxelles (Belgium). DG XII/JRC

1995-12-31

While approaching the beginning of the twenty first century, the scientific community is faced with the formidable tasks of monitoring and detecting, understanding and predicting changes in the Earth System and its interactions with human beings. A crucial challenge is to make scientific research results accessible and usable for those involved in the decision making process related to the concept of Sustainable Development. Major international scientific programmes under the umbrella of ICSU, such as the IGBP and WCRP, are dealing with these issues. Although there exist many well developed global change research programmes in several European countries and effective collaboration networks between research institutes, there is an urgent need for overall communication with a view to promoting wider international links ensuring complementarity, synergy and coherence. Recognizing the importance of promoting coherence in research and utilising research results for various European Union (EU) policies, the European Commissioner responsible for Science, Research and Development wrote in March 1992 to all the EU Research Ministers to propose an initiative in this domain. In a rapid response, a group of Senior Experts from the EU Member States was set up in April 1992. This Group established a Task Force to develop the concept of the European Network for Research In Global CHange (ENRICH) which was approved in July 1993

Magnetic vortex state and multi-domain pattern in electrodeposited hemispherical nanogranular nickel films

International Nuclear Information System (INIS)

Samardak, Alexander; Sukovatitsina, Ekaterina; Ognev, Alexey; Stebliy, Maksim; Davydenko, Alexander; Chebotkevich, Ludmila; Keun Kim, Young; Nasirpouri, Forough; Janjan, Seyed-Mehdi; Nasirpouri, Farzad

2014-01-01

Magnetic states of nickel nanogranular films were studied in two distinct structures of individual and agglomerated granules electrodeposited on n-type Si(1 1 1) surface from a modified Watts bath at a low pH of 2. Magnetic force microscopy and micromagnetic simulations revealed three-dimensional out-of-plane magnetic vortex states in stand-alone hemispherical granules and their arrays, and multi-domain patterns in large agglomerates and integrated films. Once the granules coalesce into small chains or clusters, the coercivity values increased due to the reduction of inter-granular spacing and strengthening of the magnetostatic interaction. Further growth leads to the formation of a continuous granulated film which strongly affected the coercivity and remanence. This was characterized by the domain wall nucleation and propagation leading to a stripe domain pattern. Magnetoresistance measurements as a function of external magnetic field are indicative of anisotropic magnetoresistance (AMR) for the continuous films electrodeposited on Si substrate. - Highlights: • Magnetic states of electrodeposited nickel in isolated spherical and agglomerated nanogranules, and a continuous film. • Preferential magnetization reversal mechanism in isolated granules is vortex state. • Micromagnetic simulations confirm the three-dimensional vortex. • Transition between the vortex state and multi-domain magnetic pattern causes a significant decrease in the coercive force. • Continuous nickel films electrodeposited on silicon substrate exhibit AMR whose magnitude increases with the film thickness

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

International Nuclear Information System (INIS)

Xie Wei-Hao; Zhou Bin; Liu En-Xiao; Lu Wei-Dang; Zhou Ting

2015-01-01

Many real communication networks, such as oceanic monitoring network and land environment observation network, can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue (HMQ) routing strategy and global forward-predicting hybrid minimum degree and queue (HMDQ) routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity. (paper)

An information theory framework for dynamic functional domain connectivity.

Science.gov (United States)

Vergara, Victor M; Miller, Robyn; Calhoun, Vince

2017-06-01

Dynamic functional network connectivity (dFNC) analyzes time evolution of coherent activity in the brain. In this technique dynamic changes are considered for the whole brain. This paper proposes an information theory framework to measure information flowing among subsets of functional networks call functional domains. Our method aims at estimating bits of information contained and shared among domains. The succession of dynamic functional states is estimated at the domain level. Information quantity is based on the probabilities of observing each dynamic state. Mutual information measurement is then obtained from probabilities across domains. Thus, we named this value the cross domain mutual information (CDMI). Strong CDMIs were observed in relation to the subcortical domain. Domains related to sensorial input, motor control and cerebellum form another CDMI cluster. Information flow among other domains was seldom found. Other methods of dynamic connectivity focus on whole brain dFNC matrices. In the current framework, information theory is applied to states estimated from pairs of multi-network functional domains. In this context, we apply information theory to measure information flow across functional domains. Identified CDMI clusters point to known information pathways in the basal ganglia and also among areas of sensorial input, patterns found in static functional connectivity. In contrast, CDMI across brain areas of higher level cognitive processing follow a different pattern that indicates scarce information sharing. These findings show that employing information theory to formally measured information flow through brain domains reveals additional features of functional connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

The network researchers' network

DEFF Research Database (Denmark)

Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

2009-01-01

The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi......The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

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.

MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

Science.gov (United States)

Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

2016-03-18

Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

Directory of Open Access Journals (Sweden)

Hongqiang Li

2016-10-01

Full Text Available Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

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.

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.

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.

Just how multi-level is leadership research? A document co-citation analysis 1980–2013 on leadership constructs and outcomes

OpenAIRE

Batistic, S.; Cerne, M.; Vogel, Bernd

2017-01-01

The use of multi-level theories and methodologies in leadership has gained momentum in recent years. However, the leadership field still suffers from a fragmented and unclear evolution and practice of multi-level approaches. The questions of how and to what extent multi-level research has evolved in both leadership phenomena and leadership outcomes, and which informal research networks drove this evolution, remain vastly unexplored. In this study, the extent of literature published between 19...

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

An Architecture to Manage Incoming Traffic of Inter-Domain Routing Using OpenFlow Networks

Directory of Open Access Journals (Sweden)

Walber José Adriano Silva

2018-04-01

Full Text Available The Border Gateway Protocol (BGP is the current state-of-the-art inter-domain routing between Autonomous Systems (ASes. Although BGP has different mechanisms to manage outbound traffic in an AS domain, it lacks an efficient tool for inbound traffic control from transit ASes such as Internet Service Providers (ISPs. For inter-domain routing, the BGP’s destination-based forwarding paradigm limits the granularity of distributing the network traffic among the multiple paths of the current Internet topology. Thus, this work offered a new architecture to manage incoming traffic in the inter-domain using OpenFlow networks. The architecture explored direct inter-domain communication to exchange control information and the functionalities of the OpenFlow protocol. Based on the achieved results of the size of exchanging messages, the proposed architecture is not only scalable, but also capable of performing load balancing for inbound traffic using different strategies.

Multi-beam synchronous measurement based on PSD phase detection using frequency-domain multiplexing

Science.gov (United States)

Duan, Ying; Qin, Lan; Xue, Lian; Xi, Feng; Mao, Jiubing

2013-10-01

According to the principle of centroid measurement, position-sensitive detectors (PSD) are commonly used for micro displacement detection. However, single-beam detection method cannot satisfy such tasks as multi-dimension position measurement, three dimension vision reconstruction, and robot precision positioning, which require synchronous measurement of multiple light beams. Consequently, we designed PSD phase detection method using frequency-domain multiplexing for synchronous detection of multiple modulated light beams. Compared to previous PSD amplitude detection method, the phase detection method using FDM has advantages of simplified measuring system, low cost, high capability of resistance to light interference as well as improved resolution. The feasibility of multi-beam synchronous measurement based on PSD phase detection using FDM was validated by multi-beam measuring experiments. The maximum non-linearity error of the multi-beam synchronous measurement is 6.62%.

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.

Doctoral research on architecture in Nigeria: Exploring domains, extending boundaries

Directory of Open Access Journals (Sweden)

Adetokunbo Oluwole Ilesanmi

2016-03-01

Full Text Available This paper explored through a literature review, the domains of research in Architecture and the nature of doctoral research, with a view to contributing to the evolving research agenda in the Nigerian context. The research method involved a descriptive and thematic analysis of the titles and abstracts of completed doctoral theses in Architecture in Nigeria, in the last 26 years (1990–2015, complemented by semi-structured interviews with six key informants. The study revealed an emphasis on Housing-related topics (34% relative to other research modules, such as׳ History and Theory׳ (20% and ׳Design and Production׳ (18%. It also reflected the limited coverage and scope of current research, relative to the global terrain, as evidenced in the article titles and contents of 45 Architecture-related Journals. The results of the interviews indicated the strong influence of supervisors׳ areas of interest in the choices of thesis titles. It highlighted reasons for the perceived focus on Housing, which reflect its unique place and multi-disciplinary nature. It concluded that extending the boundaries of architectural research at the doctoral level could be beneficial to the discipline and profession in Nigeria in order to align with global trends, while keeping cognizance of the local contexts.

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.

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.

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...

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.

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.

Do Nobel Laureates Create Prize-Winning Networks? An Analysis of Collaborative Research in Physiology or Medicine

NARCIS (Netherlands)

Wagner, Caroline S.; Horlings, Edwin; Whetsell, Travis A.; Mattson, Pauline; Nordqvist, Katarina

2015-01-01

Nobel Laureates in Physiology or Medicine who received the Prize between 1969 and 2011 are compared to a matched group of scientists to examine productivity, impact, coauthorship and international collaboration patterns embedded within research networks. After matching for research domain, h-index,

Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

Science.gov (United States)

Zheng, Yan

2015-03-01

Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

Library Research: A Domain Comparison of Two Library Journals

Science.gov (United States)

Davies, Karen; Thiele, Jennifer

2013-01-01

Research articles published by the "Community & Junior College Libraries" journal and the "College & Undergraduate Libraries" journal were analyzed to determine their domain. The discussion includes a comparison of past domain studies with the current research. The researchers found the majority of articles (52%) in the…

Recovering protein-protein and domain-domain interactions from aggregation of IP-MS proteomics of coregulator complexes.

Directory of Open Access Journals (Sweden)

Amin R Mazloom

2011-12-01

Full Text Available Coregulator proteins (CoRegs are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP followed by mass spectrometry (MS applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/.

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...

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...

An configuration method of patient service cloud for the home patient with multi sensor network

International Nuclear Information System (INIS)

Noji, Tamotsu; Arino, Masashi; Saito, Mayuko; Horii, Minoru; Ogino, Tadashi; Suto, Yasuzo; Sasaki, Hitoshi; Mansei, Kouiti

2010-01-01

We are advancing the research of patient service cloud in the global medical collaboration network system based on 3D electronic referral letters. In this paper it proposes one configuration method of private cloud that aims at the home care patient's health care and independence support based on voice navigation system (VONAVS). We evaluate 3D image compression rate, try image compositing Cloud's configuration by the multi sensor network, and search for the configuration method of the remote image diagnosis. The proposed configuration method expands the possibility to the global medical collaboration network system for new large areas such as a telemedicine, an emergency care, and home medical care. (author)

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin; Zhang Qi; Zheng Futang

2000-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images are presented. The software for object separating, mass calculating, 3D positioning, speed determining and cavity reconstruction are described

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin

2003-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images of terminal ballistics are presented. The software for object separating, profile calculating and 3D cavity reconstruction are described

[SOPHO-NET - a research network on psychotherapy for social phobia].

Science.gov (United States)

Leichsenring, Falk; Salzer, Simone; Beutel, Manfred E; von Consbruch, Katrin; Herpertz, Stephan; Hiller, Wolfgang; Hoyer, Jürgen; Hüsing, Johannes; Irle, Eva; Joraschky, Peter; Konnopka, Alexander; König, Hans-Helmut; de Liz, Therese; Nolting, Björn; Pöhlmann, Karin; Ruhleder, Mirjana; Schauenburg, Henning; Stangier, Ulrich; Strauss, Bernhard; Subic-Wrana, Claudia; Vormfelde, Stefan V; Weniger, Godehard; Willutzki, Ulrike; Wiltink, Jörg; Leibing, Eric

2009-01-01

This paper presents the Social Phobia Psychotherapy Research Network (SOPHO-NET). SOPHO-NET is among the five research networks on psychotherapy funded by "Bundesministerium für Bildung und Forschung". The research program encompasses a coordinated group of studies of social phobia. In the central project (Study A), a multi-center randomized controlled trial, refined models of manualized cognitive-behavioral therapy (CBT) and manualized short-term psychodynamic psychotherapy (STPP) are compared in the treatment of social phobia. A sample of n=512 outpatients will be randomized to either CBT, STPP or wait list. For quality assurance and treatment integrity, a specific project has been established (Project Q). Study A is complemented by four interrelated projects focusing on attachment style (Study B1), cost-effectiveness (Study B2), polymorphisms in the serotonin transporter gene (Study C1) and on structural and functional deviations of hippocampus and amygdala (Study C2). Thus, the SOPHO-NET program allows for a highly interdisciplinary research of psychotherapy in social phobia.

Multi-agent systems simulation and applications

CERN Document Server

Uhrmacher, Adelinde M

2009-01-01

Methodological Guidelines for Modeling and Developing MAS-Based SimulationsThe intersection of agents, modeling, simulation, and application domains has been the subject of active research for over two decades. Although agents and simulation have been used effectively in a variety of application domains, much of the supporting research remains scattered in the literature, too often leaving scientists to develop multi-agent system (MAS) models and simulations from scratch. Multi-Agent Systems: Simulation and Applications provides an overdue review of the wide ranging facets of MAS simulation, i

Performance Analysis of RF-FSO Multi-Hop Networks

KAUST Repository

Makki, Behrooz; Svensson, Tommy; Brandt-Pearce, Maite; Alouini, Mohamed-Slim

2017-01-01

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

Degrees of Freedom of Asymmetrical Multi-Way Relay Networks

DEFF Research Database (Denmark)

Sun, Fan; De Carvalho, Elisabeth

2011-01-01

In this paper, we introduce an asymmetrical multi-way relay channel where a base station conveys independent symbols to K different users while receiving independent symbols from the users. In this network, user i Shas Mi antennas (i ∈ [1, ..., K]), the base station has Σi=1K Mi antennas and the ......In this paper, we introduce an asymmetrical multi-way relay channel where a base station conveys independent symbols to K different users while receiving independent symbols from the users. In this network, user i Shas Mi antennas (i ∈ [1, ..., K]), the base station has Σi=1K Mi antennas...... and the relay is equipped with NR antennas. To study the capacity of this network, the degree of freedom (DOF) is characterized to be 2 Σi=1K Mi if NR ≥ Σi=1K Mi. The DOF implies that the number of symbols any transmitter can deliver and receive is equivalent to its number of antennas. The DOF is achievable...

Effects of biases in domain wall network evolution. II. Quantitative analysis

Science.gov (United States)

Correia, J. R. C. C. C.; Leite, I. S. C. R.; Martins, C. J. A. P.

2018-04-01

Domain walls form at phase transitions which break discrete symmetries. In a cosmological context, they often overclose the Universe (contrary to observational evidence), although one may prevent this by introducing biases or forcing anisotropic evolution of the walls. In a previous work [Correia et al., Phys. Rev. D 90, 023521 (2014), 10.1103/PhysRevD.90.023521], we numerically studied the evolution of various types of biased domain wall networks in the early Universe, confirming that anisotropic networks ultimately reach scaling while those with a biased potential or biased initial conditions decay. We also found that the analytic decay law obtained by Hindmarsh was in good agreement with simulations of biased potentials, but not of biased initial conditions, and suggested that the difference was related to the Gaussian approximation underlying the analytic law. Here, we extend our previous work in several ways. For the cases of biased potential and biased initial conditions, we study in detail the field distributions in the simulations, confirming that the validity (or not) of the Gaussian approximation is the key difference between the two cases. For anisotropic walls, we carry out a more extensive set of numerical simulations and compare them to the canonical velocity-dependent one-scale model for domain walls, finding that the model accurately predicts the linear scaling regime after isotropization. Overall, our analysis provides a quantitative description of the cosmological evolution of these networks.

3D High Resolution Mesh Deformation Based on Multi Library Wavelet Neural Network Architecture

Science.gov (United States)

Dhibi, Naziha; Elkefi, Akram; Bellil, Wajdi; Amar, Chokri Ben

2016-12-01

This paper deals with the features of a novel technique for large Laplacian boundary deformations using estimated rotations. The proposed method is based on a Multi Library Wavelet Neural Network structure founded on several mother wavelet families (MLWNN). The objective is to align features of mesh and minimize distortion with a fixed feature that minimizes the sum of the distances between all corresponding vertices. New mesh deformation method worked in the domain of Region of Interest (ROI). Our approach computes deformed ROI, updates and optimizes it to align features of mesh based on MLWNN and spherical parameterization configuration. This structure has the advantage of constructing the network by several mother wavelets to solve high dimensions problem using the best wavelet mother that models the signal better. The simulation test achieved the robustness and speed considerations when developing deformation methodologies. The Mean-Square Error and the ratio of deformation are low compared to other works from the state of the art. Our approach minimizes distortions with fixed features to have a well reconstructed object.

Design and Performance Analysis of Multi-tier Heterogeneous Network through Coverage, Throughput and Energy Efficiency

Directory of Open Access Journals (Sweden)

A. Shabbir,

2017-12-01

Full Text Available The unprecedented acceleration in wireless industry strongly compels wireless operators to increase their data network throughput, capacity and coverage on emergent basis. In upcoming 5G heterogeneous networks inclusion of low power nodes (LPNs like pico cells and femto cells for increasing network’s throughput, capacity and coverage are getting momentum. Addition of LPNs in such a massive level will eventually make a network populated in terms of base stations (BSs.The dense deployments of BSs will leads towards high operating expenditures (Op-Ex, capital expenditure (Cap-Ex and most importantly high energy consumption in future generation networks. Recognizing theses networks issues this research work investigates data throughput and energy efficiency of 5G multi-tier heterogeneous network. The network is modeled using tools from stochastic geometry. Monte Carlo results confirmed that rational deployment of LPNs can contribute towards increased throughput along with better energy efficiency of overall network.

Domain Specific Language Support for Exascale

Energy Technology Data Exchange (ETDEWEB)

Mellor-Crummey, John [Rice Univ., Houston, TX (United States)

2017-10-20

A multi-institutional project known as D-TEC (short for “Domain- specific Technology for Exascale Computing”) set out to explore technologies to support the construction of Domain Specific Languages (DSLs) to map application programs to exascale architectures. DSLs employ automated code transformation to shift the burden of delivering portable performance from application programmers to compilers. Two chief properties contribute: DSLs permit expression at a high level of abstraction so that a programmer’s intent is clear to a compiler and DSL implementations encapsulate human domain-specific optimization knowledge so that a compiler can be smart enough to achieve good results on specific hardware. Domain specificity is what makes these properties possible in a programming language. If leveraging domain specificity is the key to keep exascale software tractable, a corollary is that many different DSLs will be needed to encompass the full range of exascale computing applications; moreover, a single application may well need to use several different DSLs in conjunction. As a result, developing a general toolkit for building domain-specific languages was a key goal for the D-TEC project. Different aspects of the D-TEC research portfolio were the focus of work at each of the partner institutions in the multi-institutional project. D-TEC research and development work at Rice University focused on on three principal topics: understanding how to automate the tuning of code for complex architectures, research and development of the Rosebud DSL engine, and compiler technology to support complex execution platforms. This report provides a summary of the research and development work on the D-TEC project at Rice University.

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.

ENHANCING NETWORK SECURITY USING 'LEARNING-FROM-SIGNALS' AND FRACTIONAL FOURIER TRANSFORM BASED RF-DNA FINGERPRINTS

Energy Technology Data Exchange (ETDEWEB)

Buckner, Mark A [ORNL; Bobrek, Miljko [ORNL; Farquhar, Ethan [ORNL; Harmer, Paul K [Air Force Institute of Technology; Temple, Michael A [Air Force Institute of Technology

2011-01-01

Wireless Access Points (WAP) remain one of the top 10 network security threats. This research is part of an effort to develop a physical (PHY) layer aware Radio Frequency (RF) air monitoring system with multi-factor authentication to provide a first-line of defense for network security--stopping attackers before they can gain access to critical infrastructure networks through vulnerable WAPs. This paper presents early results on the identification of OFDM-based 802.11a WiFi devices using RF Distinct Native Attribute (RF-DNA) fingerprints produced by the Fractional Fourier Transform (FRFT). These fingerprints are input to a "Learning from Signals" (LFS) classifier which uses hybrid Differential Evolution/Conjugate Gradient (DECG) optimization to determine the optimal features for a low-rank model to be used for future predictions. Results are presented for devices under the most challenging conditions of intra-manufacturer classification, i.e., same-manufacturer, same-model, differing only in serial number. The results of Fractional Fourier Domain (FRFD) RF-DNA fingerprints demonstrate significant improvement over results based on Time Domain (TD), Spectral Domain (SD) and even Wavelet Domain (WD) fingerprints.

MULTI-PHOTON PHOSPHOR FEASIBILITY RESEARCH

Energy Technology Data Exchange (ETDEWEB)

R. Graham; W. Chow

2003-05-01

Development of multi-photon phosphor materials for discharge lamps represents a goal that would achieve up to a doubling of discharge (fluorescent) lamp efficacy. This report reviews the existing literature on multi-photon phosphors, identifies obstacles in developing such phosphors, and recommends directions for future research to address these obstacles. To critically examine issues involved in developing a multi-photon phosphor, the project brought together a team of experts from universities, national laboratories, and an industrial lamp manufacturer. Results and findings are organized into three categories: (1) Multi-Photon Systems and Processes, (2) Chemistry and Materials Issues, and (3) Concepts and Models. Multi-Photon Systems and Processes: This category focuses on how to use our current understanding of multi-photon phosphor systems to design new phosphor systems for application in fluorescent lamps. The quickest way to develop multi-photon lamp phosphors lies in finding sensitizer ions for Gd{sup 3+} and identifying activator ions to red shift the blue emission from Pr{sup 3+} due to the {sup 1}S{sub 0} {yields} {sup 1}I{sub 6} transition associated with the first cascading step. Success in either of these developments would lead to more efficient fluorescent lamps. Chemistry and Materials Issues: The most promising multi-photon phosphors are found in fluoride hosts. However, stability of fluorides in environments typically found in fluorescent lamps needs to be greatly improved. Experimental investigation of fluorides in actual lamp environments needs to be undertaken while working on oxide and oxyfluoride alternative systems for backup. Concepts and Models: Successful design of a multi-photon phosphor system based on cascading transitions of Gd{sup 3+} and Pr{sup 3+} depends critically on how the former can be sensitized and the latter can sensitize an activator ion. Methods to predict energy level diagrams and Judd-Ofelt parameters of multi

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

KAUST Repository

Moubayed, Abdallah J.

2014-05-01

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 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%. Furthermore, with the use of fractional cooperation, the average recovery overhead is further reduced by around 5% for the primary network and around 10% for the secondary network when a high fractional cooperation probability is used.

Content-based organization of the information space in multi-database networks

NARCIS (Netherlands)

Papazoglou, M.; Milliner, S.

1998-01-01

Abstract. Rapid growth in the volume of network-available data, complexity, diversity and terminological fluctuations, at different data sources, render network-accessible information increasingly difficult to achieve. The situation is particularly cumbersome for users of multi-database systems who

Multi-stability and almost periodic solutions of a class of recurrent neural networks

International Nuclear Information System (INIS)

Liu Yiguang; You Zhisheng

2007-01-01

This paper studies multi-stability, existence of almost periodic solutions of a class of recurrent neural networks with bounded activation functions. After introducing a sufficient condition insuring multi-stability, many criteria guaranteeing existence of almost periodic solutions are derived using Mawhin's coincidence degree theory. All the criteria are constructed without assuming the activation functions are smooth, monotonic or Lipschitz continuous, and that the networks contains periodic variables (such as periodic coefficients, periodic inputs or periodic activation functions), so all criteria can be easily extended to fit many concrete forms of neural networks such as Hopfield neural networks, or cellular neural networks, etc. Finally, all kinds of simulations are employed to illustrate the criteria

A Multi-Level Model of Information Seeking in the Clinical Domain

Science.gov (United States)

Hung, Peter W.; Johnson, Stephen B.; Kaufman, David R.; Mendonça, Eneida A.

2008-01-01

Objective: Clinicians often have difficulty translating information needs into effective search strategies to find appropriate answers. Information retrieval systems employing an intelligent search agent that generates adaptive search strategies based on human search expertise could be helpful in meeting clinician information needs. A prerequisite for creating such systems is an information seeking model that facilitates the representation of human search expertise. The purpose of developing such a model is to provide guidance to information seeking system development and to shape an empirical research program. Design: The information seeking process was modeled as a complex problem-solving activity. After considering how similarly complex activities had been modeled in other domains, we determined that modeling context-initiated information seeking across multiple problem spaces allows the abstraction of search knowledge into functionally consistent layers. The knowledge layers were identified in the information science literature and validated through our observations of searches performed by health science librarians. Results: A hierarchical multi-level model of context-initiated information seeking is proposed. Each level represents (1) a problem space that is traversed during the online search process, and (2) a distinct layer of knowledge that is required to execute a successful search. Grand strategy determines what information resources will be searched, for what purpose, and in what order. The strategy level represents an overall approach for searching a single resource. Tactics are individual moves made to further a strategy. Operations are mappings of abstract intentions to information resource-specific concrete input. Assessment is the basis of interaction within the strategic hierarchy, influencing the direction of the search. Conclusion: The described multi-level model provides a framework for future research and the foundation for development of an

Networked Airborne Communications Using Adaptive Multi Beam Directional Links

Science.gov (United States)

2016-03-05

Networked Airborne Communications Using Adaptive Multi-Beam Directional Links R. Bruce MacLeod Member, IEEE, and Adam Margetts Member, IEEE MIT...provide new techniques for increasing throughput in airborne adaptive directional net- works. By adaptive directional linking, we mean systems that can...techniques can dramatically increase the capacity in airborne networks. Advances in digital array technology are beginning to put these gains within reach

Frequency-Domain Adaptive Algorithm for Network Echo Cancellation in VoIP

Directory of Open Access Journals (Sweden)

Patrick A. Naylor

2008-05-01

Full Text Available We propose a new low complexity, low delay, and fast converging frequency-domain adaptive algorithm for network echo cancellation in VoIP exploiting MMax and sparse partial (SP tap-selection criteria in the frequency domain. We incorporate these tap-selection techniques into the multidelay filtering (MDF algorithm in order to mitigate the delay inherent in frequency-domain algorithms. We illustrate two such approaches and discuss their tradeoff between convergence performance and computational complexity. Simulation results show an improvement in convergence rate for the proposed algorithm over MDF and significantly reduced complexity. The proposed algorithm achieves a convergence performance close to that of the recently proposed, but substantially more complex improved proportionate MDF (IPMDF algorithm.

Frequency domain phase retrieval of simultaneous multi-wavelength phase-shifting interferometry

International Nuclear Information System (INIS)

Yin, Zhenxing; Zhong, Liyun; Xu, Xiaofei; Zhang, Wangping; Lu, Xiaoxu; Tian, Jindong

2016-01-01

In simultaneous multi-wavelength phase-shifting interferometry, we propose a novel frequency domain phase retrieval (FDPR) algorithm. First, using only a one-time phase-shifting operation, a sequence of simultaneous multi-wavelength phase-shifting interferograms (SPSMWIs) are captured by a monochrome charge-coupled device. Second, by performing a Fourier transform for each pixel of SPSMWIs, the wrapped phases of each wavelength can be retrieved from the complex amplitude located in the spectral peak of each wavelength. Finally, the phase of the synthetic wavelength can be obtained by the subtraction between the wrapped phases of a single wavelength. In this study, the principle and the application condition of the proposed approach are discussed. Both the simulation and the experimental result demonstrate the simple and convenient performance of the proposed FDPR approach. (paper)

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

Science.gov (United States)

Huang, Yue; Zheng, Han; Liu, Chi; Ding, Xinghao; Rohde, Gustavo K

2017-11-01

Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications. A very simple but effective deep learning method, that introduces the concept of unsupervised domain adaptation to a simple convolutional neural network (CNN), has been proposed in this paper. Inspired by transfer learning, our paper assumes that the training data and testing data follow different distributions, and there is an adaptation operation to more accurately estimate the kernels in CNN in feature extraction, in order to enhance performance by transferring knowledge from labeled data in source domain to unlabeled data in target domain. The model has been evaluated using three independent public epithelium-stroma datasets by cross-dataset validations. The experimental results demonstrate that for epithelium-stroma classification, the proposed framework outperforms the state-of-the-art deep neural network model, and it also achieves better performance than other existing deep domain adaptation methods. The proposed model can be considered to be a better option for real-world applications in histopathological image analysis, since there is no longer a requirement for large-scale labeled data in each specified domain.

Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

Science.gov (United States)

Garamszegi, Sara; Franzosa, Eric A; Xia, Yu

2013-01-01

A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1) domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2) domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral-host interactions that are

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Dhakal, Tilak Raj [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-02-27

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crack tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the

Distributed Multi-Commodity Network Flow Algorithm for Energy Optimal Routing in Wireless Sensor Networks.

Directory of Open Access Journals (Sweden)

J. Trdlicka

2010-12-01

Full Text Available This work proposes a distributed algorithm for energy optimal routing in a wireless sensor network. The routing problem is described as a mathematical problem by the minimum-cost multi-commodity network flow problem. Due to the separability of the problem, we use the duality theorem to derive the distributed algorithm. The algorithm computes the energy optimal routing in the network without any central node or knowledge of the whole network structure. Each node only needs to know the flow which is supposed to send or receive and the costs and capacities of the neighboring links. An evaluation of the presented algorithm on benchmarks for the energy optimal data flow routing in sensor networks with up to 100 nodes is presented.

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

A new multi objective optimization model for designing a green supply chain network under uncertainty

Directory of Open Access Journals (Sweden)

Mohammad Mahdi Saffar

2015-01-01

Full Text Available Recently, researchers have focused on how to minimize the negative effects of industrial activities on environment. Consequently, they work on mathematical models, which minimize the environmental issues as well as optimizing the costs. In the field of supply chain network design, most managers consider economic and environmental issues, simultaneously. This paper introduces a bi-objective supply chain network design, which uses fuzzy programming to obtain the capability of resisting uncertain conditions. The design considers production, recovery, and distribution centers. The advantage of using this model includes the optimal facilities, locating them and assigning the optimal facilities to them. It also chooses the type and the number of technologies, which must be bought. The fuzzy programming converts the multi objective model to an auxiliary crisp model by Jimenez approach and solves it with ε-constraint. For solving large size problems, the Multi Objective Differential Evolutionary algorithm (MODE is applied.

Network module detection: Affinity search technique with the multi-node topological overlap measure.

Science.gov (United States)

Li, Ai; Horvath, Steve

2009-07-20

Many clustering procedures only allow the user to input a pairwise dissimilarity or distance measure between objects. We propose a clustering method that can input a multi-point dissimilarity measure d(i1, i2, ..., iP) where the number of points P can be larger than 2. The work is motivated by gene network analysis where clusters correspond to modules of highly interconnected nodes. Here, we define modules as clusters of network nodes with high multi-node topological overlap. The topological overlap measure is a robust measure of interconnectedness which is based on shared network neighbors. In previous work, we have shown that the multi-node topological overlap measure yields biologically meaningful results when used as input of network neighborhood analysis. We adapt network neighborhood analysis for the use of module detection. We propose the Module Affinity Search Technique (MAST), which is a generalized version of the Cluster Affinity Search Technique (CAST). MAST can accommodate a multi-node dissimilarity measure. Clusters grow around user-defined or automatically chosen seeds (e.g. hub nodes). We propose both local and global cluster growth stopping rules. We use several simulations and a gene co-expression network application to argue that the MAST approach leads to biologically meaningful results. We compare MAST with hierarchical clustering and partitioning around medoid clustering. Our flexible module detection method is implemented in the MTOM software which can be downloaded from the following webpage: http://www.genetics.ucla.edu/labs/horvath/MTOM/

Network neighborhood analysis with the multi-node topological overlap measure.

Science.gov (United States)

Li, Ai; Horvath, Steve

2007-01-15

The goal of neighborhood analysis is to find a set of genes (the neighborhood) that is similar to an initial 'seed' set of genes. Neighborhood analysis methods for network data are important in systems biology. If individual network connections are susceptible to noise, it can be advantageous to define neighborhoods on the basis of a robust interconnectedness measure, e.g. the topological overlap measure. Since the use of multiple nodes in the seed set may lead to more informative neighborhoods, it can be advantageous to define multi-node similarity measures. The pairwise topological overlap measure is generalized to multiple network nodes and subsequently used in a recursive neighborhood construction method. A local permutation scheme is used to determine the neighborhood size. Using four network applications and a simulated example, we provide empirical evidence that the resulting neighborhoods are biologically meaningful, e.g. we use neighborhood analysis to identify brain cancer related genes. An executable Windows program and tutorial for multi-node topological overlap measure (MTOM) based analysis can be downloaded from the webpage (http://www.genetics.ucla.edu/labs/horvath/MTOM/).

Regulatory networks, legal federalism, and multi-level regulatory systems

OpenAIRE

Kerber, Wolfgang; Wendel, Julia

2016-01-01

Transnational regulatory networks play important roles in multi-level regulatory regimes, as e.g, the European Union. In this paper we analyze the role of regulatory networks from the perspective of the economic theory of legal federalism. Often sophisticated intermediate institutional solutions between pure centralisation and pure decentralisation can help to solve complex tradeoff problems between the benefits and problems of centralised and decentralised solutions. Drawing upon the insight...

A Survey on Virtualization of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Ga-Won Lee

2012-02-01

Full Text Available Wireless Sensor Networks (WSNs are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.

A Survey on Virtualization of Wireless Sensor Networks

Science.gov (United States)

Islam, Md. Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization. PMID:22438759

A survey on virtualization of Wireless Sensor Networks.

Science.gov (United States)

Islam, Md Motaharul; Hassan, Mohammad Mehedi; Lee, Ga-Won; Huh, Eui-Nam

2012-01-01

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization.

EnzDP: improved enzyme annotation for metabolic network reconstruction based on domain composition profiles.

Science.gov (United States)

Nguyen, Nam-Ninh; Srihari, Sriganesh; Leong, Hon Wai; Chong, Ket-Fah

2015-10-01

Determining the entire complement of enzymes and their enzymatic functions is a fundamental step for reconstructing the metabolic network of cells. High quality enzyme annotation helps in enhancing metabolic networks reconstructed from the genome, especially by reducing gaps and increasing the enzyme coverage. Currently, structure-based and network-based approaches can only cover a limited number of enzyme families, and the accuracy of homology-based approaches can be further improved. Bottom-up homology-based approach improves the coverage by rebuilding Hidden Markov Model (HMM) profiles for all known enzymes. However, its clustering procedure relies firmly on BLAST similarity score, ignoring protein domains/patterns, and is sensitive to changes in cut-off thresholds. Here, we use functional domain architecture to score the association between domain families and enzyme families (Domain-Enzyme Association Scoring, DEAS). The DEAS score is used to calculate the similarity between proteins, which is then used in clustering procedure, instead of using sequence similarity score. We improve the enzyme annotation protocol using a stringent classification procedure, and by choosing optimal threshold settings and checking for active sites. Our analysis shows that our stringent protocol EnzDP can cover up to 90% of enzyme families available in Swiss-Prot. It achieves a high accuracy of 94.5% based on five-fold cross-validation. EnzDP outperforms existing methods across several testing scenarios. Thus, EnzDP serves as a reliable automated tool for enzyme annotation and metabolic network reconstruction. Available at: www.comp.nus.edu.sg/~nguyennn/EnzDP .

Multi-year expansion planning of large transmission networks

Energy Technology Data Exchange (ETDEWEB)

Binato, S; Oliveira, G C [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil)

1994-12-31

This paper describes a model for multi-year transmission network expansion to be used in long-term system planning. The network is represented by a linearized (DC) power flow and, for each year, operation costs are evaluated by a linear programming (LP) based algorithm that provides sensitivity indices for circuit reinforcements. A Backward/Forward approaches is proposed to devise an expansion plan over the study period. A case study with the southeastern Brazilian system is presented and discussed. (author) 18 refs., 5 figs., 1 tab.

Multi-objective ant algorithm for wireless sensor network positioning

International Nuclear Information System (INIS)

Fidanova, S.; Shindarov, M.; Marinov, P.

2013-01-01

It is impossible to imagine our modern life without telecommunications. Wireless networks are a part of telecommunications. Wireless sensor networks (WSN) consist of spatially distributed sensors, which communicate in wireless way. This network monitors physical or environmental conditions. The objective is the full coverage of the monitoring region and less energy consumption of the network. The most appropriate approach to solve the problem is metaheuristics. In this paper the full coverage of the area is treated as a constrain. The objectives which are optimized are a minimal number of sensors and energy (lifetime) of the network. We apply multi-objective Ant Colony Optimization to solve this important telecommunication problem. We chose MAX-MIN Ant System approach, because it is proven to converge to the global optima

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.

Cracking up (and down): Linking multi-domain hydraulic properties with multi-scale hydrological processes in shrink-swell soils

Science.gov (United States)

Stewart, R. D.; Rupp, D. E.; Abou Najm, M. R.; Selker, J. S.

2017-12-01

Shrink-swell soils, often classified as Vertisols or vertic intergrades, are found on every continent except Antarctica and within many agricultural and urban regions. These soils are characterized by cyclical shrinking and swelling, in which bulk density and porosity distributions vary as functions of time and soil moisture. Crack networks that form in these soils act as dominant environmental controls on the movement of water, contaminants, and gases, making it important to develop fundamental understanding and tractable models of their hydrologic characteristics and behaviors. In this study, which took place primarily in the Secano Interior region of South-Central Chile, we quantified soil-water interactions across scales using a diverse and innovative dataset. These measurements were then utilized to develop a set of parsimonious multi-domain models for describing hydraulic properties and hydrological processes in shrink-swell soils. In a series of examples, we show how this model can predict porosity distributions, crack widths, saturated hydraulic conductivities, and surface runoff (i.e., overland flow) thresholds, by capturing the dominant mechanisms by which water moves through and interacts with clayey soils. Altogether, these models successfully link small-scale shrinkage/swelling behaviors with large-scale thresholds, and can be applied to describe important processes such as infiltration, overland flow development, and the preferential flow and transport of fluids and gases.

Application of neural networks and its prospect. 1. General comment on application to nuclear fusion and plasma researches

International Nuclear Information System (INIS)

Takeda, Tatsuoki

2006-01-01

The back ground of application of neutral networks to R and D of scientific field and increasing of application fields are stated. A definition of neural networks, the kinds of neural networks and functions, error back propagation, and generalization are explained. An application of multi-layer neural networks to nuclear fusion and plasma researches are described by inverse problem, interpolation, time series prediction, and computerized tomography. Some examples of researches such as MHD of plasma from magnetic probe data of fusion reactor systems, parameter prediction of distribution of the impurity spectra and the charge exchange neutral particle energy spectra, disruption prediction, and residual minimization training neural network are commented. (S.Y.)

Information Architecture Used to Manage Multi-Domain Data Analysis in Intensively Managed Landscape - Critical Zone Observatory

Science.gov (United States)

Kooper, R.; Angelo, B.; Marini, L.; Kumar, P.; Muste, M.

2016-12-01

The Intensively Managed Landscapes-Critical Zone Observatory (IML-CZO) is a multi-agency partnership that aims to understand the coevoluationary dynamics of change in the context of the landscape, soil, and biota. The Data Management aspect of IML-CZO provides data preservation and analysis for each of the scientific domains as they pursue environmental monitoring throughout the midwestern United States. Data Management is facilitated via data ingestion and storage through Clowder, an open-source, scalable data repository for organizing and analyzing data; and Geodashboard, a web application that provides exploring, querying, visualizing and downloading the data ingested into Clowder. The data collected covers many domains including geology, hydrology, and bioengineering. The data across these domains varies greatly; from real-time streams of environmental measurements to individual soil samples that are sent through a series of laboratories for analysis. All data can be uploaded to Clowder where metadata can be extracted or dynamically calculated based on the nature of the information. Geodashboard was created to provide scientists with a tool to explore data across these varying domains, and to visualize the extracted data from Clowder. Once Clowder has extracted the data, it is available for querying from a REST API for standardized and streamlined access. Users are able to explore the data on multiple axis, and are able to download data across multiple domains in a standardized format for further analysis and research. IML-CZO's Clowder has over 60 users and over 180 datasets. There are over 1.1 million extracted data points that date back to 1992, and it is continually growing.

a Multi Objective Model for Optimization of a Green Supply Chain Network

Science.gov (United States)

Paksoy, Turan; Özceylan, Eren; Weber, Gerhard-Wilhelm

2010-06-01

This study develops a model of a closed-loop supply chain (CLSC) network which starts with the suppliers and recycles with the decomposition centers. As a traditional network design, we consider minimizing the all transportation costs and the raw material purchasing costs. To pay attention for the green impacts, different transportation choices are presented between echelons according to their CO2 emissions. The plants can purchase different raw materials in respect of their recyclable ratios. The focuses of this paper are conducting the minimizing total CO2 emissions. Also we try to encourage the customers to use recyclable materials as an environmental performance viewpoint besides minimizing total costs. A multi objective linear programming model is developed via presenting a numerical example. We close the paper with recommendations for future researches.

A comprehensive multi-local-world model for complex networks

International Nuclear Information System (INIS)

Fan Zhengping; Chen Guanrong; Zhang Yunong

2009-01-01

The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li; Shihada, Basem

2014-01-01

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

A Jackson network model and threshold policy for joint optimization of energy and delay in multi-hop wireless networks

KAUST Repository

Xia, Li

2014-11-20

This paper studies the joint optimization problem of energy and delay in a multi-hop wireless network. The optimization variables are the transmission rates, which are adjustable according to the packet queueing length in the buffer. The optimization goal is to minimize the energy consumption of energy-critical nodes and the packet transmission delay throughout the network. In this paper, we aim at understanding the well-known decentralized algorithms which are threshold based from a different research angle. By using a simplified network model, we show that we can adopt the semi-open Jackson network model and study this optimization problem in closed form. This simplified network model further allows us to establish some significant optimality properties. We prove that the system performance is monotonic with respect to (w.r.t.) the transmission rate. We also prove that the threshold-type policy is optimal, i.e., when the number of packets in the buffer is larger than a threshold, transmit with the maximal rate (power); otherwise, no transmission. With these optimality properties, we develop a heuristic algorithm to iteratively find the optimal threshold. Finally, we conduct some simulation experiments to demonstrate the main idea of this paper.

Domain Engineering, A Software Engineering Discipline in Need of Research

DEFF Research Database (Denmark)

Bjørner, Dines

2000-01-01

. The aim of this paper is to advocate: that researchers study these development method components, and that universities focus their education on basing well-nigh any course on the use of formal techniques: Specification and verification, and that software engineers take heed: Start applying formal......, and these again seem more stable than software designs. Thus, almost like the universal laws of physics, it pays off to first develop theories of domains. But domain engineering, as in fact also requirements engineering, really is in need of thoroughly researched development principles, techniques and tools...... techniques. A brief example of describing stake-holder perspectives will be given - on the background of which we then proceed to survey the notions of domain intrinsics, domain support technologies, domain management & organisation, domain rules & regulations, domain human behaviour, etc. We show elsewhere...

Improving the performance of DomainDiscovery of protein domain boundary assignment using inter-domain linker index

Directory of Open Access Journals (Sweden)

Zomaya Albert Y

2006-12-01

Full Text Available Abstract Background Knowledge of protein domain boundaries is critical for the characterisation and understanding of protein function. The ability to identify domains without the knowledge of the structure – by using sequence information only – is an essential step in many types of protein analyses. In this present study, we demonstrate that the performance of DomainDiscovery is improved significantly by including the inter-domain linker index value for domain identification from sequence-based information. Improved DomainDiscovery uses a Support Vector Machine (SVM approach and a unique training dataset built on the principle of consensus among experts in defining domains in protein structure. The SVM was trained using a PSSM (Position Specific Scoring Matrix, secondary structure, solvent accessibility information and inter-domain linker index to detect possible domain boundaries for a target sequence. Results Improved DomainDiscovery is compared with other methods by benchmarking against a structurally non-redundant dataset and also CASP5 targets. Improved DomainDiscovery achieves 70% accuracy for domain boundary identification in multi-domains proteins. Conclusion Improved DomainDiscovery compares favourably to the performance of other methods and excels in the identification of domain boundaries for multi-domain proteins as a result of introducing support vector machine with benchmark_2 dataset.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

Science.gov (United States)

Taboun, Mohammed S; Brennan, Robert W

2017-09-14

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

Competitive dynamics of lexical innovations in multi-layer networks

Science.gov (United States)

Javarone, Marco Alberto

2014-04-01

We study the introduction of lexical innovations into a community of language users. Lexical innovations, i.e. new term added to people's vocabulary, plays an important role in the process of language evolution. Nowadays, information is spread through a variety of networks, including, among others, online and offline social networks and the World Wide Web. The entire system, comprising networks of different nature, can be represented as a multi-layer network. In this context, lexical innovations diffusion occurs in a peculiar fashion. In particular, a lexical innovation can undergo three different processes: its original meaning is accepted; its meaning can be changed or misunderstood (e.g. when not properly explained), hence more than one meaning can emerge in the population. Lastly, in the case of a loan word, it can be translated into the population language (i.e. defining a new lexical innovation or using a synonym) or into a dialect spoken by part of the population. Therefore, lexical innovations cannot be considered simply as information. We develop a model for analyzing this scenario using a multi-layer network comprising a social network and a media network. The latter represents the set of all information systems of a society, e.g. television, the World Wide Web and radio. Furthermore, we identify temporal directed edges between the nodes of these two networks. In particular, at each time-step, nodes of the media network can be connected to randomly chosen nodes of the social network and vice versa. In doing so, information spreads through the whole system and people can share a lexical innovation with their neighbors or, in the event they work as reporters, by using media nodes. Lastly, we use the concept of "linguistic sign" to model lexical innovations, showing its fundamental role in the study of these dynamics. Many numerical simulations have been performed to analyze the proposed model and its outcomes.

Data Aggregation in Multi-Agent Systems in the Presence of Hybrid Faults

Science.gov (United States)

Srinivasan, Satish Mahadevan

2010-01-01

Data Aggregation (DA) is a set of functions that provide components of a distributed system access to global information for purposes of network management and user services. With the diverse new capabilities that networks can provide, applicability of DA is growing. DA is useful in dealing with multi-value domain information and often requires…

Multi-objective evolutionary optimization for constructing neural networks for virtual reality visual data mining: application to geophysical prospecting.

Science.gov (United States)

Valdés, Julio J; Barton, Alan J

2007-05-01

A method for the construction of virtual reality spaces for visual data mining using multi-objective optimization with genetic algorithms on nonlinear discriminant (NDA) neural networks is presented. Two neural network layers (the output and the last hidden) are used for the construction of simultaneous solutions for: (i) a supervised classification of data patterns and (ii) an unsupervised similarity structure preservation between the original data matrix and its image in the new space. A set of spaces are constructed from selected solutions along the Pareto front. This strategy represents a conceptual improvement over spaces computed by single-objective optimization. In addition, genetic programming (in particular gene expression programming) is used for finding analytic representations of the complex mappings generating the spaces (a composition of NDA and orthogonal principal components). The presented approach is domain independent and is illustrated via application to the geophysical prospecting of caves.

Performance analysis of multi-hop wireless packet networks

Directory of Open Access Journals (Sweden)

Lim J.-T.

1997-01-01

Full Text Available In this paper, a unified analytical framework for performance analysis of multi-hop wireless packet networks is developed. The effect of coupling between the hops on the degradation of the delay-throughput characteristics and the probability of blocking is investigated. The issue of hop decoupling is addressed.

Signatures of pleiotropy, economy and convergent evolution in a domain-resolved map of human-virus protein-protein interaction networks.

Directory of Open Access Journals (Sweden)

Sara Garamszegi

Full Text Available A central challenge in host-pathogen systems biology is the elucidation of general, systems-level principles that distinguish host-pathogen interactions from within-host interactions. Current analyses of host-pathogen and within-host protein-protein interaction networks are largely limited by their resolution, treating proteins as nodes and interactions as edges. Here, we construct a domain-resolved map of human-virus and within-human protein-protein interaction networks by annotating protein interactions with high-coverage, high-accuracy, domain-centric interaction mechanisms: (1 domain-domain interactions, in which a domain in one protein binds to a domain in a second protein, and (2 domain-motif interactions, in which a domain in one protein binds to a short, linear peptide motif in a second protein. Analysis of these domain-resolved networks reveals, for the first time, significant mechanistic differences between virus-human and within-human interactions at the resolution of single domains. While human proteins tend to compete with each other for domain binding sites by means of sequence similarity, viral proteins tend to compete with human proteins for domain binding sites in the absence of sequence similarity. Independent of their previously established preference for targeting human protein hubs, viral proteins also preferentially target human proteins containing linear motif-binding domains. Compared to human proteins, viral proteins participate in more domain-motif interactions, target more unique linear motif-binding domains per residue, and contain more unique linear motifs per residue. Together, these results suggest that viruses surmount genome size constraints by convergently evolving multiple short linear motifs in order to effectively mimic, hijack, and manipulate complex host processes for their survival. Our domain-resolved analyses reveal unique signatures of pleiotropy, economy, and convergent evolution in viral

Optimal Traffic Allocation for Multi-Stream Aggregation in Heterogeneous Networks

DEFF Research Database (Denmark)

Popovska Avramova, Andrijana; Iversen, Villy Bæk

2015-01-01

nature of radio access networks are considered as important factors for performance improvement by multi-stream aggregation. Therefore, in our model, the networks are represented by different queueing systems in order to indicate networks with opposite quality of service provisioning, capacity and delay...... variations. Furthermore, services with different traffic characteristics in terms of quality of service requirements are considered. The simulation results show the advantages of our scheme with respect to efficient increase in data rate and delay performance compared to traditional schemes....

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.

Scientometrical approach of the definition of a research domain using scientific journals; Approche scientometrique de la definition d`un domaine de recherche par des revues scientifiques

Energy Technology Data Exchange (ETDEWEB)

Signogneau, A

1995-11-22

The goal of this thesis is to analyse how the academic domain of a research entity can be defined by a panel of scientific journals. The aim of this work is to contribute to the creation of information tools as a help in research management. The first part gives an analysis of the scientific journals as markers of the scientific development: the production and diffusion of scientific journals and their ``scientometrical`` analysis (references, citation reports, citation indexes etc..). In the second part, a research unit is analyzed according to its related scientific journals and to its research domain. The SPAM (Photons, Atoms and Molecules Service) of the CEA was chosen for this task (main journals and co-publications network, specialization, main topics, collaborations and competition). The OST (Observatory of Sciences and Techniques) has in charge the production of scientific and technical indicators for research operators. The third part evaluates the methods used by the OST (analyses of reviews and journals) to provide a documentary corpus, taking the topic of the environment as an example. Finally the relevance of the information products obtained is evaluated. (J.S.).

Dynamic virtual optical network embedding in spectral and spatial domains over elastic optical networks with multicore fibers

Science.gov (United States)

Zhu, Ruijie; Zhao, Yongli; Yang, Hui; Tan, Yuanlong; Chen, Haoran; Zhang, Jie; Jue, Jason P.

2016-08-01

Network virtualization can eradicate the ossification of the infrastructure and stimulate innovation of new network architectures and applications. Elastic optical networks (EONs) are ideal substrate networks for provisioning flexible virtual optical network (VON) services. However, as network traffic continues to increase exponentially, the capacity of EONs will reach the physical limitation soon. To further increase network flexibility and capacity, the concept of EONs is extended into the spatial domain. How to map the VON onto substrate networks by thoroughly using the spectral and spatial resources is extremely important. This process is called VON embedding (VONE).Considering the two kinds of resources at the same time during the embedding process, we propose two VONE algorithms, the adjacent link embedding algorithm (ALEA) and the remote link embedding algorithm (RLEA). First, we introduce a model to solve the VONE problem. Then we design the embedding ability measurement of network elements. Based on the network elements' embedding ability, two VONE algorithms were proposed. Simulation results show that the proposed VONE algorithms could achieve better performance than the baseline algorithm in terms of blocking probability and revenue-to-cost ratio.

Actor-Network Theory as a sociotechnical lens to explore the relationship of nurses and technology in practice: methodological considerations for nursing research.

Science.gov (United States)

Booth, Richard G; Andrusyszyn, Mary-Anne; Iwasiw, Carroll; Donelle, Lorie; Compeau, Deborah

2016-06-01

Actor-Network Theory is a research lens that has gained popularity in the nursing and health sciences domains. The perspective allows a researcher to describe the interaction of actors (both human and non-human) within networked sociomaterial contexts, including complex practice environments where nurses and health technology operate. This study will describe Actor-Network Theory and provide methodological considerations for researchers who are interested in using this sociotechnical lens within nursing and informatics-related research. Considerations related to technology conceptualization, levels of analysis, and sampling procedures in Actor-Network Theory based research are addressed. Finally, implications for future nursing research within complex environments are highlighted. © 2015 John Wiley & Sons Ltd.

Analysis of Few-Mode Multi-Core Fiber Splice Behavior Using an Optical Vector Network Analyzer

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, Jose Manuel Delgado; Klaus, Werner

2017-01-01

The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively and negativ......The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively...

An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks

International Nuclear Information System (INIS)

Cao Jinde

2004-01-01

In this Letter, the domain of attraction of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are estimated by means of matrix measure and comparison principle. A new estimation is given for the domain of attraction of memory patterns and exponential convergence rate. These results can be used for the evaluation of fault-tolerance capability and the synthesis procedures for Hopfield continuous feedback associative memory neural networks

The multi-domain protein Np95 connects DNA methylation and histone modification.

Science.gov (United States)

Rottach, Andrea; Frauer, Carina; Pichler, Garwin; Bonapace, Ian Marc; Spada, Fabio; Leonhardt, Heinrich

2010-04-01

DNA methylation and histone modifications play a central role in the epigenetic regulation of gene expression and cell differentiation. Recently, Np95 (also known as UHRF1 or ICBP90) has been found to interact with Dnmt1 and to bind hemimethylated DNA, indicating together with genetic studies a central role in the maintenance of DNA methylation. Using in vitro binding assays we observed a weak preference of Np95 and its SRA (SET- and Ring-associated) domain for hemimethylated CpG sites. However, the binding kinetics of Np95 in living cells was not affected by the complete loss of genomic methylation. Investigating further links with heterochromatin, we could show that Np95 preferentially binds histone H3 N-terminal tails with trimethylated (H3K9me3) but not acetylated lysine 9 via a tandem Tudor domain. This domain contains three highly conserved aromatic amino acids that form an aromatic cage similar to the one binding H3K9me3 in the chromodomain of HP1ss. Mutations targeting the aromatic cage of the Np95 tandem Tudor domain (Y188A and Y191A) abolished specific H3 histone tail binding. These multiple interactions of the multi-domain protein Np95 with hemimethylated DNA and repressive histone marks as well as with DNA and histone methyltransferases integrate the two major epigenetic silencing pathways.

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

Science.gov (United States)

Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs

KAUST Repository

Yasin Yazicioǧlu, A.; Egerstedt, Magnus; Shamma, Jeff S.

2015-01-01

Multi-Agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-Agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m ϵ [k+k ] 2. Accordingly, the agents improve the robustness of the network while maintaining a similar number of links as the initial configuration by locally adding or removing some edges. © 2015 IEEE.

Formation of Robust Multi-Agent Networks through Self-Organizing Random Regular Graphs

KAUST Repository

Yasin Yazicioǧlu, A.

2015-11-25

Multi-Agent networks are often modeled as interaction graphs, where the nodes represent the agents and the edges denote some direct interactions. The robustness of a multi-Agent network to perturbations such as failures, noise, or malicious attacks largely depends on the corresponding graph. In many applications, networks are desired to have well-connected interaction graphs with relatively small number of links. One family of such graphs is the random regular graphs. In this paper, we present a decentralized scheme for transforming any connected interaction graph with a possibly non-integer average degree of k into a connected random m-regular graph for some m ϵ [k+k ] 2. Accordingly, the agents improve the robustness of the network while maintaining a similar number of links as the initial configuration by locally adding or removing some edges. © 2015 IEEE.

Robust exponential stability and domains of attraction in a class of interval neural networks

International Nuclear Information System (INIS)

Yang Xiaofan; Liao Xiaofeng; Bai Sen; Evans, David J

2005-01-01

This paper addresses robust exponential stability as well as domains of attraction in a class of interval neural networks. A sufficient condition for an equilibrium point to be exponentially stable is established. And an estimate on the domains of attraction of exponentially stable equilibrium points is presented. Both the condition and the estimate are formulated in terms of the parameter intervals, the neurons' activation functions and the equilibrium point. Hence, they are easily checkable. In addition, our results neither depend on monotonicity of the activation functions nor on coupling conditions between the neurons. Consequently, these results are of practical importance in evaluating the performance of interval associative memory networks

Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel information

Science.gov (United States)

Mabu, Shingo; Kido, Shoji; Hashimoto, Noriaki; Hirano, Yasushi; Kuremoto, Takashi

2018-02-01

This research proposes a multi-channel deep convolutional neural network (DCNN) for computer-aided diagnosis (CAD) that classifies normal and abnormal opacities of diffuse lung diseases in Computed Tomography (CT) images. Because CT images are gray scale, DCNN usually uses one channel for inputting image data. On the other hand, this research uses multi-channel DCNN where each channel corresponds to the original raw image or the images transformed by some preprocessing techniques. In fact, the information obtained only from raw images is limited and some conventional research suggested that preprocessing of images contributes to improving the classification accuracy. Thus, the combination of the original and preprocessed images is expected to show higher accuracy. The proposed method realizes region of interest (ROI)-based opacity annotation. We used lung CT images taken in Yamaguchi University Hospital, Japan, and they are divided into 32 × 32 ROI images. The ROIs contain six kinds of opacities: consolidation, ground-glass opacity (GGO), emphysema, honeycombing, nodular, and normal. The aim of the proposed method is to classify each ROI into one of the six opacities (classes). The DCNN structure is based on VGG network that secured the first and second places in ImageNet ILSVRC-2014. From the experimental results, the classification accuracy of the proposed method was better than the conventional method with single channel, and there was a significant difference between them.

A cooperative game framework for detecting overlapping communities in social networks

Science.gov (United States)

Jonnalagadda, Annapurna; Kuppusamy, Lakshmanan

2018-02-01

Community detection in social networks is a challenging and complex task, which received much attention from researchers of multiple domains in recent years. The evolution of communities in social networks happens merely due to the self-interest of the nodes. The interesting feature of community structure in social networks is the multi membership of the nodes resulting in overlapping communities. Assuming the nodes of the social network as self-interested players, the dynamics of community formation can be captured in the form of a game. In this paper, we propose a greedy algorithm, namely, Weighted Graph Community Game (WGCG), in order to model the interactions among the self-interested nodes of the social network. The proposed algorithm employs the Shapley value mechanism to discover the inherent communities of the underlying social network. The experimental evaluation on the real-world and synthetic benchmark networks demonstrates that the performance of the proposed algorithm is superior to the state-of-the-art overlapping community detection algorithms.

Experimental demonstration of an OpenFlow based software-defined optical network employing packet, fixed and flexible DWDM grid technologies on an international multi-domain testbed.

Science.gov (United States)

Channegowda, M; Nejabati, R; Rashidi Fard, M; Peng, S; Amaya, N; Zervas, G; Simeonidou, D; Vilalta, R; Casellas, R; Martínez, R; Muñoz, R; Liu, L; Tsuritani, T; Morita, I; Autenrieth, A; Elbers, J P; Kostecki, P; Kaczmarek, P

2013-03-11

Software defined networking (SDN) and flexible grid optical transport technology are two key technologies that allow network operators to customize their infrastructure based on application requirements and therefore minimizing the extra capital and operational costs required for hosting new applications. In this paper, for the first time we report on design, implementation & demonstration of a novel OpenFlow based SDN unified control plane allowing seamless operation across heterogeneous state-of-the-art optical and packet transport domains. We verify and experimentally evaluate OpenFlow protocol extensions for flexible DWDM grid transport technology along with its integration with fixed DWDM grid and layer-2 packet switching.

SYNTHESIS AND REDUCED LOGIC GATE REALIZATION OF MULTI-VALUED LOGIC FUNCTIONS USING NEURAL NETWORK DEPLOYMENT ALGORITHM

Directory of Open Access Journals (Sweden)

A. K. CHOWDHURY

2016-02-01

Full Text Available In this paper an evolutionary technique for synthesizing Multi-Valued Logic (MVL functions using Neural Network Deployment Algorithm (NNDA is presented. The algorithm is combined with back-propagation learning capability and neural MVL operators. This research article is done to observe the anomalistic characteristics of MVL neural operators and their role in synthesis. The advantages of NNDA-MVL algorithm is demonstrated with realization of synthesized many valued functions with lesser MVL operators. The characteristic feature set consists of MVL gate count, network link count, network propagation delay and accuracy achieved in training. In brief, this paper depicts an effort of reduced network size for synthesized MVL functions. Trained MVL operators improve the basic architecture by reducing MIN gate and interlink connection by 52.94% and 23.38% respectively.

Keystone Business Models for Network Security Processors

OpenAIRE

Arthur Low; Steven Muegge

2013-01-01

Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor...

Multi-hop localization algorithm based on grid-scanning for wireless sensor networks.

Science.gov (United States)

Wan, Jiangwen; Guo, Xiaolei; Yu, Ning; Wu, Yinfeng; Feng, Renjian

2011-01-01

For large-scale wireless sensor networks (WSNs) with a minority of anchor nodes, multi-hop localization is a popular scheme for determining the geographical positions of the normal nodes. However, in practice existing multi-hop localization methods suffer from various kinds of problems, such as poor adaptability to irregular topology, high computational complexity, low positioning accuracy, etc. To address these issues in this paper, we propose a novel Multi-hop Localization algorithm based on Grid-Scanning (MLGS). First, the factors that influence the multi-hop distance estimation are studied and a more realistic multi-hop localization model is constructed. Then, the feasible regions of the normal nodes are determined according to the intersection of bounding square rings. Finally, a verifiably good approximation scheme based on grid-scanning is developed to estimate the coordinates of the normal nodes. Additionally, the positioning accuracy of the normal nodes can be improved through neighbors' collaboration. Extensive simulations are performed in isotropic and anisotropic networks. The comparisons with some typical algorithms of node localization confirm the effectiveness and efficiency of our algorithm.

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

Science.gov (United States)

Brennan, Robert W.

2017-01-01

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network. PMID:28906452

Pilot-Assisted Channel Estimation for Orthogonal Multi-Carrier DS-CDMA with Frequency-Domain Equalization

Science.gov (United States)

Shima, Tomoyuki; Tomeba, Hiromichi; Adachi, Fumiyuki

Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of time-domain spreading and orthogonal frequency division multiplexing (OFDM). In orthogonal MC DS-CDMA, the frequency diversity gain can be obtained by applying frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion to a block of OFDM symbols and can improve the bit error rate (BER) performance in a severe frequency-selective fading channel. FDE requires an accurate estimate of the channel gain. The channel gain can be estimated by removing the pilot modulation in the frequency domain. In this paper, we propose a pilot-assisted channel estimation suitable for orthogonal MC DS-CDMA with FDE and evaluate, by computer simulation, the BER performance in a frequency-selective Rayleigh fading channel.

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...

Multi-dimensional discovery of biomarker and phenotype complexes

Directory of Open Access Journals (Sweden)

Huang Kun

2010-10-01

Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

Network Analysis of Rodent Transcriptomes in Spaceflight

Science.gov (United States)

Ramachandran, Maya; Fogle, Homer; Costes, Sylvain

2017-01-01

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

Multi-frequency complex network from time series for uncovering oil-water flow structure.

Science.gov (United States)

Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

2015-02-04

Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

Design and construction of multi research reactor

International Nuclear Information System (INIS)

1985-05-01

This is the report about design and construction of multi research reactor, which introduces the purpose and necessity of the project, business contents, plan of progress of project and budget for the project. There are three appendixes about status of research reactor in other country, a characteristic of research reactor, three charts about evaluation, process and budget for the multi research reactor and three drawings for the project.

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.

Fused Regression for Multi-source Gene Regulatory Network Inference.

Directory of Open Access Journals (Sweden)

Kari Y Lam

2016-12-01

Full Text Available Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method's utility in learning from data collected on different experimental platforms.

Research, Boundaries, and Policy in Networked Learning

DEFF Research Database (Denmark)

This book presents cutting-edge, peer reviewed research on networked learning organized by three themes: policy in networked learning, researching networked learning, and boundaries in networked learning. The "policy in networked learning" section explores networked learning in relation to policy...... networks, spaces of algorithmic governance and more. The "boundaries in networked learning" section investigates frameworks of students' digital literacy practices, among other important frameworks in digital learning. Lastly, the "research in networked learning" section delves into new research methods...

Multiplex multivariate recurrence network from multi-channel signals for revealing oil-water spatial flow behavior.

Science.gov (United States)

Gao, Zhong-Ke; Dang, Wei-Dong; Yang, Yu-Xuan; Cai, Qing

2017-03-01

The exploration of the spatial dynamical flow behaviors of oil-water flows has attracted increasing interests on account of its challenging complexity and great significance. We first technically design a double-layer distributed-sector conductance sensor and systematically carry out oil-water flow experiments to capture the spatial flow information. Based on the well-established recurrence network theory, we develop a novel multiplex multivariate recurrence network (MMRN) to fully and comprehensively fuse our double-layer multi-channel signals. Then we derive the projection networks from the inferred MMRNs and exploit the average clustering coefficient and the spectral radius to quantitatively characterize the nonlinear recurrent behaviors related to the distinct flow patterns. We find that these two network measures are very sensitive to the change of flow states and the distributions of network measures enable to uncover the spatial dynamical flow behaviors underlying different oil-water flow patterns. Our method paves the way for efficiently analyzing multi-channel signals from multi-layer sensor measurement system.

The International Network of Obstetric Survey Systems (INOSS): benefits of multi-country studies of severe and uncommon maternal morbidities.

Science.gov (United States)

Knight, Marian

2014-02-01

The International Network of Obstetric Survey Systems (INOSS) is a multi-country collaboration formed to facilitate studies of uncommon and severe complications of pregnancy and childbirth. Collaborations such as INOSS offer many benefits in the study of rare complications. The use of uniform case definitions, common datasets, specifically collected detailed data and prospectively agreed comparative and combined analyses all add to the validity of studies and their utility to guide policy and clinical practice and hence improve the quality of care. Such multi-national collaborations allow for the conduct of robust studies less subject to many of the biases attributed to typical observational studies. For very rare conditions such collaborations may provide the only route to providing high quality evidence to guide practice. Clinicians and researchers conducting studies into rare and severe complications should consider working through a network such as INOSS to maximize the value of their research. © 2013 Nordic Federation of Societies of Obstetrics and Gynecology.

Spatial aliasing and distortion of energy distribution in the wave vector domain under multi-spacecraft measurements

Directory of Open Access Journals (Sweden)

Y. Narita

2009-08-01

Full Text Available Aliasing is a general problem in the analysis of any measurements that make sampling at discrete points. Sampling in the spatial domain results in a periodic pattern of spectra in the wave vector domain. This effect is called spatial aliasing, and it is of particular importance for multi-spacecraft measurements in space. We first present the theoretical background of aliasing problems in the frequency domain and generalize it to the wave vector domain, and then present model calculations of spatial aliasing. The model calculations are performed for various configurations of the reciprocal vectors and energy spectra or distribution that are placed at different positions in the wave vector domain, and exhibit two effects on aliasing. One is weak aliasing, in which the true spectrum is distorted because of non-uniform aliasing contributions in the Brillouin zone. It is demonstrated that the energy distribution becomes elongated in the shortest reciprocal lattice vector direction in the wave vector domain. The other effect is strong aliasing, in which aliases have a significant contribution in the Brillouin zone and the energy distribution shows a false peak. These results give a caveat in multi-spacecraft data analysis in that spectral anisotropy obtained by a measurement has in general two origins: (1 natural and physical origins like anisotropy imposed by a mean magnetic field or a flow direction; and (2 aliasing effects that are imposed by the configuration of the measurement array (or the set of reciprocal vectors. This manuscript also discusses a possible method to estimate aliasing contributions in the Brillouin zone based on the measured spectrum and to correct the spectra for aliasing.

Classifying medical relations in clinical text via convolutional neural networks.

Science.gov (United States)

He, Bin; Guan, Yi; Dai, Rui

2018-05-16

Deep learning research on relation classification has achieved solid performance in the general domain. This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. Copyright © 2018. Published by Elsevier B.V.

Rescuing policy in tourism network research

DEFF Research Database (Denmark)

Dredge, Dianne

2018-01-01

Networks provide a powerful lens to understand complex relational entanglements that are transforming social, economic and political life. Through a discussion of the various streams of network research in tourism, this paper argues that policy matters run across and throughout these strands....... Rather than arguing for increased interest in tourism policy network research as a separate subfield, the paper argues for deeper theoretical engagement with the policy dimension in tourism network research. Researchers adopting a network ontology could gain considerable insights and open up new lines...

Multi purpose research reactor

International Nuclear Information System (INIS)

Raina, V.K.; Sasidharan, K.; Sengupta, Samiran; Singh, Tej

2006-01-01

At present Dhruva and Cirus reactors provide the majority of research reactor based facilities to cater to the various needs of a vast pool of researchers in the field of material sciences, physics, chemistry, bio sciences, research and development work for nuclear power plants and production of radio isotopes. With a view to further consolidate and expand the scope of research and development in nuclear and allied sciences, a new 20 MWt multi purpose research reactor is being designed. This paper describes some of the design features and safety aspects of this reactor

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks

Directory of Open Access Journals (Sweden)

Shalin Savalia

2018-05-01

Full Text Available The electrocardiogram (ECG plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP and convolution neural network (CNN. The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The ECG databases accessible at PhysioBank.com and kaggle.com were used for training, testing, and validation of the MLP and CNN algorithms. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia. The accuracy of the algorithm surpasses the performance of the current algorithms that have been developed by other cardiologists in both sensitivity and precision.

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks.

Science.gov (United States)

Savalia, Shalin; Emamian, Vahid

2018-05-04

The electrocardiogram (ECG) plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP) and convolution neural network (CNN). The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The ECG databases accessible at PhysioBank.com and kaggle.com were used for training, testing, and validation of the MLP and CNN algorithms. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia. The accuracy of the algorithm surpasses the performance of the current algorithms that have been developed by other cardiologists in both sensitivity and precision.

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

Science.gov (United States)

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

The multi-domain protein Np95 connects DNA methylation and histone modification

Science.gov (United States)

Rottach, Andrea; Frauer, Carina; Pichler, Garwin; Bonapace, Ian Marc; Spada, Fabio; Leonhardt, Heinrich

2010-01-01