WorldWideScience

Sample records for generation networks

  1. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    When it comes to discussing the future of electronic communication, social networking is the buzzword. The Internet has become a platform where new social networks emerge and the Internet it itself support the more traditional computer supported communication. The way users build and verifies...... different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...

  2. Next Generation Virtual Private Networks

    Science.gov (United States)

    2003-10-01

    setup and teardown of IPSec tunnels between trusted participants, without requiring intervention from the network administrator. Finally, another...Internet 2 between participating sites, which required debugging some problems found in the campus network infrastructures. The AA- VPN was...requirements, was accomplished by the generation VPN that achieves end-to-end optimization of the network path based upon the requirements of individual

  3. Generating random networks and graphs

    CERN Document Server

    Coolen, Ton; Roberts, Ekaterina

    2017-01-01

    This book supports researchers who need to generate random networks, or who are interested in the theoretical study of random graphs. The coverage includes exponential random graphs (where the targeted probability of each network appearing in the ensemble is specified), growth algorithms (i.e. preferential attachment and the stub-joining configuration model), special constructions (e.g. geometric graphs and Watts Strogatz models) and graphs on structured spaces (e.g. multiplex networks). The presentation aims to be a complete starting point, including details of both theory and implementation, as well as discussions of the main strengths and weaknesses of each approach. It includes extensive references for readers wishing to go further. The material is carefully structured to be accessible to researchers from all disciplines while also containing rigorous mathematical analysis (largely based on the techniques of statistical mechanics) to support those wishing to further develop or implement the theory of rand...

  4. Conception of Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Slavko Šarić

    2004-11-01

    tool for the realization ofadditional se1vices and for enabling the control in NGN. Theproblem of JP routers for NGN has also been mentioned, aswell as the importance of the new core generation of optical networks.The conceptual framework of NGN is based today onIP/ATM transport technology, which is at this level of developmentgenerally accepted as the optimal transp011 solution. The problem of addressing caused by the insufficient address spaceof Ipv4 has been stressed and the solution of that problem hasbeen anticipated with the introduction of lpv6 technology,which, due to its complexity and high costs, would be graduallyintroduced by a dual approach into the system.The differentiating elements of NGN in relation to the existingnetworks have been specially pointed out. The modulm;that is, plane nature of the NGN conception in relation to thevertical and hierarchical conception of PSTN has beenstressed, as well as the pdvileges that this open conception offerswhen choosing the equipment of the highest quality by differentmanufacturers. Both existing, voice (TDM and data(NGN (ATM/IP, networks will act parallel in the next yearsuntil new solutions to NGN will have been introduced.

  5. Traffic Management for Next Generation Transport Networks

    DEFF Research Database (Denmark)

    Yu, Hao

    Video services are believed to be prevalent in the next generation transport networks. The popularity of these bandwidth-intensive services, such as Internet Protocol Television (IPTV), online gaming, and Videoon- Demand (VoD), are currently driving the network service providers to upgrade...... their network capacities. However, in order to provide more advanced video services than simply porting the traditional television services to the network, the service provider needs to do more than just augment the network capacity. Advanced traffic management capability is one of the relevant abilities...... required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...

  6. Editorial: Next Generation Access Networks

    Science.gov (United States)

    Ruffini, Marco; Cincotti, Gabriella; Pizzinat, Anna; Vetter, Peter

    2015-12-01

    Over the past decade we have seen an increasing number of operators deploying Fibre-to-the-home (FTTH) solutions in access networks, in order to provide home users with a much needed network access upgrade, to support higher peak rates, higher sustained rates and a better and more uniform broadband coverage of the territory.

  7. Optical Subsystems for Next Generation Access Networks

    DEFF Research Database (Denmark)

    Lazaro, J.A; Polo, V.; Schrenk, B.

    2011-01-01

    Recent optical technologies are providing higher flexibility to next generation access networks: on the one hand, providing progressive FTTx and specifically FTTH deployment, progressively shortening the copper access network; on the other hand, also opening fixed-mobile convergence solutions...... in next generation PON architectures. It is provided an overview of the optical subsystems developed for the implementation of the proposed NG-Access Networks....

  8. Generating Seismograms with Deep Neural Networks

    Science.gov (United States)

    Krischer, L.; Fichtner, A.

    2017-12-01

    The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of

  9. Optimizing the next generation optical access networks

    DEFF Research Database (Denmark)

    Amaya Fernández, Ferney Orlando; Soto, Ana Cardenas; Tafur Monroy, Idelfonso

    2009-01-01

    Several issues in the design and optimization of the next generation optical access network (NG-OAN) are presented. The noise, the distortion and the fiber optic nonlinearities are considered to optimize the video distribution link in a passive optical network (PON). A discussion of the effect...

  10. Achieving universal access to next generation networks

    DEFF Research Database (Denmark)

    Falch, Morten; Henten, Anders

    The paper examines investment dimensions of next generation networks in a universal service perspective in a European context. The question is how new network infrastructures for getting access to communication, information and entertainment services in the present and future information society...

  11. Gender Differences in Cross-Generation Networks.

    Science.gov (United States)

    Troll, Lillian E.

    1987-01-01

    Members of cross-generational networks, which are primarily among kin, are likely to share basic values or to avoid issues that might cause conflict. Mother-daughter bonds are both the strongest through life and the most complex, linking household units into modified extended family networks. Critical conceptual methodological problems abound.…

  12. Membership generation using multilayer neural network

    Science.gov (United States)

    Kim, Jaeseok

    1992-01-01

    There has been intensive research in neural network applications to pattern recognition problems. Particularly, the back-propagation network has attracted many researchers because of its outstanding performance in pattern recognition applications. In this section, we describe a new method to generate membership functions from training data using a multilayer neural network. The basic idea behind the approach is as follows. The output values of a sigmoid activation function of a neuron bear remarkable resemblance to membership values. Therefore, we can regard the sigmoid activation values as the membership values in fuzzy set theory. Thus, in order to generate class membership values, we first train a suitable multilayer network using a training algorithm such as the back-propagation algorithm. After the training procedure converges, the resulting network can be treated as a membership generation network, where the inputs are feature values and the outputs are membership values in the different classes. This method allows fairly complex membership functions to be generated because the network is highly nonlinear in general. Also, it is to be noted that the membership functions are generated from a classification point of view. For pattern recognition applications, this is highly desirable, although the membership values may not be indicative of the degree of typicality of a feature value in a particular class.

  13. Next Generation Reliable Transport Networks

    DEFF Research Database (Denmark)

    Zhang, Jiang

    the wavelength and fiber assignment problem is proposed and implemented for avionic optical transport networks. Simulation results give out resource consumptions and prove the efficiency of the proposed mechanisms. Finally, a Home Environment Service Knowledge Management system is proposed. Through ontology...... technologies, a knowledge base is constructed to represent the whole information of a home environment. By applying the reasoner tool, the proposed system manages to keep the consistency in a home environment and helps all software configure and update procedures across multiple vendors....

  14. Young generation network: facing the future

    International Nuclear Information System (INIS)

    Berk, R.

    1997-01-01

    The future of the nuclear industry lies with the young generation. That's why in 1995, ENS supported the creation of the Young Generation Network (YGN). The YGN aims to fulfill the needs and interests of young people working in the nuclear business by organizing special programs with interesting opportunities and activities. (author)

  15. Generating confidence intervals on biological networks

    Directory of Open Access Journals (Sweden)

    Stumpf Michael PH

    2007-11-01

    Full Text Available Abstract Background In the analysis of networks we frequently require the statistical significance of some network statistic, such as measures of similarity for the properties of interacting nodes. The structure of the network may introduce dependencies among the nodes and it will in general be necessary to account for these dependencies in the statistical analysis. To this end we require some form of Null model of the network: generally rewired replicates of the network are generated which preserve only the degree (number of interactions of each node. We show that this can fail to capture important features of network structure, and may result in unrealistic significance levels, when potentially confounding additional information is available. Methods We present a new network resampling Null model which takes into account the degree sequence as well as available biological annotations. Using gene ontology information as an illustration we show how this information can be accounted for in the resampling approach, and the impact such information has on the assessment of statistical significance of correlations and motif-abundances in the Saccharomyces cerevisiae protein interaction network. An algorithm, GOcardShuffle, is introduced to allow for the efficient construction of an improved Null model for network data. Results We use the protein interaction network of S. cerevisiae; correlations between the evolutionary rates and expression levels of interacting proteins and their statistical significance were assessed for Null models which condition on different aspects of the available data. The novel GOcardShuffle approach results in a Null model for annotated network data which appears better to describe the properties of real biological networks. Conclusion An improved statistical approach for the statistical analysis of biological network data, which conditions on the available biological information, leads to qualitatively different results

  16. Design Guidelines for New Generation Network Architecture

    Science.gov (United States)

    Harai, Hiroaki; Fujikawa, Kenji; Kafle, Ved P.; Miyazawa, Takaya; Murata, Masayuki; Ohnishi, Masaaki; Ohta, Masataka; Umezawa, Takeshi

    Limitations are found in the recent Internet because a lot of functions and protocols are patched to the original suite of layered protocols without considering global optimization. This reveals that end-to-end argument in the original Internet was neither sufficient for the current societal network and nor for a sustainable network of the future. In this position paper, we present design guidelines for a future network, which we call the New Generation Network, which provides the inclusion of diverse human requirements, reliable connection between the real-world and virtual network space, and promotion of social potentiality for human emergence. The guidelines consist of the crystal synthesis, the reality connection, and the sustainable & evolutional guidelines.

  17. NASA's Next Generation Space Geodesy Network

    Science.gov (United States)

    Desai, S. D.; Gross, R. S.; Hilliard, L.; Lemoine, F. G.; Long, J. L.; Ma, C.; McGarry, J. F.; Merkowitz, S. M.; Murphy, D.; Noll, C. E.; hide

    2012-01-01

    NASA's Space Geodesy Project (SGP) is developing a prototype core site for a next generation Space Geodetic Network (SGN). Each of the sites in this planned network co-locate current state-of-the-art stations from all four space geodetic observing systems, GNSS, SLR, VLBI, and DORIS, with the goal of achieving modern requirements for the International Terrestrial Reference Frame (ITRF). In particular, the driving ITRF requirements for this network are 1.0 mm in accuracy and 0.1 mm/yr in stability, a factor of 10-20 beyond current capabilities. Development of the prototype core site, located at NASA's Geophysical and Astronomical Observatory at the Goddard Space Flight Center, started in 2011 and will be completed by the end of 2013. In January 2012, two operational GNSS stations, GODS and GOON, were established at the prototype site within 100 m of each other. Both stations are being proposed for inclusion into the IGS network. In addition, work is underway for the inclusion of next generation SLR and VLBI stations along with a modern DORIS station. An automated survey system is being developed to measure inter-technique vectorties, and network design studies are being performed to define the appropriate number and distribution of these next generation space geodetic core sites that are required to achieve the driving ITRF requirements. We present the status of this prototype next generation space geodetic core site, results from the analysis of data from the established geodetic stations, and results from the ongoing network design studies.

  18. BGen: A UML Behavior Network Generator Tool

    Science.gov (United States)

    Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

    2010-01-01

    BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

  19. Micro-generation network connection (renewables)

    Energy Technology Data Exchange (ETDEWEB)

    Thornycroft, J.; Russell, T.; Curran, J.

    2003-07-01

    The drive to reduce emissions of carbon dioxide will result in an increase in the number of small generation units seeking connection to the electric power distribution network. The objectives of this study were to consider connection issues relating to micro-generation from renewables and their integration into the UK distribution network. The document is divided into two sections. The first section describes the present system which includes input from micro-generation, the technical impacts and the financial considerations. The second part discusses technical, financial and governance options for the future. A summary of preferred options and recommendations is given. The study was carried out by the Halcrow Group Ltd under contract to the DTI.

  20. Biology Question Generation from a Semantic Network

    Science.gov (United States)

    Zhang, Lishan

    Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students' learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student's current competence so that a suitable question could be selected based on the student's previous performance. A between-subjects experiment with 42 participants was performed, where half of the participants studied with adaptive selected questions and the rest studied with mal-adaptive order of questions. Both groups significantly improved their test scores, and the participants in adaptive group registered larger learning gains than participants in the control group. To explore the possibility of generating rich instructional feedback for machine-generated questions, a question-paragraph mapping task was identified. Given a set of questions and a list of paragraphs for a textbook, the goal of the task was to map the related paragraphs to each question. An algorithm was developed whose performance was comparable to human annotators. A multiple-choice question with high quality distractors (incorrect answers) can be pedagogically valuable as well as being much easier to grade than open-response questions. Thus, an algorithm was developed to generate good distractors for multiple-choice questions. The machine-generated multiple-choice questions were compared to human-generated questions in terms of three measures: question difficulty, question discrimination and distractor usefulness. By recruiting 200 participants from

  1. Automatic Generation of Network Protocol Gateways

    DEFF Research Database (Denmark)

    Bromberg, Yérom-David; Réveillère, Laurent; Lawall, Julia

    2009-01-01

    for describing protocol behaviors, message structures, and the gateway logic.  Z2z includes a compiler that checks essential correctness properties and produces efficient code. We have used z2z to develop a number of gateways, including SIP to RTSP, SLP to UPnP, and SMTP to SMTP via HTTP, involving a range......The emergence of networked devices in the home has made it possible to develop applications that control a variety of household functions. However, current devices communicate via a multitude of incompatible protocols, and thus gateways are needed to translate between them.  Gateway construction......, however, requires an intimate knowledge of the relevant protocols and a substantial understanding of low-level network programming, which can be a challenge for many application programmers. This paper presents a generative approach to gateway construction, z2z, based on a domain-specific language...

  2. Network integration of distributed power generation

    Science.gov (United States)

    Dondi, Peter; Bayoumi, Deia; Haederli, Christoph; Julian, Danny; Suter, Marco

    The world-wide move to deregulation of the electricity and other energy markets, concerns about the environment, and advances in renewable and high efficiency technologies has led to major emphasis being placed on the use of small power generation units in a variety of forms. The paper reviews the position of distributed generation (DG, as these small units are called in comparison with central power plants) with respect to the installation and interconnection of such units with the classical grid infrastructure. In particular, the status of technical standards both in Europe and USA, possible ways to improve the interconnection situation, and also the need for decisions that provide a satisfactory position for the network operator (who remains responsible for the grid, its operation, maintenance and investment plans) are addressed.

  3. Cascading Generative Adversarial Networks for Targeted

    KAUST Repository

    Hamdi, Abdullah

    2018-04-09

    Abundance of labelled data played a crucial role in the recent developments in computer vision, but that faces problems like scalability and transferability to the wild. One alternative approach is to utilize the data without labels, i.e. unsupervised learning, in learning valuable information and put it in use to tackle vision problems. Generative Adversarial Networks (GANs) have gained momentum for their ability to model image distributions in unsupervised manner. They learn to emulate the training set and that enables sampling from that domain and using the knowledge learned for useful applications. Several methods proposed enhancing GANs, including regularizing the loss with some feature matching. We seek to push GANs beyond the data in the training and try to explore unseen territory in the image manifold. We first propose a new regularizer for GAN based on K-Nearest Neighbor (K-NN) selective feature matching to a target set Y in high-level feature space, during the adversarial training of GAN on the base set X, and we call this novel model K-GAN. We show that minimizing the added term follows from cross-entropy minimization between the distributions of GAN and set Y. Then, we introduce a cascaded framework for GANs that try to address the task of imagining a new distribution that combines the base set X and target set Y by cascading sampling GANs with translation GANs, and we dub the cascade of such GANs as the Imaginative Adversarial Network (IAN). Several cascades are trained on a collected dataset Zoo-Faces and generated innovative samples are shown, including from K-GAN cascade. We conduct an objective and subjective evaluation for different IAN setups in the addressed task of generating innovative samples and we show the effect of regularizing GAN on different scores. We conclude with some useful applications for these IANs, like multi-domain manifold traversing.

  4. The guitar chord-generating algorithm based on complex network

    Science.gov (United States)

    Ren, Tao; Wang, Yi-fan; Du, Dan; Liu, Miao-miao; Siddiqi, Awais

    2016-02-01

    This paper aims to generate chords for popular songs automatically based on complex network. Firstly, according to the characteristics of guitar tablature, six chord networks of popular songs by six pop singers are constructed and the properties of all networks are concluded. By analyzing the diverse chord networks, the accompaniment regulations and features are shown, with which the chords can be generated automatically. Secondly, in terms of the characteristics of popular songs, a two-tiered network containing a verse network and a chorus network is constructed. With this network, the verse and chorus can be composed respectively with the random walk algorithm. Thirdly, the musical motif is considered for generating chords, with which the bad chord progressions can be revised. This method can make the accompaniments sound more melodious. Finally, a popular song is chosen for generating chords and the new generated accompaniment sounds better than those done by the composers.

  5. System and method for generating a relationship network

    Science.gov (United States)

    Franks, Kasian [Kensington, CA; Myers, Cornelia A [St. Louis, MO; Podowski, Raf M [Pleasant Hill, CA

    2011-07-26

    A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

  6. Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks

    CERN Document Server

    Santi, Paolo

    2012-01-01

    Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and

  7. Analysis on Voltage Profile of Distribution Network with Distributed Generation

    Science.gov (United States)

    Shao, Hua; Shi, Yujie; Yuan, Jianpu; An, Jiakun; Yang, Jianhua

    2018-02-01

    Penetration of distributed generation has some impacts on a distribution network in load flow, voltage profile, reliability, power loss and so on. After the impacts and the typical structures of the grid-connected distributed generation are analyzed, the back/forward sweep method of the load flow calculation of the distribution network is modelled including distributed generation. The voltage profiles of the distribution network affected by the installation location and the capacity of distributed generation are thoroughly investigated and simulated. The impacts on the voltage profiles are summarized and some suggestions to the installation location and the capacity of distributed generation are given correspondingly.

  8. Deep Convolutional Generative Adversarial Network for Procedural 3D Landscape Generation Based on DEM

    DEFF Research Database (Denmark)

    Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig

    2018-01-01

    This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM...

  9. Building next-generation converged networks theory and practice

    CERN Document Server

    Pathan, Al-Sakib Khan

    2013-01-01

    Supplying a comprehensive introduction to next-generation networks, Building Next-Generation Converged Networks: Theory and Practice strikes a balance between how and why things work and how to make them work. It compiles recent advancements along with basic issues from the wide range of fields related to next generation networks. Containing the contributions of 56 industry experts and researchers from 16 different countries, the book presents relevant theoretical frameworks and the latest research. It investigates new technologies such as IPv6 over Low Power Wireless Personal Area Network (6L

  10. Transient stability analysis of a distribution network with distributed generators

    NARCIS (Netherlands)

    Xyngi, I.; Ishchenko, A.; Popov, M.; Van der Sluis, L.

    2009-01-01

    This letter describes the transient stability analysis of a 10-kV distribution network with wind generators, microturbines, and CHP plants. The network being modeled in Matlab/Simulink takes into account detailed dynamic models of the generators. Fault simulations at various locations are

  11. CO-GENERATION AND OPERATING NETWORK CELLS

    DEFF Research Database (Denmark)

    Nielsen, John Eli

    2008-01-01

    In Denmark several thousands of generators are connected to the distribution system (10 kV and 0.4 kV). The production from these generators many times exceeds the load. The generators can be divided into two types, Wind turbines and CHP generators. These generators have one thing in common......, the power system they are connected to, has never been designed to accommodate so many generators. In Denmark we now expect a third type of generators: the microgenerators. This time we want to be prepared. Denmark therefore now participates in a lot of research and full scale demonstration projects. A key...

  12. Centralized Networks to Generate Human Body Motions.

    Science.gov (United States)

    Vakulenko, Sergei; Radulescu, Ovidiu; Morozov, Ivan; Weber, Andres

    2017-12-14

    We consider continuous-time recurrent neural networks as dynamical models for the simulation of human body motions. These networks consist of a few centers and many satellites connected to them. The centers evolve in time as periodical oscillators with different frequencies. The center states define the satellite neurons' states by a radial basis function (RBF) network. To simulate different motions, we adjust the parameters of the RBF networks. Our network includes a switching module that allows for turning from one motion to another. Simulations show that this model allows us to simulate complicated motions consisting of many different dynamical primitives. We also use the model for learning human body motion from markers' trajectories. We find that center frequencies can be learned from a small number of markers and can be transferred to other markers, such that our technique seems to be capable of correcting for missing information resulting from sparse control marker settings.

  13. Wild cricket social networks show stability across generations.

    Science.gov (United States)

    Fisher, David N; Rodríguez-Muñoz, Rolando; Tregenza, Tom

    2016-07-27

    A central part of an animal's environment is its interactions with conspecifics. There has been growing interest in the potential to capture these interactions in the form of a social network. Such networks can then be used to examine how relationships among individuals affect ecological and evolutionary processes. However, in the context of selection and evolution, the utility of this approach relies on social network structures persisting across generations. This is an assumption that has been difficult to test because networks spanning multiple generations have not been available. We constructed social networks for six annual generations over a period of eight years for a wild population of the cricket Gryllus campestris. Through the use of exponential random graph models (ERGMs), we found that the networks in any given year were able to predict the structure of networks in other years for some network characteristics. The capacity of a network model of any given year to predict the networks of other years did not depend on how far apart those other years were in time. Instead, the capacity of a network model to predict the structure of a network in another year depended on the similarity in population size between those years. Our results indicate that cricket social network structure resists the turnover of individuals and is stable across generations. This would allow evolutionary processes that rely on network structure to take place. The influence of network size may indicate that scaling up findings on social behaviour from small populations to larger ones will be difficult. Our study also illustrates the utility of ERGMs for comparing networks, a task for which an effective approach has been elusive.

  14. Plan Generation and Evaluation Using Action Networks

    National Research Council Canada - National Science Library

    Peot, Mark

    2003-01-01

    ... from potential actions of the plan. Methods used to accomplish these results included the use of Action Networks, and development of a suite of analysis tools in support of the AFRL Campaign Assessment Tool...

  15. 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...... (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...... with Domain Path Vector based protocol that compute the domain level path dynamically for the further inter-domain path routing mechanism Backward Recursive Path Computation (BRPC). Furthermore, several algorithms are proposed to compute the domain-level path under more than one constrains (multi...

  16. Phoebus: Network Middleware for Next-Generation Network Computing

    Energy Technology Data Exchange (ETDEWEB)

    Martin Swany

    2012-06-16

    The Phoebus project investigated algorithms, protocols, and middleware infrastructure to improve end-to-end performance in high speed, dynamic networks. The Phoebus system essentially serves as an adaptation point for networks with disparate capabilities or provisioning. This adaptation can take a variety of forms including acting as a provisioning agent across multiple signaling domains, providing transport protocol adaptation points, and mapping between distributed resource reservation paradigms and the optical network control plane. We have successfully developed the system and demonstrated benefits. The Phoebus system was deployed in Internet2 and in ESnet, as well as in GEANT2, RNP in Brazil and over international links to Korea and Japan. Phoebus is a system that implements a new protocol and associated forwarding infrastructure for improving throughput in high-speed dynamic networks. It was developed to serve the needs of large DOE applications on high-performance networks. The idea underlying the Phoebus model is to embed Phoebus Gateways (PGs) in the network as on-ramps to dynamic circuit networks. The gateways act as protocol translators that allow legacy applications to use dedicated paths with high performance.

  17. Do-it-yourself networks: a novel method of generating weighted networks.

    Science.gov (United States)

    Shanafelt, D W; Salau, K R; Baggio, J A

    2017-11-01

    Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social-ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.

  18. Migration of optical core network to next generation networks - Carrier Grade Ethernet Optical Transport Network

    Science.gov (United States)

    Glamočanin, D.

    2017-05-01

    In order to maintain the continuity of the telecom operators’ network construction, while monitoring development needs, increasing customers’ demands and application of technological improvements, it is necessary to migrate optical transport core network to the next generation networks - Carrier Grade Ethernet Optical Transport Network (OTN CE). The primary objective of OTN CE is to realize an environment that is based solely on the switching in the optical domain, i.e. the realization of transparent optical networks and optical switching to the second layer of ISO / OSI model. The realization of such a network provides opportunities for further development of existing, but also technologically more demanding, new services. It is also a prerequisite to provide higher scalability, reliability, security and quality of QoS service, as well as prerequisites for the establishment of SLA (Service Level Agreement) for existing services, especially traffic in real time. This study aims to clarify the proposed model, which has the potential to be eventually adjusted in accordance with new scientific knowledge in this field as well as market requirements.

  19. Innovation and networking among entrepreneurs across generations of Asian tigers

    DEFF Research Database (Denmark)

    Vang, Jan; Jensen, Kent Wickstrøm; Schøtt, Thomas

    2017-01-01

    entrepreneurship monitor (GEM) data, this paper aims at reducing this research gap by conducting an analysis of the generational differences between the tiger economies entrepreneurs in respect to their innovative performance, their inclination to network and the importance of the quality of the network...... strategies. The literature has, however, not paid much systematic attention to generational differences in connection to moving from an imitation-based strategy towards an innovation-based strategy. This is especially the case concerning the entrepreneurial companies. On the basis of the global...... for their innovative performance. The paper finds a significant difference in the quality of the networks and its impact on innovation across the tiger generations....

  20. Convergence of wireless, wireline, and photonics next generation networks

    CERN Document Server

    Iniewski, Krzysztof

    2010-01-01

    Filled with illustrations and practical examples from industry, this book provides a brief but comprehensive introduction to the next-generation wireless networks that will soon replace more traditional wired technologies. Written by a mixture of top industrial experts and key academic professors, it is the only book available that covers both wireless networks (such as wireless local area and personal area networks) and optical networks (such as long-haul and metropolitan networks) in one volume. It gives engineers and engineering students the necessary knowledge to meet challenges of next-ge

  1. Probing next Generation Portuguese Academic Network

    Science.gov (United States)

    Friacas, Carlos; Massano, Emanuel; Domingues, Monica; Veiga, Pedro

    2008-01-01

    Purpose: The purpose of this article is to provide several viewpoints about monitoring aspects related to recent deployments of a new technology (IPv6). Design/methodology/approach: Several views and domains were used, with a common point: the Portuguese research and education network (RCTS). Findings: A significant amount of work is yet to be…

  2. The Operational Risk Assessment for Distribution Network with Distributed Generations

    Science.gov (United States)

    Hua, Xie; Yaqi, Wu; Yifan, Wang; Qian, Sun; Jianwei, Ma

    2017-05-01

    Distribution network is an important part of the power system and is connected to the consumers directly. Many distributed generations that have discontinuous output power are connected in the distribution networks, which may cause adverse impact to the distribution network. Therefore, to ensure the security and reliability of distribution network with numerous distributed generations, the risk analysis is necessary for this kind of distribution networks. After study of stochastic load flow algorithm, this paper applies it in the static security risk assessment. The wind and photovoltaic output probabilistic model are built. The voltage over-limit is chosen to calculate the risk indicators. As a case study, the IEEE 33 system is simulated for analyzing impact of distributed generations on system risk in the proposed method.

  3. Physical Configuration of the Next Generation Home Network

    Science.gov (United States)

    Terada, Shohei; Kakishima, Yu; Hanawa, Dai; Oguchi, Kimio

    The number of broadband users is rapidly increasing worldwide. Japan already has over 10 million FTTH users. Another trend is the rapid digitalization of home electrical equipment e. g. digital cameras and hard disc recorders. These trends will encourage the emergence of the next generation home network. In this paper, we introduce the next generation home network image and describe the five domains into which home devices can be classified. We then clarify the optimum medium with which to configure the network given the requirements imposed by the home environment. Wiring cable lengths for three network topologies are calculated. The results gained from the next generation home network implemented on the first phase testbed are shown. Finally, our conclusions are given.

  4. Efficient Video Streaming Scheme for Next Generations of Mobile Networks

    Directory of Open Access Journals (Sweden)

    Majdi Ashibani

    2005-04-01

    Full Text Available Video streaming over next generations of mobile networks has undergone enormous development recently due to the continuing growth in wireless communication, especially since the emergence of 3G wireless networks. The new generations of wireless networks pose many challenges, including supporting quality of service over wireless communication links. This is due to the time-varying characteristics of wireless channel. Therefore, a more flexible and efficient bandwidth allocation scheme is needed. This paper is a part of ongoing work to come up with a more robust scheme that is capable of rapidly adapting to changes in network conditions. The proposed scheme focuses on the wireless part of the network, providing high quality video service and better utilization of network resources.

  5. Harmonics: Generation and Suppression in AC System Networks ...

    African Journals Online (AJOL)

    However, reactive power flow in electrical networks has adverse effects depending on their magnitude and the nature of the supply network. How these harmonics are generated by nonlinear loads and the means by which they can be kept low are the focus of this paper. Keywords: non-linear loads, harmonics, reactive ...

  6. Distributed network generation based on preferential attachment in ABS

    NARCIS (Netherlands)

    K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank)

    2017-01-01

    textabstractGeneration of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the

  7. Penetration tests in next generation networks

    Science.gov (United States)

    Rezac, Filip; Voznak, Miroslav

    2012-06-01

    SIP proxy server is without any doubts centerpiece of any SIP IP telephony infrastructure. It also often provides other services than those related to VoIP traffic. These softswitches are, however, very often become victims of attacks and threats coming from public networks. The paper deals with a system that we developed as an analysis and testing tool to verify if the target SIP server is adequately secured and protected against any real threats. The system is designed as an open-source application, thus allowing independent access and is fully extensible to other test modules.

  8. Modeling of regional warehouse network generation

    Directory of Open Access Journals (Sweden)

    Popov Pavel Vladimirovich

    2016-08-01

    Full Text Available One of the factors that has a significant impact on the socio-economic development of the Russian Federation’s regions is the logistics infrastructure. It provides integrated transportation and distribution service of material flows. One of the main elements of logistics infrastructure is a storage infrastructure, which includes distribution center, distribution-and-sortout and sortout warehouses. It is the most expedient to place distribution center in the vicinity of the regional center. One of the tasks of the distribution network creation within the regions of the Russian Federation is to determine the location, capacity and number of stores. When determining regional network location of general purpose warehouses methodological approaches to solving the problems of location of production and non-production can be used which depend on various economic factors. The mathematical models for solving relevant problems are the deployment models. However, the existing models focus on the dimensionless power storage. The purpose of the given work is to develop a model to determine the optimal location of general-purpose warehouses on the Russian Federation area. At the first stage of the work, the authors assess the main economic indicators influencing the choice of the location of general purpose warehouses. An algorithm for solving the first stage, based on ABC, discriminant and cluster analysis were proposed by the authors in earlier papers. At the second stage the specific locations of general purpose warehouses and their power is chosen to provide the cost minimization for the construction and subsequent maintenance of warehouses and transportation heterogeneous products. In order to solve this problem the authors developed a mathematical model that takes into account the possibility of delivery in heterogeneous goods from suppliers and manufacturers in the distribution and storage sorting with specified set of capacities. The model allows

  9. Generating English Discourse from Semantic Networks.

    Science.gov (United States)

    Simmons, R. F.; Slocum, Jonathan

    The system described in this report is designed for use as a computational tool that allows a linguist to develop and study methods for generating surface strings from an underlying semantic structure. Initial findings with regard to form-determiners (such as voice, form, tense, and mood), some rules for embedding sentences, and some attention to…

  10. Scholarly publishing for the network generation

    Directory of Open Access Journals (Sweden)

    Liz Allen

    2015-03-01

    Full Text Available The increasing momentum towards opening up various dimensions of society is discussed in this article, and the authors consider whether ‘open’ is now an unstoppable force for change in the world. Various topics within research communication, such as open access (OA and post-publication peer review (PPPR, are considered from the perspective of the authors as participants in the scholarly communication community of more than 20 years’ standing, with both for- and non-profit credentials. The authors explore how harnessing the wisdom of the crowd in rating everyday services manifests itself by improving our ability to make choices in our daily lives. They explain how this network effect can be applied to scholarly communication and how it provided some of the inspiration behind the launch of ScienceOpen, the research and OA publishing network, in May 2014. This publishing platform is then described as an example of democratizing publishing. The increasing importance of software development in publishing and the need for stand-alone expertise in this space (as opposed to a publisher-centric approach is also discussed. Finally, the authors consider the role that the impact factor and the promotion/tenure system play in holding back progress in scholarly communication and they highlight the efforts of early career researchers to break the stalemate by taking ‘open’ pledges.

  11. Comparing Generative Adversarial Network Techniques for Image Creation and Modification

    NARCIS (Netherlands)

    Pieters, Mathijs; Wiering, Marco

    2018-01-01

    Generative adversarial networks (GANs) have demonstrated to be successful at generating realistic real-world images. In this paper we compare various GAN techniques, both supervised and unsupervised. The effects on training stability of different objective functions are compared. We add an encoder

  12. WDCC Metadata Generation with GeoNetwork

    Science.gov (United States)

    Ramthun, Hans; Lautenschlager, Michael; Winter, Hans-Hermann

    2010-05-01

    Earth system science data like modeling output data are described by metadata. At the WDCC (World Data Center of Climate) the data and metadata are stored inside the CERA (Climate and Environmental Retrieval and Archive) relational database. To fill in the describing metadata several types of XML documents are used to upload data into the database. GeoNetwork is an Ajax based web framework, which offers a wide range of XML data handling for search and update and is especially designed to meet the ISO19115/19139 standard. This framework was extended by the schema's which allow create and update CERA upload XML records. An upload function is also included as well as a connection to the local LDAP (Lightweight Directory Access Protocol) for authentication. Keywords: metadata, WDCC, CERA, Ajax

  13. Transmission Network Expansion Planning Considering Desired Generation Security

    Directory of Open Access Journals (Sweden)

    Samaneh GOLESTANI

    2014-02-01

    Full Text Available Transmission Network Expansion Planning (TNEP is an important part of power system planning in both conventional and new structured power market. Its goal is to minimize the network construction and operational cost while satisfying the demand increase, considering technical and economic conditions. Planning algorithm in this paper consisted of two stages. The former specifies highly uncertain lines and probability of congestion, considering desired generation security level (e.g. N-2 generation security level. The latter determines the optimal expansion capacity of existing lines. Splitting required capacity for reinforcement of weak lines due to desired generation security level simplifies the TNEP problem. In addition, it monitors the impact of generation uncertainty on transmission lines. Simulation results of the proposed idea are presented for IEEE-RTS-24bus network.

  14. Patch layout generation by detecting feature networks

    KAUST Repository

    Cao, Yuanhao

    2015-02-01

    The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines several key ingredients, including feature detection, feature filtering, feature curve extension, patch subdivision and boundary smoothing. Our framework is able to compute patch layouts through concave features as previous approaches, but also able to generate nice layouts through smoothing regions. We demonstrate the effectiveness of our framework by comparing with the state-of-the-art methods.

  15. Mobility management techniques for the next-generation wireless networks

    Science.gov (United States)

    Sun, Junzhao; Howie, Douglas P.; Sauvola, Jaakko J.

    2001-10-01

    The tremendous demands from social market are pushing the booming development of mobile communications faster than ever before, leading to plenty of new advanced techniques emerging. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Mobility management is an important issue in the area of mobile communications, which can be best solved at the network layer. One of the key features of the next generation wireless networks is all-IP infrastructure. This paper discusses the mobility management schemes for the next generation mobile networks through extending IP's functions with mobility support. A global hierarchical framework model for the mobility management of wireless networks is presented, in which the mobility management is divided into two complementary tasks: macro mobility and micro mobility. As the macro mobility solution, a basic principle of Mobile IP is introduced, together with the optimal schemes and the advances in IPv6. The disadvantages of the Mobile IP on solving the micro mobility problem are analyzed, on the basis of which three main proposals are discussed as the micro mobility solutions for mobile communications, including Hierarchical Mobile IP (HMIP), Cellular IP, and Handoff-Aware Wireless Access Internet Infrastructure (HAWAII). A unified model is also described in which the different micro mobility solutions can coexist simultaneously in mobile networks.

  16. Thermalnet: a Deep Convolutional Network for Synthetic Thermal Image Generation

    Science.gov (United States)

    Kniaz, V. V.; Gorbatsevich, V. S.; Mizginov, V. A.

    2017-05-01

    Deep convolutional neural networks have dramatically changed the landscape of the modern computer vision. Nowadays methods based on deep neural networks show the best performance among image recognition and object detection algorithms. While polishing of network architectures received a lot of scholar attention, from the practical point of view the preparation of a large image dataset for a successful training of a neural network became one of major challenges. This challenge is particularly profound for image recognition in wavelengths lying outside the visible spectrum. For example no infrared or radar image datasets large enough for successful training of a deep neural network are available to date in public domain. Recent advances of deep neural networks prove that they are also capable to do arbitrary image transformations such as super-resolution image generation, grayscale image colorisation and imitation of style of a given artist. Thus a natural question arise: how could be deep neural networks used for augmentation of existing large image datasets? This paper is focused on the development of the Thermalnet deep convolutional neural network for augmentation of existing large visible image datasets with synthetic thermal images. The Thermalnet network architecture is inspired by colorisation deep neural networks.

  17. Deep Convolutional Generative Adversarial Network for Procedural 3D Landscape Generation Based on DEM

    DEFF Research Database (Denmark)

    Wulff-Jensen, Andreas; Rant, Niclas Nerup; Møller, Tobias Nordvig

    2017-01-01

    This paper proposes a novel framework for improving procedural generation of 3D landscapes using machine learning. We utilized a Deep Convolutional Generative Adversarial Network (DC-GAN) to generate heightmaps. The network was trained on a dataset consisting of Digital Elevation Maps (DEM......) of the alps. During map generation, the batch size and learning rate were optimized for the most efficient and satisfying map production. The diversity of the final output was tested against Perlin noise using Mean Square Error [1] and Structure Similarity Index [2]. Perlin noise is especially interesting...

  18. Generation of clusters in complex dynamical networks via pinning control

    International Nuclear Information System (INIS)

    Li Kezan; Fu Xinchu; Small, Michael

    2008-01-01

    Many real-world networks show community structure, i.e., groups (or clusters) of nodes that have a high density of links within them but with a lower density of links between them. In this paper, by applying feedback injections to a fraction of network nodes, various clusters are synchronized independently according to the community structure generated by the group partition of the network (cluster synchronization). This control is achieved by pinning (i.e. applying linear feedback control) to a subset of the network nodes. Those pinned nodes are selected not randomly but according to the topological structure of communities of a given network. Specifically, for a given group partition of a network, those nodes with direct connections between groups must be pinned in order to achieve cluster synchronization. Both the local stability and global stability of cluster synchronization are investigated. Taking the tree-shaped network and the most modular network as two particular examples, we illustrate in detail how the pinning strategy influences the generation of clusters. The simulations verify the efficiency of the pinning schemes used in this paper

  19. A Vector Network Analyzer Based on Pulse Generators

    Directory of Open Access Journals (Sweden)

    B. Schulte

    2005-01-01

    Full Text Available A fast four channel network analyzer is introduced to measure S-parameters in a frequency range from 10MHz to 3GHz. The signal generation for this kind of analyzer is based on pulse generators, which are realized with bipolar transistors. The output signal of the transistor is differentiated and two short pulses, a slow and a fast one, with opposite polarities are generated. The slow pulse is suppressed with a clipping network. Thus the generation of very short electrical pulses with a duration of about 100ps is possible. The structure of the following network analyzer is similar to the structure of a conventional four channel network analyzer. All four pulses, which contain the high frequency information of the device under test, are evaluated after the digitalization of intermediate frequencies. These intermediate frequencies are generated with sampling mixers. The recorded data is evaluated with a special analysis technique, which is based on a Fourier transformation. The calibration techniques used are the same as for conventional four channel network analyzers, no new calibration techniques need to be developed.

  20. Flexible Transmission Network Planning Considering the Impacts of Distributed Generation

    OpenAIRE

    Junhua Zhao; John Foster

    2010-01-01

    The restructuring of global power industries has introduced a number of challenges, such as conflicting planning objectives and increasing uncertainties,to transmission network planners. During the recent past, a number of distributed generation technologies also reached a stage allowing large scale implementation, which will profoundly influence the power industry, as well as the practice of transmission network expansion. In the new market environment, new approaches are needed to meet the ...

  1. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

    OpenAIRE

    Radford, Alec; Metz, Luke; Chintala, Soumith

    2015-01-01

    In recent years, supervised learning with convolutional networks (CNNs) has seen huge adoption in computer vision applications. Comparatively, unsupervised learning with CNNs has received less attention. In this work we hope to help bridge the gap between the success of CNNs for supervised learning and unsupervised learning. We introduce a class of CNNs called deep convolutional generative adversarial networks (DCGANs), that have certain architectural constraints, and demonstrate that they ar...

  2. Multicriteria Reconfiguration of Distribution Network with Distributed Generation

    OpenAIRE

    Voropai, N. I.; Bat-Undraal, B.

    2012-01-01

    The paper addresses the problem of multicriteria reconfiguration of distribution network with distributed generation according to the criterion of minimum power loss under normal conditions and the criterion of power supply reliability under postemergency conditions. Efficient heuristic and multicriteria methods are used to solve the problem including advanced ant colony algorithm for minimum loss reconfiguration of distribution network, the sorting-out algorithm of cell formation for island ...

  3. Formal Specification Based Automatic Test Generation for Embedded Network Systems

    Directory of Open Access Journals (Sweden)

    Eun Hye Choi

    2014-01-01

    Full Text Available Embedded systems have become increasingly connected and communicate with each other, forming large-scaled and complicated network systems. To make their design and testing more reliable and robust, this paper proposes a formal specification language called SENS and a SENS-based automatic test generation tool called TGSENS. Our approach is summarized as follows: (1 A user describes requirements of target embedded network systems by logical property-based constraints using SENS. (2 Given SENS specifications, test cases are automatically generated using a SAT-based solver. Filtering mechanisms to select efficient test cases are also available in our tool. (3 In addition, given a testing goal by the user, test sequences are automatically extracted from exhaustive test cases. We’ve implemented our approach and conducted several experiments on practical case studies. Through the experiments, we confirmed the efficiency of our approach in design and test generation of real embedded air-conditioning network systems.

  4. Toward green next-generation passive optical networks

    Science.gov (United States)

    Srivastava, Anand

    2015-01-01

    Energy efficiency has become an increasingly important aspect of designing access networks, due to both increased concerns for global warming and increased network costs related to energy consumption. Comparing access, metro, and core, the access constitutes a substantial part of the per subscriber network energy consumption and is regarded as the bottleneck for increased network energy efficiency. One of the main opportunities for reducing network energy consumption lies in efficiency improvements of the customer premises equipment. Access networks in general are designed for low utilization while supporting high peak access rates. The combination of large contribution to overall network power consumption and low Utilization implies large potential for CPE power saving modes where functionality is powered off during periods of idleness. Next-generation passive optical network, which is considered one of the most promising optical access networks, has notably matured in the past few years and is envisioned to massively evolve in the near future. This trend will increase the power requirements of NG-PON and make it no longer coveted. This paper will first provide a comprehensive survey of the previously reported studies on tackling this problem. A novel solution framework is then introduced, which aims to explore the maximum design dimensions and achieve the best possible power saving while maintaining the QoS requirements for each type of service.

  5. Robust network topologies for generating switch-like cellular responses.

    Directory of Open Access Journals (Sweden)

    Najaf A Shah

    2011-06-01

    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  6. Generation of a Social Network Graph by Using Apache Spark

    Directory of Open Access Journals (Sweden)

    Y. A. Belov

    2016-01-01

    Full Text Available We plan to create a method of clustering a social network graph. For testing the method there is a need to generate a graph similar in structure to existing social networks. The article presents an algorithm for the graph distributed generation. We took into account basic properties such as power-law distribution of the users communities number, dense intersections of the social networks and others. This algorithm also considers the problems that are present in similar works of other authors, for example, the multiple edges problem in the generation process. A special feature of the created algorithm is the implementation depending on the communities number parameter rather than on the connected users number as it is done in other works. It is connected with a peculiarity of progressing the existing social network structure. There are properties of its graph in the paper. We described a table containing the variables needed for the algorithm. A step-by-step generation algorithm was compiled. Appropriate mathematical parameters were calculated for it. A generation is performed in a distributed way by Apache Spark framework. It was described in detail how the tasks division with the help of this framework runs. The Erdos-Renyi model for random graphs is used in the algorithm. It is the most suitable and easy one to implement. The main advantages of the created method are the small amount of resources in comparison with other similar generators and execution speed. Speed is achieved through distributed work and the fact that in any time network users have their own unique numbers and are ordered by these numbers, so there is no need to sort them out. The designed algorithm will promote not only the efficient clustering method creation. It can be useful in other development areas connected, for example, with the social networks search engines.

  7. Embedded generation connection incentives for distribution network operators

    Energy Technology Data Exchange (ETDEWEB)

    Williams, P.; Andrews, S.

    2002-07-01

    This is the final report with respect to work commissioned by the Department of Trade and Industry (DTI) as part of the New and Renewable Energy Programme into incentives for distribution network operators (DNOs) for the connection of embedded generation. This report, which incorporates the contents of the interim report submitted in February 2002, considers the implications of changes in the structure and regulation in the UK electricity industry on the successful technical and commercial integrated of embedded generation into distribution networks. The report examines: the obligations of public electricity suppliers (PESs); current DNO practices regarding the connection of embedded generation; the changes introduced by the Utilities Act 2000, including the impact of new obligations placed on DNOs on the connection of embedded generation and the requirements of the new Electricity Distribution Standard Licence conditions; and problems and prospects for DNO incentives.

  8. Application of Generative Adversarial Networks (GANs) to jet images

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    https://arxiv.org/abs/1701.05927 We provide a bridge between generative modeling in the Machine Learning community and simulated physical processes in High Energy Particle Physics by applying a novel Generative Adversarial Network (GAN) architecture to the production of jet images -- 2D representations of energy depositions from particles interacting with a calorimeter. We propose a simple architecture, the Location-Aware Generative Adversarial Network, that learns to produce realistic radiation patterns from simulated high energy particle collisions. The pixel intensities of GAN-generated images faithfully span over many orders of magnitude and exhibit the desired low-dimensional physical properties (i.e., jet mass, n-subjettiness, etc.). We shed light on limitations, and provide a novel empirical validation of image quality and validity of GAN-produced simulations of the natural world. This work provides a base for further explorations of GANs for use in faster simulation in High Energy Particle Physics.

  9. Loss optimization in distribution networks with distributed generation

    DEFF Research Database (Denmark)

    Pokhrel, Basanta Raj; Nainar, Karthikeyan; Bak-Jensen, Birgitte

    2017-01-01

    in highly active distribution grids. This issue is tackled by formulating a hybrid loss optimization problem and solved using the Interior Point Method. Sensitivity analysis is used to identify the optimum location of storage units. Different scenarios of reconfiguration, storage and distributed generation......This paper presents a novel power loss minimization approach in distribution grids considering network reconfiguration, distributed generation and storage installation. Identification of optimum configuration in such scenario is one of the main challenges faced by distribution system operators...

  10. Creating Turbulent Flow Realizations with Generative Adversarial Networks

    Science.gov (United States)

    King, Ryan; Graf, Peter; Chertkov, Michael

    2017-11-01

    Generating valid inflow conditions is a crucial, yet computationally expensive, step in unsteady turbulent flow simulations. We demonstrate a new technique for rapid generation of turbulent inflow realizations that leverages recent advances in machine learning for image generation using a deep convolutional generative adversarial network (DCGAN). The DCGAN is an unsupervised machine learning technique consisting of two competing neural networks that are trained against each other using backpropagation. One network, the generator, tries to produce samples from the true distribution of states, while the discriminator tries to distinguish between true and synthetic samples. We present results from a fully-trained DCGAN that is able to rapidly draw random samples from the full distribution of possible inflow states without needing to solve the Navier-Stokes equations, eliminating the costly process of spinning up inflow turbulence. This suggests a new paradigm in physics informed machine learning where the turbulence physics can be encoded in either the discriminator or generator. Finally, we also propose additional applications such as feature identification and subgrid scale modeling.

  11. Generating private recommendations in a social trust network

    NARCIS (Netherlands)

    Erkin, Z.; Veugen, P.J.M.; Lagendijk, R.L.

    2011-01-01

    Recommender systems have become increasingly important in e-commerce as they can guide customers with finding personalized services and products. A variant of recommender systems that generates recommendations from a set of trusted people is recently getting more attention in social networks.

  12. Converged Wireless Networking and Optimization for Next Generation Services

    Directory of Open Access Journals (Sweden)

    J. Rodriguez

    2010-01-01

    Full Text Available The Next Generation Network (NGN vision is tending towards the convergence of internet and mobile services providing the impetus for new market opportunities in combining the appealing services of internet with the roaming capability of mobile networks. However, this convergence does not go far enough, and with the emergence of new coexistence scenarios, there is a clear need to evolve the current architecture to provide cost-effective end-to-end communication. The LOOP project, a EUREKA-CELTIC driven initiative, is one piece in the jigsaw by helping European industry to sustain a leading role in telecommunications and manufacturing of high-value products and machinery by delivering pioneering converged wireless networking solutions that can be successfully demonstrated. This paper provides an overview of the LOOP project and the key achievements that have been tunneled into first prototypes for showcasing next generation services for operators and process manufacturers.

  13. Tri-generation in urban networks; Trigeneration en reseau urbain

    Energy Technology Data Exchange (ETDEWEB)

    Malahieude, J.M. [Trigen Energy Corp., New-York (United States)

    1996-12-31

    The concepts of tri-generation (simultaneous production of heat, electric power and refrigerating energy) and thermal energy distribution networks, are presented. The different components of the tri-generation system from Trigen Energy Corp. are ammonia as a refrigerant for the production of cooled water, screw compressors, gas turbines and an induction motor-generator in order to optimize the combined gas turbine and compressor utilization. The energy efficiency and pollution reduction of the system are evaluated; the system has been enhanced through re-powering and post combustion

  14. Overcoming barriers to scheduling embedded generation to support distribution networks

    Energy Technology Data Exchange (ETDEWEB)

    Wright, A.J.; Formby, J.R.

    2000-07-01

    Current scheduling of embedded generation for distribution in the UK is limited and patchy. Some DNOs actively schedule while others do none. The literature on the subject is mainly about accommodating volatile wind output, and optimising island systems, for both cost of supply and network stability. The forthcoming NETA will lower prices, expose unpredictable generation to imbalance markets and could introduce punitive constraint payments on DNOs, but at the same time create a dynamic market for both power and ancillary services from embedded generators. Most renewable generators either run as base load (e.g. waste ) or according to the vagaries of the weather (e.g. wind, hydro), so offer little scope for scheduling other than 'off'. CHP plant is normally heat- led for industrial processes or building needs, but supplementary firing or thermal storage often allow considerable scope for scheduling. Micro-CHP with thermal storage could provide short-term scheduling, but tends to be running anyway during the evening peak. Standby generation appears to be ideal for scheduling, but in practice operators may be unwilling to run parallel with the network, and noise and pollution problems may preclude frequent operation. Statistical analysis can be applied to calculate the reliability of several generators compared to one; with a large number of generators such as micro-CHP reliability of a proportion of load is close to unity. The type of communication for generation used will depend on requirements for bandwidth, cost, reliability and whether it is bundled with other services. With high levels of deeply embedded, small-scale generation using induction machines, voltage control and black start capability will become important concerns on 11 kV and LV networks. This will require increased generation monitoring and remote control of switchgear. Examples of cost benefits from scheduling are given, including deferred reinforcement, increased exports on non

  15. Address Translation Problems in IMS Based Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Balazs Godor

    2006-01-01

    Full Text Available The development of packed based multimedia networks reached a turning point when the ITU-T and the ETSIhave incorporated the IMS to the NGN. With the fast development of mobile communication more and more services andcontent are available. In contrast with fix network telephony both the services and the devices are personalized in the “mobileworld”. Services, known from the Internet - like e-mail, chat, browsing, presence, etc. – are already available via mobiledevices as well. The IMS originally wanted to exploit both the benefits of mobile networks and the fancy services of theInternet. But today it is already more than that. IMS is the core of the next generation telecommunication networks and abasis for fix-mobile convergent services. The fact however that IMS was originally a “mobile” standard, where IPv6 was notoddity generated some problems for the fix networks, where IPv4 is used. In this article I give an overview of these problemsand mention some solutions as well.

  16. Generative modelling of regulated dynamical behavior in cultured neuronal networks

    Science.gov (United States)

    Volman, Vladislav; Baruchi, Itay; Persi, Erez; Ben-Jacob, Eshel

    2004-04-01

    The spontaneous activity of cultured in vitro neuronal networks exhibits rich dynamical behavior. Despite the artificial manner of their construction, the networks’ activity includes features which seemingly reflect the action of underlying regulating mechanism rather than arbitrary causes and effects. Here, we study the cultured networks dynamical behavior utilizing a generative modelling approach. The idea is to include the minimal required generic mechanisms to capture the non-autonomous features of the behavior, which can be reproduced by computer modelling, and then, to identify the additional features of biotic regulation in the observed behavior which are beyond the scope of the model. Our model neurons are composed of soma described by the two Morris-Lecar dynamical variables (voltage and fraction of open potassium channels), with dynamical synapses described by the Tsodyks-Markram three variables dynamics. The model neuron satisfies our self-consistency test: when fed with data recorded from a real cultured networks, it exhibits dynamical behavior very close to that of the networks’ “representative” neuron. Specifically, it shows similar statistical scaling properties (approximated by similar symmetric Lévy distribution with finite mean). A network of such M-L elements spontaneously generates (when weak “structured noise” is added) synchronized bursting events (SBEs) similar to the observed ones. Both the neuronal statistical scaling properties within the bursts and the properties of the SBEs time series show generative (a new discussed concept) agreement with the recorded data. Yet, the model network exhibits different structure of temporal variations and does not recover the observed hierarchical temporal ordering, unless fed with recorded special neurons (with much higher rates of activity), thus indicating the existence of self-regulation mechanisms. It also implies that the spontaneous activity is not simply noise-induced. Instead, the

  17. A method of generating moving objects on the constrained network

    Science.gov (United States)

    Zhang, Jie; Ma, Linbing

    2008-10-01

    Moving objects databases have become an important research issue in recent years. In case large real data sets acquired by GPS, PDA or other mobile devices are not available, benchmarking requires the generation of artificial data sets following the real-world behavior of spatial objects that change their locations over time. In the field of spatiotemporal databases, a number of publications about the generation of test data are restricted to few papers. However, most of the existing moving-object generators assume a fixed and often unrealistic mobility model and do not consider several important characteristics of the network. In this paper, a new generator is presented to solve these problems. First of all, the network is realistic transportation network of Guangzhou. Second, the observation records of vehicle flow are available. Third, in order to simplify the whole simulation process and to help us visualize the process, this framework is built under .Net development platform of Microsoft and ArcEngine9 environment.

  18. Neural network based control of Doubly Fed Induction Generator in wind power generation

    Science.gov (United States)

    Barbade, Swati A.; Kasliwal, Prabha

    2012-07-01

    To complement the other types of pollution-free generation wind energy is a viable option. Previously wind turbines were operated at constant speed. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. In this paper the phasor model of DFIG is used. This paper presents a study of a doubly fed induction generator driven by a wind turbine connected to the grid, and controlled by artificial neural network ANN controller. The behaviour of the system is shown with PI control, and then as controlled by ANN. The effectiveness of the artificial neural network controller is compared to that of a PI controller. The SIMULINK/MATLAB simulation for Doubly Fed Induction Generator and corresponding results and waveforms are displayed.

  19. An artificial neural network model for periodic trajectory generation

    Science.gov (United States)

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

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

  20. Prioritizing Signaling Information Transmission in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Jasmina Baraković

    2011-01-01

    Full Text Available Next generation transport network is characterized by the use of in-band signaling, where Internet Protocol (IP packets carrying signaling or media information are mixed in transmission. Since transport resources are limited, when any segment of access or core network is congested, IP packets carrying signaling information may be discarded. As a consequence, it may be impossible to implement reachability and quality of service (QoS. Since present approaches are insufficient to completely address this problem, a novel approach is proposed, which is based on prioritizing signaling information transmission. To proof the concept, a simulation study was performed using Network Simulator version 2 (ns-2 and independently developed Session Initiation Protocol (SIP module. The obtained results were statistically processed using Statistical Package for the Social Sciences (SPSS version 15.0. Summarizing our research results, several issues are identified for future work.

  1. Gender roles in social network sites from generation Y

    Directory of Open Access Journals (Sweden)

    F. Javier Rondan-Cataluña

    2017-12-01

    Full Text Available One of the fundamental and most commonly used communication tools by the generation Y or Millennials are online social networks. The first objective of this study is to model the effects that exercise social participation, community integration and trust in community satisfaction, as an antecedent of routinization. Besides, we propose as a second objective checking if gender roles proposed to underlie the different behaviors that develop social network users. An empirical study was carried out on a sample of 1,448 undergraduate students that are SNS users from Generation Y. First, we applied a structural equation modeling approach to test the proposed model. Second, we followed a methodology using a scale of masculinity and femininity to categorize the sample obtaining three groups: feminine, masculine, and androgynous.

  2. Towards Third-Generation Living Lab Networks in Cities

    Directory of Open Access Journals (Sweden)

    Seppo Leminen

    2017-11-01

    Full Text Available Many cities engage in diverse experimentation, innovation, and development activities with a broad variety of environments and stakeholders to the benefit of citizens, companies, municipalities, and other organizations. Hence, this article discusses such engagement in terms of next-generation living lab networks in the city context. In so doing, the study contributes to the discussion on living labs by introducing a framework of collaborative innovation networks in cities and suggesting a typology of third-generation living labs. Our framework is characterized by diverse platforms and participation approaches, resulting in four distinctive modes of collaborative innovation networks where the city is: i a provider, ii a neighbourhood participator, iii a catalyst, or iv a rapid experimenter. The typology is based on an analysis of 118 interviews with participants in six Finnish cities and reveals various ways to organize innovation activities in the city context. In particular, cities can benefit from innovation networks by simultaneously exploiting multiple platforms such as living labs for innovation. We conclude by discussing implications to theory and practice, and suggesting directions for future research.

  3. Small Distributed Renewable Energy Generation for Low Voltage Distribution Networks

    Directory of Open Access Journals (Sweden)

    Chindris M.

    2016-08-01

    Full Text Available Driven by the existing energy policies, the use of renewable energy has increased considerably all over the world in order to respond to the increasing energy consumption and to reduce the environmental impact of the electricity generation. Although most policy makers and companies are focusing on large applications, the use of cheap small generation units, based on local renewable resources, has become increasingly attractive for the general public, small farms and remote communities. The paper presents several results of a research project aiming to identify the power quality issues and the impact of RES based distributed generation (DG or other non-linear loads on low voltage (LV distribution networks in Romania; the final goal is to develop a Universal Power Quality Conditioner (UPQC able to diminish the existing disturbances. Basically, the work analyses the existing DG technologies and identifies possible solutions for their integration in Romania; taking into account the existent state of the art, the attention was paid on small systems, using wind and solar energy, and on possibility to integrate them into suburban and rural LV distribution networks. The presence of DG units at distribution voltage level means the transition from traditional passive to active distribution networks. In general, the relatively low penetration levels of DG does not produce problems; however, the nowadays massive increase of local power generation have led to new integration challenges in order to ensure the reliability and quality of the power supply. Power quality issues are identified and their assessment is the key element in the design of measures aiming to diminish all existing disturbances.

  4. Understanding the Generation of Network Bursts by Adaptive Oscillatory Neurons

    Directory of Open Access Journals (Sweden)

    Tanguy Fardet

    2018-02-01

    Full Text Available Experimental and numerical studies have revealed that isolated populations of oscillatory neurons can spontaneously synchronize and generate periodic bursts involving the whole network. Such a behavior has notably been observed for cultured neurons in rodent's cortex or hippocampus. We show here that a sufficient condition for this network bursting is the presence of an excitatory population of oscillatory neurons which displays spike-driven adaptation. We provide an analytic model to analyze network bursts generated by coupled adaptive exponential integrate-and-fire neurons. We show that, for strong synaptic coupling, intrinsically tonic spiking neurons evolve to reach a synchronized intermittent bursting state. The presence of inhibitory neurons or plastic synapses can then modulate this dynamics in many ways but is not necessary for its appearance. Thanks to a simple self-consistent equation, our model gives an intuitive and semi-quantitative tool to understand the bursting behavior. Furthermore, it suggests that after-hyperpolarization currents are sufficient to explain bursting termination. Through a thorough mapping between the theoretical parameters and ion-channel properties, we discuss the biological mechanisms that could be involved and the relevance of the explored parameter-space. Such an insight enables us to propose experimentally-testable predictions regarding how blocking fast, medium or slow after-hyperpolarization channels would affect the firing rate and burst duration, as well as the interburst interval.

  5. Handover Based IMS Registration Scheme for Next Generation Mobile Networks

    Directory of Open Access Journals (Sweden)

    Shireen Tahira

    2017-01-01

    Full Text Available Next generation mobile networks aim to provide faster speed and more capacity along with energy efficiency to support video streaming and massive data sharing in social and communication networks. In these networks, user equipment has to register with IP Multimedia Subsystem (IMS which promises quality of service to the mobile users that frequently move across different access networks. After each handover caused due to mobility, IMS provides IPSec Security Association establishment and authentication phases. The main issue is that unnecessary reregistration after every handover results in latency and communication overhead. To tackle these issues, this paper presents a lightweight Fast IMS Mobility (FIM registration scheme that avoids unnecessary conventional registration phases such as security associations, authentication, and authorization. FIM maintains a flag to avoid deregistration and sends a subsequent message to provide necessary parameters to IMS servers after mobility. It also handles the change of IP address for user equipment and transferring the security associations from old to new servers. We have validated the performance of FIM by developing a testbed consisting of IMS servers and user equipment. The experimental results demonstrate the performance supremacy of FIM. It reduces media disruption time, number of messages, and packet loss up to 67%, 100%, and 61%, respectively, as compared to preliminaries.

  6. Generating route choice sets with operation information on metro networks

    Directory of Open Access Journals (Sweden)

    Wei Zhu

    2016-06-01

    Full Text Available In recent years, the metro system has advanced into an efficient transport system and become the mainstay of urban passenger transport in many mega-cities. Passenger flow is the foundation of making and coordinating operation plans for the metro system, and therefore, a variety of studies were conducted on transit assignment models. Nevertheless route choice sets of passengers also play a paramount role in flow estimation and demand prediction. This paper first discusses the main route constraints of which the train schedule is the most important, that distinguish rail networks from road networks. Then, a two-step approach to generate route choice set in a metro network is proposed. Particularly, the improved approach introduces a route filtering with train operational information based on the conventional method. An initial numerical test shows that the proposed approach gives more reasonable route choice sets for scheduled metro networks, and, consequently, obtains more accurate results from passenger flow assignment. Recommendations for possible opportunities to apply this approach to metro operations are also provided, including its integration into a metro passenger flow assignment and simulation system in practice to help metro authorities provide more precise guidance information for passengers to travel.

  7. Morphological Transformation and Force Generation of Active Cytoskeletal Networks.

    Directory of Open Access Journals (Sweden)

    Tamara Carla Bidone

    2017-01-01

    Full Text Available Cells assemble numerous types of actomyosin bundles that generate contractile forces for biological processes, such as cytokinesis and cell migration. One example of contractile bundles is a transverse arc that forms via actomyosin-driven condensation of actin filaments in the lamellipodia of migrating cells and exerts significant forces on the surrounding environments. Structural reorganization of a network into a bundle facilitated by actomyosin contractility is a physiologically relevant and biophysically interesting process. Nevertheless, it remains elusive how actin filaments are reoriented, buckled, and bundled as well as undergo tension buildup during the structural reorganization. In this study, using an agent-based computational model, we demonstrated how the interplay between the density of myosin motors and cross-linking proteins and the rigidity, initial orientation, and turnover of actin filaments regulates the morphological transformation of a cross-linked actomyosin network into a bundle and the buildup of tension occurring during the transformation.

  8. Prediction of municipal solid waste generation using nonlinear autoregressive network.

    Science.gov (United States)

    Younes, Mohammad K; Nopiah, Z M; Basri, N E Ahmad; Basri, H; Abushammala, Mohammed F M; Maulud, K N A

    2015-12-01

    Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.

  9. Amplified CWDM-based Next Generation Broadband Access Networks

    Science.gov (United States)

    Peiris, Sasanthi Chamarika

    The explosive growth of both fixed and mobile data-centric traffic along with the inevitable trend towards all-IP/Ethernet transport protocols and packet switched networks will ultimately lead to an all-packet-based converged fixed-mobile optical transport network from the core all the way out to the access network. To address the increasing capacity and speed requirements in the access networks, Wavelength-Division Multiplexed (WDM) and/or Coarse WDM (CWDM)-based Passive Optical Networks (PONs) are expected to emerge as the next-generation optical access infrastructures. However, due to several techno-economic hurdles, CWDM-PONs are still considered an expensive solution and have not yet made any significant inroads into the current access area. One of the key technology hurdles is the scalability of the CWDM-based PONs. Passive component optical insertion losses limit the reach of the network or the number of served optical network units (ONUs). In the recent years, optical amplified CWDM approaches have emerged and new designs of optical amplifiers have been proposed and demonstrated. The critical design parameter for these amplifiers is the very wide optical amplification bandwidth (e.g., 340 nm combined for both directions). The objective of this PhD dissertation work is first to engineer ring and tree-ring based PON architectures that can achieve longer unamplified PON reach and/or provide service to a greater number of ONUs and customers. Secondly is to develop new novel optical amplifier schemes to further address the scalability limitation of the CWDM-based PONs. Specifically, this work proposes and develops novel ultra wide-band hybrid Raman-Optical parametric amplifier (HROPA) schemes that operate over nearly the entire specified CWDM band to provide 340 nm bidirectional optical gain bandwidth over the amplified PON's downstream and upstream CWDM wavelength bands (about 170 nm in each direction). The performance of the proposed HROPA schemes is assessed

  10. Custom Topology Generation for Network-on-Chip

    DEFF Research Database (Denmark)

    Stuart, Matthias Bo; Sparsø, Jens

    2007-01-01

    This paper compares simulated annealing and tabu search for generating custom topologies for applications with periodic behaviour executing on a network-on-chip. The approach differs from previous work by starting from a fixed mapping of IP-cores to routers and performing design space exploration...... around an initial topology. The tabu search has been modified from its normally encountered form to allow easier escaping from local minima. A number of synthetic benchmarks are used for tuning the parameters of both heuristics and for testing the quality of the solutions each heuristic produces...

  11. Reactive power management of power networks with wind generation

    CERN Document Server

    Amaris, Hortensia; Ortega, Carlos Alvarez

    2012-01-01

    As the energy sector shifts and changes to focus on renewable technologies, the optimization of wind power becomes a key practical issue. Reactive Power Management of Power Networks with Wind Generation brings into focus the development and application of advanced optimization techniques to the study, characterization, and assessment of voltage stability in power systems. Recent advances on reactive power management are reviewed with particular emphasis on the analysis and control of wind energy conversion systems and FACTS devices. Following an introduction, distinct chapters cover the 5 key

  12. Wireless next generation networks a virtue-based trust model

    CERN Document Server

    Harvey, Melissa

    2014-01-01

    This SpringerBrief proposes a trust model motivated by virtue epistemology, addressing the need for a more efficient and flexible trust model for wireless next generation networks. This theory of trust simplifies the computation and communication overhead of strictly cognitive-computational models of trust. Both the advantages and the challenges of virtue-based trust models are discussed. This brief offers new research and a general theory of rationality that enables users to interpret trust and reason as complementary mechanisms that guide our rational conduct at two different epistemic level

  13. The European Nuclear Society Young Generation Network: Five years of networking experience

    International Nuclear Information System (INIS)

    Meskens, Gaston

    2000-01-01

    In 1995, Mr Jan Runermark (Sweden), aware of a need for an exchange of knowledge from the older to the younger generation, came up with the idea of starting a European Nuclear Society Young Generation Network. A first network was formed with Sweden, the Netherlands, Spain, Finland, Germany and Belgium. The ENSYGN is now affiliated to the European Nuclear Society and brings together young students and professionals from 21 member countries Belgium, Bulgaria, Croatia, Czech Republic, Denmark Finland, France, Germany, Hungary, Italy, Netherlands, Poland, Romania, Russia, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Ukraine, and United Kingdom, The ENSYGN Core group meets (at least) twice a year and elects its own chair and co chair for a term of two years. The ENSYGN chair has a seat in the ENS Steering Committee and in the ENS Board. The ENSYGN works closely together with other young generation networks from the US, Australia, Japan and South America. ENSYGN organises workshops and courses on European level, takes part in international meetings (fl. UNFCCC, OECD) and stimulates networking on national level

  14. Using Neural Networks to Generate Inferential Roles for Natural Language

    Directory of Open Access Journals (Sweden)

    Peter Blouw

    2018-01-01

    Full Text Available Neural networks have long been used to study linguistic phenomena spanning the domains of phonology, morphology, syntax, and semantics. Of these domains, semantics is somewhat unique in that there is little clarity concerning what a model needs to be able to do in order to provide an account of how the meanings of complex linguistic expressions, such as sentences, are understood. We argue that one thing such models need to be able to do is generate predictions about which further sentences are likely to follow from a given sentence; these define the sentence's “inferential role.” We then show that it is possible to train a tree-structured neural network model to generate very simple examples of such inferential roles using the recently released Stanford Natural Language Inference (SNLI dataset. On an empirical front, we evaluate the performance of this model by reporting entailment prediction accuracies on a set of test sentences not present in the training data. We also report the results of a simple study that compares human plausibility ratings for both human-generated and model-generated entailments for a random selection of sentences in this test set. On a more theoretical front, we argue in favor of a revision to some common assumptions about semantics: understanding a linguistic expression is not only a matter of mapping it onto a representation that somehow constitutes its meaning; rather, understanding a linguistic expression is mainly a matter of being able to draw certain inferences. Inference should accordingly be at the core of any model of semantic cognition.

  15. Implementing Value Added Applications in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Yuan-Kuang Tu

    2010-08-01

    Full Text Available One of the major issues in the future Internet is the integration of telecom networks with the Internet. In many countries, large Internet Service Providers (ISPs are also telecom operators that have been focusing on providing Internet services through their telecom networks with telecom-grade mechanisms. In this article, we show that IP Multimedia Subsystem (IMS is a telecom-grade mechanism that addresses this important issue. In Next Generation Network (NGN, IMS supports IP-based multimedia services that can be accessed from various wireless and wired access technologies through fixed-mobile convergence. We show how to integrate Internet Protocol Television (IPTV with NGN/IMS to offer enhanced IPTV services for subscribers with set-top boxes or mobile phones. We specifically describe the implementations of three services: weather forecasts, short messages on TV screens and TV shopping/food ordering for mobile users. Although these services can be directly implemented in the Internet, our commercial operation experiences indicate that the NGN/IMS implementation has advantages in terms of telecom-grade security, Quality of Service (QoS, and flexible service creation.

  16. An Intelligent Handover Management System for Future Generation Wireless Networks

    Directory of Open Access Journals (Sweden)

    Kassar Meriem

    2008-01-01

    Full Text Available Abstract Future generation wireless networks should provide to mobile users the best connectivity to services anywhere at anytime. The most challenging problem is the seamless intersystem/vertical mobility across heterogeneous wireless networks. In order to answer it, a vertical handover management system is needed. In our paper, we propose an intelligent solution answering user requirements and ensuring service continuity. We focus on a vertical handover decision strategy based on the context-awareness concept. The given strategy chooses the appropriate time and the most suitable access network among those available to perform a handover. It uses advanced decision algorithms (for more efficiency and intelligence and it is governed by handover policies as decision rules (for more flexibility and optimization. To maintain a seamless service continuity, handover execution is based on mobile IP functionalities. We study our decision system in a case of a 3G/UMTS-WLAN scenario and we discuss all the handover decision issues in our solution.

  17. Generative Recurrent Networks for De Novo Drug Design.

    Science.gov (United States)

    Gupta, Anvita; Müller, Alex T; Huisman, Berend J H; Fuchs, Jens A; Schneider, Petra; Schneider, Gisbert

    2018-01-01

    Generative artificial intelligence models present a fresh approach to chemogenomics and de novo drug design, as they provide researchers with the ability to narrow down their search of the chemical space and focus on regions of interest. We present a method for molecular de novo design that utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells. This computational model captured the syntax of molecular representation in terms of SMILES strings with close to perfect accuracy. The learned pattern probabilities can be used for de novo SMILES generation. This molecular design concept eliminates the need for virtual compound library enumeration. By employing transfer learning, we fine-tuned the RNN's predictions for specific molecular targets. This approach enables virtual compound design without requiring secondary or external activity prediction, which could introduce error or unwanted bias. The results obtained advocate this generative RNN-LSTM system for high-impact use cases, such as low-data drug discovery, fragment based molecular design, and hit-to-lead optimization for diverse drug targets. © 2017 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

  18. Integrating generation and transmission networks reliability for unit commitment solution

    International Nuclear Information System (INIS)

    Jalilzadeh, S.; Shayeghi, H.; Hadadian, H.

    2009-01-01

    This paper presents a new method with integration of generation and transmission networks reliability for the solution of unit commitment (UC) problem. In fact, in order to have a more accurate assessment of system reserve requirement, in addition to unavailability of generation units, unavailability of transmission lines are also taken into account. In this way, evaluation of the required spinning reserve (SR) capacity is performed by applying reliability constraints based on loss of load probability and expected energy not supplied (EENS) indices. Calculation of the above parameters is accomplished by employing a novel procedure based on the linear programming which it also minimizes them to achieve optimum level of the SR capacity and consequently a cost-benefit reliability constrained UC schedule. In addition, a powerful solution technique called 'integer-coded genetic algorithm (ICGA)' is being used for the solution of the proposed method. Numerical results on the IEEE reliability test system show that the consideration of transmission network unavailability has an important influence on reliability indices of the UC schedules

  19. Optimal power flow for distribution networks with distributed generation

    Directory of Open Access Journals (Sweden)

    Radosavljević Jordan

    2015-01-01

    Full Text Available This paper presents a genetic algorithm (GA based approach for the solution of the optimal power flow (OPF in distribution networks with distributed generation (DG units, including fuel cells, micro turbines, diesel generators, photovoltaic systems and wind turbines. The OPF is formulated as a nonlinear multi-objective optimization problem with equality and inequality constraints. Due to the stochastic nature of energy produced from renewable sources, i.e. wind turbines and photovoltaic systems, as well as load uncertainties, a probabilisticalgorithm is introduced in the OPF analysis. The Weibull and normal distributions are employed to model the input random variables, namely the wind speed, solar irradiance and load power. The 2m+1 point estimate method and the Gram Charlier expansion theory are used to obtain the statistical moments and the probability density functions (PDFs of the OPF results. The proposed approach is examined and tested on a modified IEEE 34 node test feeder with integrated five different DG units. The obtained results prove the efficiency of the proposed approach to solve both deterministic and probabilistic OPF problems for different forms of the multi-objective function. As such, it can serve as a useful decision-making supporting tool for distribution network operators. [Projekat Ministarstva nauke Republike Srbije, br. TR33046

  20. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  1. Efficient Pruning Method for Ensemble Self-Generating Neural Networks

    Directory of Open Access Journals (Sweden)

    Hirotaka Inoue

    2003-12-01

    Full Text Available Recently, multiple classifier systems (MCS have been used for practical applications to improve classification accuracy. Self-generating neural networks (SGNN are one of the suitable base-classifiers for MCS because of their simple setting and fast learning. However, the computation cost of the MCS increases in proportion to the number of SGNN. In this paper, we propose an efficient pruning method for the structure of the SGNN in the MCS. We compare the pruned MCS with two sampling methods. Experiments have been conducted to compare the pruned MCS with an unpruned MCS, the MCS based on C4.5, and k-nearest neighbor method. The results show that the pruned MCS can improve its classification accuracy as well as reducing the computation cost.

  2. Latest generation interconnect technologies in APEnet+ networking infrastructure

    Science.gov (United States)

    Ammendola, Roberto; Biagioni, Andrea; Cretaro, Paolo; Frezza, Ottorino; Lo Cicero, Francesca; Lonardo, Alessandro; Martinelli, Michele; Stanislao Paolucci, Pier; Pastorelli, Elena; Rossetti, Davide; Simula, Francesco; Vicini, Piero

    2017-10-01

    In this paper we present the status of the 3rd generation design of the APEnet board (V5) built upon the 28nm Altera Stratix V FPGA; it features a PCIe Gen3 x8 interface and enhanced embedded transceivers with a maximum capability of 12.5Gbps each. The network architecture is designed in accordance to the Remote DMA paradigm. The APEnet+ V5 prototype is built upon the Stratix V DevKit with the addition of a proprietary, third party IP core implementing multi-DMA engines. Support for zero-copy communication is assured by the possibility of DMA-accessing either host and GPU memory, offloading the CPU from the chore of data copying. The current implementation plateaus to a bandwidth for memory read of 4.8GB/s. Here we describe the hardware optimization to the memory write process which relies on the use of two independent DMA engines and an improved TLB.

  3. Optimizing Low Speed VoIP Network for Rural Next Generation Network (R-NGN

    Directory of Open Access Journals (Sweden)

    Yoanes Bandung

    2007-11-01

    Full Text Available In this research, we propose an optimization method based-on E-Model for designing an efficient low speed VoIP network for Rural Next Generation Network (R-NGN. We are choosing 128 kbps and 256 kbps bandwidth as the typical community link to be used in the designing of R-NGN infrastructure. The method is based on selection of some VoIP network parameters such as voice coder, communication protocol, packet loss level, network utilization and resource allocation. We draw analytic approach for achieving rating value (R of E-model that represent level of quality of service. In this approach, we focus on delay and packet loss calculation to find the rating value. We state the rating value = 70 as minimum level of quality of service for each call, equivalent to 3.6 of Mean Opinion Score (MOS. In our experiments, either G.723.1 5.3 kbps or G.729 is chosen for maximizing the number of VoIP calls, it depends on link utilization and level of packet loss.

  4. Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

    Science.gov (United States)

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-03-01

    A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

  5. TopoGen: A Network Topology Generation Architecture with application to automating simulations of Software Defined Networks

    CERN Document Server

    Laurito, Andres; The ATLAS collaboration

    2017-01-01

    Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...

  6. TopoGen: A Network Topology Generation Architecture with application to automating simulations of Software Defined Networks

    CERN Document Server

    Laurito, Andres; The ATLAS collaboration

    2018-01-01

    Simulation is an important tool to validate the performance impact of control decisions in Software Defined Networks (SDN). Yet, the manual modeling of complex topologies that may change often during a design process can be a tedious error-prone task. We present TopoGen, a general purpose architecture and tool for systematic translation and generation of network topologies. TopoGen can be used to generate network simulation models automatically by querying information available at diverse sources, notably SDN controllers. The DEVS modeling and simulation framework facilitates a systematic translation of structured knowledge about a network topology into a formal modular and hierarchical coupling of preexisting or new models of network entities (physical or logical). TopoGen can be flexibly extended with new parsers and generators to grow its scope of applicability. This permits to design arbitrary workflows of topology transformations. We tested TopoGen in a network engineering project for the ATLAS detector ...

  7. Investigation of a generator system for generating electrical power, to supply directly to the public network, using a windmill

    Science.gov (United States)

    Tromp, C.

    1979-01-01

    A windpowered generator system is described which uses a windmill to convert mechanical energy to electrical energy for a three phase (network) voltage of constant amplitude and frequency. The generator system controls the windmill by the number of revolutions so that the power drawn from the wind for a given wind velocity is maximum. A generator revolution which is proportional to wind velocity is achieved. The stator of the generator is linked directly to the network and a feed converter at the rotor takes care of constant voltage and frequency at the stator.

  8. Challenges in Second-Generation Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Pescapé Antonio

    2008-01-01

    Full Text Available Wireless mesh networks have the potential to provide ubiquitous high-speed Internet access at low costs. The good news is that initial deployments of WiFi meshes show the feasibility of providing ubiquitous Internet connectivity. However, their performance is far below the necessary and achievable limit. Moreover, users' subscription in the existing meshes is dismal even though the technical challenges to get connectivity are low. This paper provides an overview of the current status of mesh networks' deployment, and highlights the technical, economical, and social challenges that need to be addressed in the next years. As a proof-of-principle study, we discuss the above-mentioned challenges with reference to three real networks: (i MagNets, an operator-driven planned two-tier mesh network; (ii Berlin Freifunk network as a pure community-driven single-tier network; (iii Weimar Freifunk network, also a community-driven but two-tier network.

  9. Challenges in Second-Generation Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Thomas Huehn

    2008-10-01

    Full Text Available Wireless mesh networks have the potential to provide ubiquitous high-speed Internet access at low costs. The good news is that initial deployments of WiFi meshes show the feasibility of providing ubiquitous Internet connectivity. However, their performance is far below the necessary and achievable limit. Moreover, users' subscription in the existing meshes is dismal even though the technical challenges to get connectivity are low. This paper provides an overview of the current status of mesh networks' deployment, and highlights the technical, economical, and social challenges that need to be addressed in the next years. As a proof-of-principle study, we discuss the above-mentioned challenges with reference to three real networks: (i MagNets, an operator-driven planned two-tier mesh network; (ii Berlin Freifunk network as a pure community-driven single-tier network; (iii Weimar Freifunk network, also a community-driven but two-tier network.

  10. Automatic generation of investigator bibliographies for institutional research networking systems.

    Science.gov (United States)

    Johnson, Stephen B; Bales, Michael E; Dine, Daniel; Bakken, Suzanne; Albert, Paul J; Weng, Chunhua

    2014-10-01

    Publications are a key data source for investigator profiles and research networking systems. We developed ReCiter, an algorithm that automatically extracts bibliographies from PubMed using institutional information about the target investigators. ReCiter executes a broad query against PubMed, groups the results into clusters that appear to constitute distinct author identities and selects the cluster that best matches the target investigator. Using information about investigators from one of our institutions, we compared ReCiter results to queries based on author name and institution and to citations extracted manually from the Scopus database. Five judges created a gold standard using citations of a random sample of 200 investigators. About half of the 10,471 potential investigators had no matching citations in PubMed, and about 45% had fewer than 70 citations. Interrater agreement (Fleiss' kappa) for the gold standard was 0.81. Scopus achieved the best recall (sensitivity) of 0.81, while name-based queries had 0.78 and ReCiter had 0.69. ReCiter attained the best precision (positive predictive value) of 0.93 while Scopus had 0.85 and name-based queries had 0.31. ReCiter accesses the most current citation data, uses limited computational resources and minimizes manual entry by investigators. Generation of bibliographies using named-based queries will not yield high accuracy. Proprietary databases can perform well but requite manual effort. Automated generation with higher recall is possible but requires additional knowledge about investigators. Copyright © 2014 Elsevier Inc. All rights reserved.

  11. Mobile location services over the next generation IP core network

    DEFF Research Database (Denmark)

    Thongthammachart, Saowanee; Olesen, Henning

    2003-01-01

    network is changing from circuit-switched to packet-switched technology and evolving to an IP core network based on IPv6. The IP core network will allow all IP devices to be connected seamlessly. Due to the movement detection mechanism of Mobile IPv6, mobile terminals will periodically update...

  12. Ichthyoplankton Classification Tool using Generative Adversarial Networks and Transfer Learning

    KAUST Repository

    Aljaafari, Nura

    2018-04-15

    The study and the analysis of marine ecosystems is a significant part of the marine science research. These systems are valuable resources for fisheries, improving water quality and can even be used in drugs production. The investigation of ichthyoplankton inhabiting these ecosystems is also an important research field. Ichthyoplankton are fish in their early stages of life. In this stage, the fish have relatively similar shape and are small in size. The currently used way of identifying them is not optimal. Marine scientists typically study such organisms by sending a team that collects samples from the sea which is then taken to the lab for further investigation. These samples need to be studied by an expert and usually end needing a DNA sequencing. This method is time-consuming and requires a high level of experience. The recent advances in AI have helped to solve and automate several difficult tasks which motivated us to develop a classification tool for ichthyoplankton. We show that using machine learning techniques, such as generative adversarial networks combined with transfer learning solves such a problem with high accuracy. We show that using traditional machine learning algorithms fails to solve it. We also give a general framework for creating a classification tool when the dataset used for training is a limited dataset. We aim to build a user-friendly tool that can be used by any user for the classification task and we aim to give a guide to the researchers so that they can follow in creating a classification tool.

  13. Hybrid scheduling mechanisms for Next-generation Passive Optical Networks based on network coding

    Science.gov (United States)

    Zhao, Jijun; Bai, Wei; Liu, Xin; Feng, Nan; Maier, Martin

    2014-10-01

    Network coding (NC) integrated into Passive Optical Networks (PONs) is regarded as a promising solution to achieve higher throughput and energy efficiency. To efficiently support multimedia traffic under this new transmission mode, novel NC-based hybrid scheduling mechanisms for Next-generation PONs (NG-PONs) including energy management, time slot management, resource allocation, and Quality-of-Service (QoS) scheduling are proposed in this paper. First, we design an energy-saving scheme that is based on Bidirectional Centric Scheduling (BCS) to reduce the energy consumption of both the Optical Line Terminal (OLT) and Optical Network Units (ONUs). Next, we propose an intra-ONU scheduling and an inter-ONU scheduling scheme, which takes NC into account to support service differentiation and QoS assurance. The presented simulation results show that BCS achieves higher energy efficiency under low traffic loads, clearly outperforming the alternative NC-based Upstream Centric Scheduling (UCS) scheme. Furthermore, BCS is shown to provide better QoS assurance.

  14. R&D on wireless broadband communication systems: new generation ubiquitous mobile network

    Science.gov (United States)

    Ogawa, Hiroyo

    2007-09-01

    R&D on new generation mobile network has attracted a growing interest over the world on the background of rapid market growth for 2nd and 3rd - generation cellular networks and wireless LANs/MANs. The National Institute of Information and Communications Technology (NICT) has been carried out the New Generation Mobile Network Project from April 2002 to March 2006, and has developed fundamental technologies to enable seamless and secure integration of various wireless access networks such as existing cellular networks, wireless LANs, home networks, intelligent transport systems (ITS), the Beyond-3G (B3G) cellular and other wireless access systems. From April 2006, Ubiquitous Mobile Network project focused on cognitive radio technology and integrated seamless networking technology was started. This paper overviews the achievement and the future plan of these projects.

  15. Effects of traffic generation patterns on the robustness of complex networks

    Science.gov (United States)

    Wu, Jiajing; Zeng, Junwen; Chen, Zhenhao; Tse, Chi K.; Chen, Bokui

    2018-02-01

    Cascading failures in communication networks with heterogeneous node functions are studied in this paper. In such networks, the traffic dynamics are highly dependent on the traffic generation patterns which are in turn determined by the locations of the hosts. The data-packet traffic model is applied to Barabási-Albert scale-free networks to study the cascading failures in such networks and to explore the effects of traffic generation patterns on network robustness. It is found that placing the hosts at high-degree nodes in a network can make the network more robust against both intentional attacks and random failures. It is also shown that the traffic generation pattern plays an important role in network design.

  16. Identifying options for regulating the coordination of network investments with investments in distributed electricity generation

    International Nuclear Information System (INIS)

    Nisten, E.

    2010-02-01

    The increase in the distributed generation of electricity, with wind turbines and solar panels, necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments and the frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the DSOs to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulation, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generators.

  17. Optogenetic stimulation effectively enhances intrinsically generated network synchrony

    Directory of Open Access Journals (Sweden)

    Ahmed eEl Hady

    2013-10-01

    Full Text Available Synchronized bursting is found in many brain areas and has also been implicated in the pathophysiology of neuropsychiatric disorders such as epilepsy, Parkinson’s disease and schizophrenia. Despite extensive studies of network burst synchronization, it is insufficiently understood how this type of network wide synchronization can be strengthened, reduced or even abolished. We combined electrical recording using multi-electrode array with optical stimulation of cultured channelrhodopsin-2 transducted hippocampal neurons to study and manipulate network burst synchronization. We found low frequency photo-stimulation protocols that are sufficient to induce potentiation of network bursting, modifying bursting dynamics and increasing interneuronal synchronization. Surprisingly, slowly fading-in light stimulation, which substantially delayed and reduced light driven spiking, was at least as effective in reorganizing network dynamics as much stronger pulsed light stimulation. Our study shows that mild stimulation protocols that do not enforce particular activity patterns onto the network can be highly effective inducers of network-level plasticity.

  18. Optogenetic stimulation effectively enhances intrinsically generated network synchrony

    Science.gov (United States)

    El Hady, Ahmed; Afshar, Ghazaleh; Bröking, Kai; Schlüter, Oliver M.; Geisel, Theo; Stühmer, Walter; Wolf, Fred

    2013-01-01

    Synchronized bursting is found in many brain areas and has also been implicated in the pathophysiology of neuropsychiatric disorders such as epilepsy, Parkinson’s disease, and schizophrenia. Despite extensive studies of network burst synchronization, it is insufficiently understood how this type of network wide synchronization can be strengthened, reduced, or even abolished. We combined electrical recording using multi-electrode array with optical stimulation of cultured channelrhodopsin-2 transducted hippocampal neurons to study and manipulate network burst synchronization. We found low frequency photo-stimulation protocols that are sufficient to induce potentiation of network bursting, modifying bursting dynamics, and increasing interneuronal synchronization. Surprisingly, slowly fading-in light stimulation, which substantially delayed and reduced light-driven spiking, was at least as effective in reorganizing network dynamics as much stronger pulsed light stimulation. Our study shows that mild stimulation protocols that do not enforce particular activity patterns onto the network can be highly effective inducers of network-level plasticity. PMID:24155695

  19. Question Generation and Adaptation Using a Bayesian Network of the Learner’s Achievements

    NARCIS (Netherlands)

    Wißner, M.; Linnebank, F.; Liem, J.; Bredeweg, B.; André, E.; Lane, H.C.; Yacef, K.; Mostow, J.; Pavlik, P.

    2013-01-01

    This paper presents a domain independent question generation and interaction procedure that automatically generates multiple-choice questions for conceptual models created with Qualitative Reasoning vocabulary. A Bayesian Network is deployed that captures the learning progress based on the answers

  20. Security management of next generation telecommunications networks and services

    CERN Document Server

    Jacobs, Stuart

    2014-01-01

    This book will cover network management security issues and currently available security mechanisms by discussing how network architectures have evolved into the contemporary NGNs which support converged services (voice, video, TV, interactive information exchange, and classic data communications). It will also analyze existing security standards and their applicability to securing network management. This book will review 21st century security concepts of authentication, authorization, confidentiality, integrity, nonrepudiation, vulnerabilities, threats, risks, and effective approaches to enc

  1. Cisco Networking Academy: Next-Generation Assessments and Their Implications for K-12 Education

    Science.gov (United States)

    Liu, Meredith

    2014-01-01

    To illuminate the possibilities for next-generation assessments in K-12 schools, this case study profiles the Cisco Networking Academy, which creates comprehensive online training curriculum to teach networking skills. Since 1997, the Cisco Networking Academy has served more than five million high school and college students and now delivers…

  2. Social network indices in the Generations and Gender Survey: An appraisal

    NARCIS (Netherlands)

    Dykstra, P.A.; Bühler, C.; Fokkema, T.; Petric, G.; Platinovsek, R.; Kogovsek, T.; Hlebec, V.

    2016-01-01

    Background: In this contribution we critically appraise the social network indices in the Generations and Gender Survey (GGS). Objective: After discussing the rationale for including social network indices in the GGS, we provide descriptive information on social network characteristics and an

  3. Next Generation Flexible and Cognitive Heterogeneous Optical Networks

    DEFF Research Database (Denmark)

    Tomkos, Ioannis; Angelou, Marianna; Barroso, Ramón J. Durán

    2012-01-01

    Optical networking is the cornerstone of the Future Internet as it provides the physical infrastructure of the core backbone networks. Recent developments have enabled much better quality of service/experience for the end users, enabled through the much higher capacities that can be supported...... the capabilities of the Future Internet. In this book chapter, we highlight the latest activities of the optical networking community and in particular what has been the focus of EU funded research. The concepts of flexible and cognitive optical networks are introduced and their key expected benefits...

  4. Advanced satellite concepts for future generation VSAT networks

    Science.gov (United States)

    Naderi, F. Michael; Wu, William W.

    1988-01-01

    Advanced communication networks that use very-small-aperture terminals (VSATs) are considered. The techniques and technologies suitable for powerful satellites and system architectures for future VSAT networks are discussed. These include high effective isotropic radiated power, multiple-beam satellite antennas, and various access techniques. Examples of systems planned by the government and private industry are described.

  5. Network as a service for next generation internet

    CERN Document Server

    Duan, Qiang

    2017-01-01

    This book presents the state of the art of the Network-as-a-Service (NaaS) paradigm, including its concepts, architecture, key technologies, applications, and development directions for future network service provisioning. It provides a comprehensive reference that reflects the most current technical developments related to NaaS.

  6. Channel modeling for fifth generation cellular networks and wireless sensor networks

    Science.gov (United States)

    Torabi, Amir

    In view of exponential growth in data traffic demand, the wireless communications industry has aimed to increase the capacity of existing networks by 1000 times over the next 20 years. A combination of extreme cell densification, more bandwidth, and higher spectral efficiency is needed to support the data traffic requirements for fifth generation (5G) cellular communications. In this research, the potential improvements achieved by using three major 5G enabling technologies (i.e., small cells, millimeter-wave spectrum, and massive MIMO) in rural and urban environments are investigated. This work develops SPM and KA-based ray models to investigate the impact of geometrical parameters on terrain-based multiuser MIMO channel characteristic. Moreover, a new directional 3D channel model is developed for urban millimeter-wave (mmW) small cells. Path-loss, spatial correlation, coverage distance, and coherence length are studied in urban areas. Exploiting physical optics (PO) and geometric optics (GO) solutions, closed form expressions are derived for spatial correlation. Achievable spatial diversity is evaluated using horizontal and vertical linear arrays as well as planar 2D arrays. In another study, a versatile near-ground field prediction model is proposed to facilitate accurate wireless sensor network (WSN) simulations. Monte Carlo simulations are used to investigate the effects of antenna height, frequency of operation, polarization, and terrain dielectric and roughness properties on WSNs performance.

  7. Column Generation for Transmission Switching of Electricity Networks with Unit Commitment

    DEFF Research Database (Denmark)

    Villumsen, Jonas Christoffer; Philpott, Andy B.

    2011-01-01

    This paper presents the problem of finding the minimum cost dispatch and commitment of power generation units in a transmission network with active switching.We use the term active switching to denote the use of switches to optimize network topology in an operational context. We propose a Dantzig......-Wolfe reformulation and a novel column generation framework to solve the problem efficiently. Preliminary results are presented for the IEEE-118 bus network with 19 generator units. Active switching is shown to reduce total cost by up to 15 % for a particular 24-hour period. Furthermore, the need for generator...

  8. A two-stage flow-based intrusion detection model for next-generation networks.

    Science.gov (United States)

    Umer, Muhammad Fahad; Sher, Muhammad; Bi, Yaxin

    2018-01-01

    The next-generation network provides state-of-the-art access-independent services over converged mobile and fixed networks. Security in the converged network environment is a major challenge. Traditional packet and protocol-based intrusion detection techniques cannot be used in next-generation networks due to slow throughput, low accuracy and their inability to inspect encrypted payload. An alternative solution for protection of next-generation networks is to use network flow records for detection of malicious activity in the network traffic. The network flow records are independent of access networks and user applications. In this paper, we propose a two-stage flow-based intrusion detection system for next-generation networks. The first stage uses an enhanced unsupervised one-class support vector machine which separates malicious flows from normal network traffic. The second stage uses a self-organizing map which automatically groups malicious flows into different alert clusters. We validated the proposed approach on two flow-based datasets and obtained promising results.

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

    Science.gov (United States)

    Zhang, Xianjun

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

  10. Next generation network: How to stimulate investment while maintaining a competitive market

    OpenAIRE

    Gallo, Elena; Solimene, Laura

    2010-01-01

    High-speed communication networks are the basic infrastructure for a whole range of next generation communication services. They can induce a wave of innovations and eventually lead to growth and new employment. However, large investments will be needed to generate Next Generation Networks (NGN) and the risks for the investor will be substantial. On the other hand, investors can create monopolistic bottlenecks which prevent competitors from gaining access to essential infrastructure. As a con...

  11. Active local distribution network management for embedded generation

    Energy Technology Data Exchange (ETDEWEB)

    White, S.

    2005-07-01

    With the newer electric power transmission networks, there is a requirement for power to flow in two different directions and this calls for more intelligent forms of management. To satisfy these demands, GENEVAC has produced a controller that aims to increase the energy that power plants can feed to the distribution networks. The software and hardware have undergone trials at two 33/11 kV substations in England. The hardware was designed to monitor voltage, current and phase angle at various points in the network. The software estimates the value of the voltages at every node in the network. The results showed good correlation between estimated and measured voltages: other findings are reported. Recommendations for further work are made including development of a full commercial system. The study was conducted by Econnect Ltd under contract to the DTI.

  12. Fiber-wireless convergence in next-generation communication networks systems, architectures, and management

    CERN Document Server

    Chang, Gee-Kung; Ellinas, Georgios

    2017-01-01

    This book investigates new enabling technologies for Fi-Wi convergence. The editors discuss Fi-Wi technologies at the three major network levels involved in the path towards convergence: system level, network architecture level, and network management level. The main topics will be: a. At system level: Radio over Fiber (digitalized vs. analogic, standardization, E-band and beyond) and 5G wireless technologies; b. Network architecture level: NGPON, WDM-PON, BBU Hotelling, Cloud Radio Access Networks (C-RANs), HetNets. c. Network management level: SDN for convergence, Next-generation Point-of-Presence, Wi-Fi LTE Handover, Cooperative MultiPoint. • Addresses the Fi-Wi convergence issues at three different levels, namely at the system level, network architecture level, and network management level • Provides approaches in communication systems, network architecture, and management that are expected to steer the evolution towards fiber-wireless convergence • Contributions from leading experts in the field of...

  13. Ethernet-Based Services for Next Generation Networks

    Science.gov (United States)

    Hernandez-Valencia, Enrique

    Over the last few years, Ethernet technology and services have emerged as an indispensable component of the broadband networking and telecommunications infrastructure, both for network operators and service providers. As an example, Worldwide Enterprise customer demand for Ethernet services by itself is expected to hit the 30B US mark by year 2012. Use of Ethernet technology in the feeder networks that support residential applications, such as "triple play" voice, data, and video services, is equally on the rise. As the synergies between packet-aware transport and service oriented equipment continue to be exploited in the path toward transport convergence. Ethernet technology is expected to play a critical part in the evolution toward converged Optical/Packet Transport networks. Here we discuss the main business motivations, services, and technologies driving the specifications of so-called carrier Ethernet and highlight challenges associated with delivering the expectations for low implementation complexity, easy of use, provisioning and management of networks and network elements embracing this technology.

  14. Novel mechanism of network protection against the new generation of cyber attacks

    Science.gov (United States)

    Milovanov, Alexander; Bukshpun, Leonid; Pradhan, Ranjit

    2012-06-01

    A new intelligent mechanism is presented to protect networks against the new generation of cyber attacks. This mechanism integrates TCP/UDP/IP protocol stack protection and attacker/intruder deception to eliminate existing TCP/UDP/IP protocol stack vulnerabilities. It allows to detect currently undetectable, highly distributed, low-frequency attacks such as distributed denial-of-service (DDoS) attacks, coordinated attacks, botnet, and stealth network reconnaissance. The mechanism also allows insulating attacker/intruder from the network and redirecting the attack to a simulated network acting as a decoy. As a result, network security personnel gain sufficient time to defend the network and collect the attack information. The presented approach can be incorporated into wireless or wired networks that require protection against known and the new generation of cyber attacks.

  15. Radio-location of mobile stations in third generation networks

    Directory of Open Access Journals (Sweden)

    Milan Manojle Šunjevarić

    2013-06-01

    Full Text Available Mobile station localization in mobile networks started with simple methods (e.g. Cell-ID method which required only slight modifications of network infrastructures. Principally, it was about network localization by which a localization service became available to all types of mobile phones. Due to low precision, the initiated development of more sophisticated methods has not been finished yet. Among the advanced location-based methods are those based on the measurement of location parameters in the time domain. In this paper the general consideration of radio location methods in 3G (UMTS radio networks is presented. The use of time based measurement methods was analysed in detail. Due to the limited article length, the use of other locating methods in 3G networks (based on power measurements, on radio direction measurement, and on cells identification – Cell ID and global positioning system - GPS are not described. Introduction Mobile station localization within modern cellular networks increases the level of user security and opens wide opportunities for commercial operators who provide this service. The major obstacle for the implementation of this service, which also prevents its practical usage, is the modification of the existing network infrastructure. In general, depending on the infrastructure used, positioning methods can be divided into two groups: integrated and independent. Integrated methods are primarily created for communication networks. A possibility to locate users represents just an additional service within a radio network. Independent methods are totally detached from the communication network in which the user whose location is being determined is. Radio location methods Determining the location of a mobile radio station is performed by determining the intersection of two or more lines of position. These lines represent the position of the set of points at which the mobile station may be located. These lines can be: (a

  16. Didactic Networks: A Proposal for e-learning Content Generation

    Directory of Open Access Journals (Sweden)

    F. Javier Del Alamo

    2010-12-01

    Full Text Available The Didactic Networks proposed in this paper are based on previous publications in the field of the RSR (Rhetorical-Semantic Relations. The RSR is a set of primitive relations used for building a specific kind of semantic networks for artificial intelligence applications on the web: the RSN (Rhetorical-Semantic Networks. We bring into focus the RSR application in the field of elearning, by defining Didactic Networks as a new set of semantic patterns oriented to the development of elearning applications. The different lines we offer in our research fall mainly into three levels: (1 The most basic one is in the field of computational linguistics and related to Logical Operations on RSR (RSR Inverses and plurals, RSR combinations, etc, once they have been created. The application of Walter Bosma's results regarding rhetorical distance application and treatment as semantic weighted networks is one of the important issues here. (2 In parallel, we have been working on the creation of a knowledge representation and storage model and data architecture capable of supporting the definition of knowledge networks based on RSR. (3 The third strategic line is in the meso-level, the formulation of a molecular structure of knowledge based on the most frequently used patterns. The main contribution at this level is the set of Fundamental Cognitive Networks (FCN as an application of Novak's mental maps proposal. This paper is part of this third intermediate level, and the Fundamental Didactic Networks (FDN are the result of the application of rhetorical theory procedures to the instructional theory. We have formulated a general set of RSR capable of building discourse, making it possible to express any concept, procedure or principle in terms of knowledge nodes and RSRs. The Instructional knowledge can then be elaborated in the same way. This network structure expressing the instructional knowledge in terms of RSR makes the objective of developing web

  17. Dynamic Session-Key Generation for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Cheng-Ta Li

    2008-09-01

    Full Text Available Recently, wireless sensor networks have been used extensively in different domains. For example, if the wireless sensor node of a wireless sensor network is distributed in an insecure area, a secret key must be used to protect the transmission between the sensor nodes. Most of the existing methods consist of preselecting m keys from a key pool and forming a key chain. Then, the sensor nodes make use of the key chain to encrypt the data. However, while the secret key is being transmitted, it can easily be exposed during transmission. We propose a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods. Additionally, the dynamic update of the key can lower the probability of the key to being guessed correctly. In addition, with the new protocol, attacks on the wireless sensor network can be avoided.

  18. Dynamic Session-Key Generation for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chen Chin-Ling

    2008-01-01

    Full Text Available Abstract Recently, wireless sensor networks have been used extensively in different domains. For example, if the wireless sensor node of a wireless sensor network is distributed in an insecure area, a secret key must be used to protect the transmission between the sensor nodes. Most of the existing methods consist of preselecting keys from a key pool and forming a key chain. Then, the sensor nodes make use of the key chain to encrypt the data. However, while the secret key is being transmitted, it can easily be exposed during transmission. We propose a dynamic key management protocol, which can improve the security of the key juxtaposed to existing methods. Additionally, the dynamic update of the key can lower the probability of the key to being guessed correctly. In addition, with the new protocol, attacks on the wireless sensor network can be avoided.

  19. Virtual networks pluralistic approach for the next generation of Internet

    CERN Document Server

    Duarte, Otto Carlos M B

    2013-01-01

    The first chapter of this title concerns virtualization techniques that allow sharing computational resources basically, slicing a real computational environment into virtual computational environments that are isolated from one another.The Xen and OpenFlow virtualization platforms are then presented in Chapter 2 and a performance analysis of both is provided. This chapter also defines the primitives that the network virtualization infrastructure must provide for allowing the piloting plane to manage virtual network elements.Following this, interfaces for system management of the two platform

  20. Next-generation science information network for leading-edge applications

    Energy Technology Data Exchange (ETDEWEB)

    Urushidani, S. [National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo 101-8430 (Japan)], E-mail: urushi@nii.ac.jp; Matsukata, J. [National Institute of Informatics, 2-1-2 Hitotsubashi Chiyoda-ku, Tokyo 101-8430 (Japan)

    2008-04-15

    High-speed networks are definitely essential tools for leading-edge applications in many research areas, including nuclear fusion research. This paper describes a number of advanced features in the Japanese next-generation science information network, called SINET3, and gives researchers clues on the uses of advanced high-speed network for their applications. The network services have four categories, multiple layer transfer, enriched virtual private network, enhanced quality-of-service, and bandwidth on demand services, and comprise a versatile service platform. The paper also describes the network architecture and advanced networking capabilities that enable economical service accommodation and flexible network resource assignment as well as effective use of Japan's first 40-Gbps lines.

  1. Next-generation science information network for leading-edge applications

    International Nuclear Information System (INIS)

    Urushidani, S.; Matsukata, J.

    2008-01-01

    High-speed networks are definitely essential tools for leading-edge applications in many research areas, including nuclear fusion research. This paper describes a number of advanced features in the Japanese next-generation science information network, called SINET3, and gives researchers clues on the uses of advanced high-speed network for their applications. The network services have four categories, multiple layer transfer, enriched virtual private network, enhanced quality-of-service, and bandwidth on demand services, and comprise a versatile service platform. The paper also describes the network architecture and advanced networking capabilities that enable economical service accommodation and flexible network resource assignment as well as effective use of Japan's first 40-Gbps lines

  2. Increasing penetration of renewable and distributed electricity generation and the need for different network regulation

    International Nuclear Information System (INIS)

    Joode, J. de; Jansen, J.C.; Welle, A.J. van der; Scheepers, M.J.J.

    2009-01-01

    The amount of decentralised electricity generation (DG) connected to distribution networks increases across EU member states. This increasing penetration of DG units poses potential costs and benefits for distribution system operators (DSOs). These DSOs are regulated since the business of electricity distribution is considered to be a natural monopoly. This paper identifies the impact of increasing DG penetration on the DSO business under varying parameters (network characteristics, DG technologies, network management type) and argues that current distribution network regulation needs to be improved in order for DSOs to continue to facilitate the integration of DG in the network. Several possible adaptations are analysed.

  3. Integration of a network aware traffic generation device into a computer network emulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2014-07-01

    Full Text Available offer a repeatable, controllable environment that can easily be modified, but lacks realism through the use of simplified and approximated models (Wei & Mirkovic, 2006). The natural trade-off between these two extremes is network emulation... platforms. Network emulation platforms offer an acceptable amount of realism and hardware requirements, as well as multiple virtual network devices that can easily be reconfigured expanded. Therefore network emulation is an attractive and cost...

  4. The Impact of Distributed Generation on Distribution Networks ...

    African Journals Online (AJOL)

    Their advantages are the ability to reduce or postpone the need for investment in the transmission and distribution infrastructure when optimally located; the ability to reduce technical losses within the transmission and distribution networks as well as general improvement in power quality and system reliability. This paper ...

  5. Perspectives on next-generation technology for environmental sensor networks

    Science.gov (United States)

    Barbara J. Benson; Barbara J. Bond; Michael P. Hamilton; Russell K. Monson; Richard. Han

    2009-01-01

    Sensor networks promise to transform and expand environmental science. However, many technological difficulties must be overcome to achieve this potential. Partnerships of ecologists with computer scientists and engineers are critical in meeting these challenges. Technological issues include promoting innovation in new sensor design, incorporating power optimization...

  6. Generating Predictive Movie Recommendations from Trust in Social Networks

    National Research Council Canada - National Science Library

    Golbeck, Jennifer

    2006-01-01

    .... Using the FilmTrust system as a foundation, they show that these recommendations are more accurate than other techniques when the user's opinions about a film are divergent from the average. They discuss this technique both as an application of social network analysis and how it suggests other analyses that can be performed to help improve collaborative filtering algorithms of all types.

  7. Detection of mobile user location on next generation wireless networks

    DEFF Research Database (Denmark)

    Schou, Saowanee; Olesen, Henning

    2005-01-01

    of a Mobile IPv6 device can be determined by mapping the geographical location information with the two care-of-addresses and the physical address of the access point where the user is connected. Such a mechanism makes location services for mobile entities available on a global IP network. The end-users can...

  8. Reconfiguration of sustainable thermoelectric generation using wireless sensor network

    DEFF Research Database (Denmark)

    Chen, Min

    2014-01-01

    wireless sensor networks (WSNs), where remotely deployed temperature and voltage sensors as well as latching relays can be organized as a whole to intelligently identify and execute the optimal interconnection of TEM strings. A reconfigurable TEM array with a WSN controller and a maximum power point...

  9. Optimal placement of distributed generation in distribution networks ...

    African Journals Online (AJOL)

    This paper proposes the application of Particle Swarm Optimization (PSO) technique to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses and enhancement in voltage profile. In the first segment, the optimal ...

  10. Power generation using photovoltaic induction in an isolated power network

    International Nuclear Information System (INIS)

    Kalantar, M.; Jiang, J.

    2001-01-01

    Owing to increased emphasis on renewable resources, the development of suitable isolated power generators driven by energy sources, the development of suitable isolated power generators driven by energy sources such as photovoltaic, wind, small hydroelectric, biogas and etc. has recently assumed greater significance. A single phase capacitor self excited induction generator has emerged as a suitable candidate of isolated power sources. This paper presents performance analysis of a single phase self-excited induction generator driven by photovoltaic (P V) system for low power isolated stand-alone applications. A single phase induction machine can work as a self-excited induction generator when its rotor is driven at suitable speed by an photovoltaic powered do motor. Its excitation is provided by connecting a single phase capacitor bank at a stator terminals. Either to augment grid power or to get uninterrupted power during grid failure stand-alone low capacity ac generators are used. These are driven by photovoltaic, wind power or I C engines using kerosene, diesel, petrol or biogas as fuel. Self-excitation with capacitors at the stator terminals of the stator terminals of the induction machines is well demonstrated experimentally on a P V powered dc motor-induction machine set. The parameters and the excitation requirements of the induction machine run in self-excited induction generator mode are determined. The effects of variations in prime mover speed,terminal capacitance and load power factor on the machine terminal voltage are studied

  11. The generation of random directed networks with prescribed 1-node and 2-node degree correlations

    Energy Technology Data Exchange (ETDEWEB)

    Zamora-Lopez, Gorka; Kurths, Juergen [Institute of Physics, University of Potsdam, PO Box 601553, 14415 Potsdam (Germany); Zhou Changsong [Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong (China); Zlatic, Vinko [Rudjer Boskovic Institute, PO Box 180, HR-10002 Zagreb (Croatia)

    2008-06-06

    The generation of random networks is a very common problem in complex network research. In this paper, we have studied the correlation nature of several real networks and found that, typically, a large number of links are deterministic, i.e. they cannot be randomized. This finding permits fast generation of ensembles of maximally random networks with prescribed 1-node and 2-node degree correlations. When the introduction of self-loops or multiple-links are not desired, random network generation methods typically reach blocked states. Here, a mechanism is proposed, the 'force-and-drop' method, to overcome such states. Our algorithm can be easily simplified for undirected graphs and reduced to account for any subclass of 2-node degree correlations.

  12. Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

    Science.gov (United States)

    Zulai, Luis G. T.; Durand, Fábio R.; Abrão, Taufik

    2015-05-01

    In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.

  13. Enabling Energy-Efficient and Backhaul-aware Next Generation Heterogeneous Networks

    OpenAIRE

    Prasad, Athul

    2015-01-01

    Heterogeneous networks have been firmly established as the direction in which next-generation cellular networks are evolving. We consider the dense deployment of small cells to provide enhanced capacity, while the macro cells provide wide area coverage. With the development of dual connectivity technology, deploying small cells on dedicated carriers has become an attractive option, with enhanced flexibility for splitting traffic within the network. The power consumption and latency requiremen...

  14. Energy Efficiency and Load Balancing in Next-Generation Wireless Cellular Networks

    OpenAIRE

    Davaslioglu, Kemal

    2015-01-01

    This dissertation focuses on the resource allocation problem in next-generation cellular wireless networks. Our goal is to design and evaluate algorithms and procedures to provide a balanced load and to improve the energy-efficiency of these networks, while satisfying the quality-of-service constraints of the users. The contributions of this dissertation are (i) a new handover policy to balance the load in Long Term Evolution (LTE) Heterogeneous Networks (HetNets), (ii) an analytical characte...

  15. Next generation network based carrier ethernet test bed for IPTV traffic

    DEFF Research Database (Denmark)

    Fu, Rong; Berger, Michael Stübert; Zheng, Yu

    2009-01-01

    This paper presents a Carrier Ethernet (CE) test bed based on the Next Generation Network (NGN) framework. After the concept of CE carried out by Metro Ethernet Forum (MEF), the carrier-grade Ethernet are obtaining more and more interests and being investigated as the low cost and high performanc...... services of transport network to carry the IPTV traffic. This test bed is approaching to support the research on providing a high performance carrier-grade Ethernet transport network for IPTV traffic....

  16. Techno Generation: Social Networking amongst Youth in South Africa

    Science.gov (United States)

    Basson, Antoinette; Makhasi, Yoliswa; van Vuuren, Daan

    Internet and cell phones can be considered as new media compared to traditional media types and have become a fundamental part of the lives of many young people across the globe. The exploratory research study investigated the diffusion and adoption of new media innovations among adolescents. It was found that new media have diffused at a high rate among South African adolescents who are not only the innovators in this area, but also changing their life styles to adapt to the new media. Social networking grew to prominence in South Africa especially among the youth. The protection of children from potential harmful exposure and other risks remain a concern and adequate measures need to be initiated and implemented for children to enjoy social networks and other forms of new media. The exploratory research study provided worthwhile and interesting insights into the role of the new media, in the lives of adolescents in South Africa.

  17. Social network indices in the Generations and Gender Survey: An appraisal

    Directory of Open Access Journals (Sweden)

    Pearl A. Dykstra

    2016-06-01

    Full Text Available Background: In this contribution we critically appraise the social network indices in the Generations and Gender Survey (GGS. Objective: After discussing the rationale for including social network indices in the GGS, we provide descriptive information on social network characteristics and an overview of substantive questions that have been addressed using GGS social network data: antecedents and consequences of demographic behaviour, care, and differences in well-being. We identify topics that have received relatively little attention in GGS research so far, despite the availability of novel and appropriate social network data. We end with a discussion of what is unique about the social network indices in the GGS. Methods: The descriptive information on social network characteristics is based on empirical analyses of GGS data, and an experimental pilot study. The overview of GGS research using social network indices is based on a library search. The identification of what is unique about the social network indices in the GGS is based on a comparison with the European Quality of Life Survey (EQLS, the Survey of Health, Ageing and Retirement (SHARE, and the International Social Survey Program (ISSP. Results: Results show a high representation of family members in the social networks, and confirm the adequacy of using a cap of five names for network-generating questions. GGS research using the social network indices has largely focused on determinants of fertility behaviour, intergenerational linkages in families, and downward care transfers. Conclusions: Topics that have received relatively little attention are demographic behaviours other than those related to parenthood, upward transfers of practical support, ties with siblings, and stepfamily ties. Social network indices in the GGS show a high degree of overlap with those in other international surveys. The unique features are the inventory of family ties ever born and still living, and the

  18. Sequential Triangle Strip Generator based on Hopfield Networks

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří; Lněnička, Radim

    2009-01-01

    Roč. 21, č. 2 (2009), s. 583-617 ISSN 0899-7667 R&D Projects: GA MŠk(CZ) 1M0545; GA AV ČR 1ET100300517; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10300504; CEZ:AV0Z10750506 Keywords : sequential triangle strip * combinatorial optimization * Hopfield network * minimum energy * simulated annealing Subject RIV: IN - Informatics, Computer Science Impact factor: 2.175, year: 2009

  19. Gene regulation networks generate diverse pigmentation patterns in plants.

    Science.gov (United States)

    Albert, Nick W; Davies, Kevin M; Schwinn, Kathy E

    2014-01-01

    The diversity of pigmentation patterns observed in plants occurs due to the spatial distribution and accumulation of colored compounds, which may also be associated with structural changes to the tissue. Anthocyanins are flavonoids that provide red/purple/blue coloration to plants, often forming complex patterns such as spots, stripes, and vein-associated pigmentation, particularly in flowers. These patterns are determined by the activity of MYB-bHLH-WDR (MBW) transcription factor complexes, which activate the anthocyanin biosynthesis genes, resulting in anthocyanin pigment accumulation. Recently, we established that the MBW complex controlling anthocyanin synthesis acts within a gene regulation network that is conserved within at least the Eudicots. This network involves hierarchy, reinforcement, and feedback mechanisms that allow for stringent and responsive regulation of the anthocyanin biosynthesis genes. The gene network and mobile nature of the WDR and R3-MYB proteins provide exciting new opportunities to explore the basis of pigmentation patterning, and to investigate the evolutionary history of the MBW components in land plants.

  20. Remote control of respiratory neural network by spinal locomotor generators.

    Directory of Open Access Journals (Sweden)

    Jean-Patrick Le Gal

    Full Text Available During exercise and locomotion, breathing rate rapidly increases to meet the suddenly enhanced oxygen demand. The extent to which direct central interactions between the spinal networks controlling locomotion and the brainstem networks controlling breathing are involved in this rhythm modulation remains unknown. Here, we show that in isolated neonatal rat brainstem-spinal cord preparations, the increase in respiratory rate observed during fictive locomotion is associated with an increase in the excitability of pre-inspiratory neurons of the parafacial respiratory group (pFRG/Pre-I. In addition, this locomotion-induced respiratory rhythm modulation is prevented both by bilateral lesion of the pFRG region and by blockade of neurokinin 1 receptors in the brainstem. Thus, our results assign pFRG/Pre-I neurons a new role as elements of a previously undescribed pathway involved in the functional interaction between respiratory and locomotor networks, an interaction that also involves a substance P-dependent modulating mechanism requiring the activation of neurokinin 1 receptors. This neurogenic mechanism may take an active part in the increased respiratory rhythmicity produced at the onset and during episodes of locomotion in mammals.

  1. An Expanded Study of Net Generation Perceptions on Privacy and Security on Social Networking Sites (SNS)

    Science.gov (United States)

    Lawler, James P.; Molluzzo, John C.; Doshi, Vijal

    2012-01-01

    Social networking on the Internet continues to be a frequent avenue of communication, especially among Net Generation consumers, giving benefits both personal and professional. The benefits may be eventually hindered by issues in information gathering and sharing on social networking sites. This study evaluates the perceptions of students taking a…

  2. Privacy and Generation Y: Applying Library Values to Social Networking Sites

    Science.gov (United States)

    Fernandez, Peter

    2010-01-01

    Librarians face many challenges when dealing with issues of privacy within the mediated space of social networking sites. Conceptually, social networking sites differ from libraries on privacy as a value. Research about Generation Y students, the primary clientele of undergraduate libraries, can inform librarians' relationship to this important…

  3. Fluid power network for centralized electricity generation in offshore wind farms

    NARCIS (Netherlands)

    Jarquin-Laguna, A.

    2014-01-01

    An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network.

  4. A Dialectic Analysis of Generativity: Issues of Network-Supported Design in Mathematics and Science

    Science.gov (United States)

    Stroup, Walter M.; Ares, Nancy M.; Hurford, Andrew C.

    2005-01-01

    New theoretical, methodological, and design frameworks for engaging classroom learning are supported by the highly interactive and group-centered capabilities of a new generation of classroom-based networks. In our analyses, networked teaching and learning are organized relative to a dialectic of (a) seeing mathematical and scientific structures…

  5. The default network and self-generated thought: component processes, dynamic control, and clinical relevance

    Science.gov (United States)

    Andrews-Hanna, Jessica R.; Smallwood, Jonathan; Spreng, R. Nathan

    2014-01-01

    Though only a decade has elapsed since the default network was first emphasized as being a large-scale brain system, recent years have brought great insight into the network’s adaptive functions. A growing theme highlights the default network as playing a key role in internally-directed—or self-generated—thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the default network. First, we present evidence that self-generated thought is a multi-faceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the default network, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced. PMID:24502540

  6. Generating prior probabilities for classifiers of brain tumours using belief networks

    Directory of Open Access Journals (Sweden)

    Arvanitis Theodoros N

    2007-09-01

    Full Text Available Abstract Background Numerous methods for classifying brain tumours based on magnetic resonance spectra and imaging have been presented in the last 15 years. Generally, these methods use supervised machine learning to develop a classifier from a database of cases for which the diagnosis is already known. However, little has been published on developing classifiers based on mixed modalities, e.g. combining imaging information with spectroscopy. In this work a method of generating probabilities of tumour class from anatomical location is presented. Methods The method of "belief networks" is introduced as a means of generating probabilities that a tumour is any given type. The belief networks are constructed using a database of paediatric tumour cases consisting of data collected over five decades; the problems associated with using this data are discussed. To verify the usefulness of the networks, an application of the method is presented in which prior probabilities were generated and combined with a classification of tumours based solely on MRS data. Results Belief networks were constructed from a database of over 1300 cases. These can be used to generate a probability that a tumour is any given type. Networks are presented for astrocytoma grades I and II, astrocytoma grades III and IV, ependymoma, pineoblastoma, primitive neuroectodermal tumour (PNET, germinoma, medulloblastoma, craniopharyngioma and a group representing rare tumours, "other". Using the network to generate prior probabilities for classification improves the accuracy when compared with generating prior probabilities based on class prevalence. Conclusion Bayesian belief networks are a simple way of using discrete clinical information to generate probabilities usable in classification. The belief network method can be robust to incomplete datasets. Inclusion of a priori knowledge is an effective way of improving classification of brain tumours by non-invasive methods.

  7. Choice set generation in multi-modal transportation networks

    NARCIS (Netherlands)

    Fiorenzo-Catalano, M.S.

    2007-01-01

    Multi-modal transport relates to trips for which travellers use two or more transport modes, for example bicycle and train, train and bus, or private car and metro. The main theme in this dissertation is to establish a choice set generation model and algorithm, and demonstrate its validity and

  8. Centralized electricity generation in offshore wind farms using hydraulic networks

    NARCIS (Netherlands)

    Jarquin Laguna, A.

    2017-01-01

    The work presented in this thesis explores a new way of generation, collection and transmission of wind energy inside a wind farm, in which the electrical conversion does not occur during any intermediate conversion step before the energy has reached the offshore central platform. A centralized

  9. Learning Orthographic Structure with Sequential Generative Neural Networks

    Science.gov (United States)

    Testolin, Alberto; Stoianov, Ivilin; Sperduti, Alessandro; Zorzi, Marco

    2016-01-01

    Learning the structure of event sequences is a ubiquitous problem in cognition and particularly in language. One possible solution is to learn a probabilistic generative model of sequences that allows making predictions about upcoming events. Though appealing from a neurobiological standpoint, this approach is typically not pursued in…

  10. Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

    International Nuclear Information System (INIS)

    Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

    2007-11-01

    The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

  11. A generative modeling approach to connectivity-Electrical conduction in vascular networks

    DEFF Research Database (Denmark)

    Hald, Bjørn Olav

    2016-01-01

    The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... generative approach to connectivity based on the observation that biological organization is hierarchical and composed of a limited set of building blocks, i.e. a vascular network consists of blood vessels which in turn are composed by one or more cell types. Fast electrical communication is crucial...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...

  12. Method of derivation and differentiation of mouse embryonic stem cells generating synchronous neuronal networks.

    Science.gov (United States)

    Gazina, Elena V; Morrisroe, Emma; Mendis, Gunarathna D C; Michalska, Anna E; Chen, Joseph; Nefzger, Christian M; Rollo, Benjamin N; Reid, Christopher A; Pera, Martin F; Petrou, Steven

    2018-01-01

    Stem cells-derived neuronal cultures hold great promise for in vitro disease modelling and drug screening. However, currently stem cells-derived neuronal cultures do not recapitulate the functional properties of primary neurons, such as network properties. Cultured primary murine neurons develop networks which are synchronised over large fractions of the culture, whereas neurons derived from mouse embryonic stem cells (ESCs) display only partly synchronised network activity and human pluripotent stem cells-derived neurons have mostly asynchronous network properties. Therefore, strategies to improve correspondence of derived neuronal cultures with primary neurons need to be developed to validate the use of stem cell-derived neuronal cultures as in vitro models. By combining serum-free derivation of ESCs from mouse blastocysts with neuronal differentiation of ESCs in morphogen-free adherent culture we generated neuronal networks with properties recapitulating those of mature primary cortical cultures. After 35days of differentiation ESC-derived neurons developed network activity very similar to that of mature primary cortical neurons. Importantly, ESC plating density was critical for network development. Compared to the previously published methods this protocol generated more synchronous neuronal networks, with high similarity to the networks formed in mature primary cortical culture. We have demonstrated that ESC-derived neuronal networks recapitulating key properties of mature primary cortical networks can be generated by optimising both stem cell derivation and differentiation. This validates the approach of using ESC-derived neuronal cultures for disease modelling and in vitro drug screening. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. A Methodology for Physical Interconnection Decisions of Next Generation Transport Networks

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Madsen, Ole Brun

    2011-01-01

    The physical interconnection for optical transport networks has critical relevance in the overall network performance and deployment costs. As telecommunication services and technologies evolve, the provisioning of higher capacity and reliability levels is becoming essential for the proper...... of possibilities when designing the physical network interconnection. This paper develops and presents a methodology in order to deal with aspects related to the interconnection problem of optical transport networks. This methodology is presented as independent puzzle pieces, covering diverse topics going from...... development of Next Generation Networks. Currently, there is a lack of specific procedures that describe the basic guidelines to design such networks better than "best possible performance for the lowest investment". Therefore, the research from different points of view will allow a broader space...

  14. Generation of tunable and pulsatile concentration gradients via microfluidic network

    KAUST Repository

    Zhou, Bingpu

    2014-06-04

    We demonstrate a compact Polydimethylsiloxane microfluidic chip which can quickly generate ten different chemical concentrations simultaneously. The concentration magnitude of each branch can be flexibly regulated based on the flow rate ratios of the two injecting streams. The temporal/pulsatile concentration gradients are achieved by integrating on-chip pneumatic actuated valves controlled by the external signals. The temporal concentration gradients can also be tuned precisely by varying applied frequency and duty cycle of the trigger signal. It is believed that such microdevice will be potentially used for some application areas of producing stable chemical gradients as well as allowing fast, pulsatile gradient transformation in seconds.

  15. Physical layer secret key generation for fiber-optical networks.

    Science.gov (United States)

    Kravtsov, Konstantin; Wang, Zhenxing; Trappe, Wade; Prucnal, Paul R

    2013-10-07

    We propose and experimentally demonstrate a method for generating and sharing a secret key using phase fluctuations in fiber optical links. The obtained key can be readily used to support secure communication between the parties. The security of our approach is based on a fundamental asymmetry associated with the optical physical layer: the sophistication of tools needed by an eavesdropping adversary to subvert the key establishment is significantly greater and more costly than the complexity needed by the legitimate parties to implement the scheme. In this sense, the method is similar to the classical asymmetric algorithms (Diffie-Hellman, RSA, etc.).

  16. Network Dynamics: Modeling And Generation Of Very Large Heterogeneous Social Networks

    Science.gov (United States)

    2015-11-23

    target with the largest degree (greedy choice), or the target whose degree is not the largest ( meek choice). The resulting network exhibits a non...not the largest ( meek choice). The resulting network may have either: 1 DISTRIBUTION A: Distribution approved for public release. (i) a non-universal...largest degree node, the 3rd largest, . . . , to the smallest-degree node. These meek choice models all exhibit a double-exponential degree

  17. Creating, generating and comparing random network models with NetworkRandomizer [version 3; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Gabriele Tosadori

    2017-11-01

    Full Text Available Biological networks are becoming a fundamental tool for the investigation of high-throughput data in several fields of biology and biotechnology. With the increasing amount of information, network-based models are gaining more and more interest and new techniques are required in order to mine the information and to validate the results. To fill the validation gap we present an app, for the Cytoscape platform, which aims at creating randomised networks and randomising existing, real networks. Since there is a lack of tools that allow performing such operations, our app aims at enabling researchers to exploit different, well known random network models that could be used as a benchmark for validating real, biological datasets. We also propose a novel methodology for creating random weighted networks, i.e. the multiplication algorithm, starting from real, quantitative data. Finally, the app provides a statistical tool that compares real versus randomly computed attributes, in order to validate the numerical findings. In summary, our app aims at creating a standardised methodology for the validation of the results in the context of the Cytoscape platform.

  18. Physician directed networks: the new generation of managed care.

    Science.gov (United States)

    Bennett, T; O'Sullivan, D

    1996-07-01

    The external pressure to reduce cost while maintaining quality and services is moving the whole industry into a rapid mode of integration. Hospitals, vendors, MCOs, and now, physicians, are faced with the difficult decisions concerning how their operations will be integrated into the larger health care delivery system. These pressures have forced physicians to consolidate, build leverage, and create efficiencies to become more productive; thereby better positioning themselves to respond to the challenges and the opportunities that lie before them. This initial phase of consolidation has given many physicians the momentum to begin to wrestle back the control of health care and the courage to design the next generation of managed care: Physician Directed Managed Care. What will be the next phase? Perhaps, the next step will be fully-integrated specialty and multi-specialty groups leading to alternate delivery sites. "Everyone thinks of changing the world, but no one thinks of changing himself." - Leo Tolstoy

  19. Synchronous ethernet and IEEE 1588 in telecoms next generation synchronization networks

    CERN Document Server

    2013-01-01

    This book addresses the multiple technical aspects of the distribution of synchronization in new generation telecommunication networks, focusing in particular on synchronous Ethernet and IEEE1588 technologies. Many packet network engineers struggle with understanding the challenges that precise synchronization distribution can impose on networks. The usual “why”, “when” and particularly “how” can cause problems for many engineers. In parallel to this, some other markets have identical synchronization requirements, but with their own design requirements, generating further questions. This book attempts to respond to the different questions by providing background technical information. Invaluable information on state of-the-art packet network synchronization and timing architectures is provided, as well as an unbiased view on the synchronization technologies that have been internationally standardized over recent years, with the aim of providing the average reader (who is not skilled in the art) wi...

  20. Development of dielectrophoresis MEMS device for PC12 cell patterning to elucidate nerve-network generation

    Science.gov (United States)

    Nakamachi, Eiji; Koga, Hirotaka; Morita, Yusuke; Yamamoto, Koji; Sakamoto, Hidetoshi

    2018-01-01

    We developed a PC12 cell trapping and patterning device by combining the dielectrophoresis (DEP) methodology and the micro electro mechanical systems (MEMS) technology for time-lapse observation of morphological change of nerve network to elucidate the generation mechanism of neural network. We succeeded a neural network generation, which consisted of cell body, axon and dendrites by using tetragonal and hexagonal cell patterning. Further, the time laps observations was carried out to evaluate the axonal extension rate. The axon extended in the channel and reached to the target cell body. We found that the shorter the PC12 cell distance, the less the axonal connection time in both tetragonal and hexagonal structures. After 48 hours culture, a maximum success rate of network formation was 85% in the case of 40 μm distance tetragonal structure.

  1. Training algorithms evaluation for artificial neural network to temporal prediction of photovoltaic generation

    International Nuclear Information System (INIS)

    Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto

    2016-01-01

    Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.

  2. Investment coordination in network industries. The case of electricity grid and electricity generation

    Energy Technology Data Exchange (ETDEWEB)

    Hoeffler, Felix [Koeln Univ. (Germany). Energiewirtschaftliches Inst.; Max-Planck-Institute for Research on Collective Goods, Bonn (Germany); Wambach, Achim [Cologne Univ. (Germany). Dept. of Economics

    2013-06-15

    Liberalization of network industries frequently separates the network from the other parts of the industry. This is important in particular for the elec- tricity industry where private firms invest into generation facilities, while network investments usually are controlled by regulators. We discuss two regulatory regimes. First, the regulator can only decide on the network extension. Second, she can additionally use a ''capacity market'' with payments contingent on private generation investment. For the first case, we find that even absent asymmetric information, a lack of regulatory commitment can cause inefficiently high or inefficiently low investments. For the second case, we develop a standard handicap auction which implements the first best under asymmetric information, if there are no shadow costs of public funds. With shadow costs, no simple mechanism can implement the second best outcome.

  3. ONU power saving modes in next generation optical access networks: progress, efficiency and challenges.

    Science.gov (United States)

    Dixit, Abhishek; Lannoo, Bart; Colle, Didier; Pickavet, Mario; Demeester, Piet

    2012-12-10

    The optical network unit (ONU), installed at a customer's premises, accounts for about 60% of power in current fiber-to-the-home (FTTH) networks. We propose a power consumption model for the ONU and evaluate the ONU power consumption in various next generation optical access (NGOA) architectures. Further, we study the impact of the power savings of the ONU in various low power modes such as power shedding, doze and sleep.

  4. Impact of Next Generation District Heating Systems on Distribution Network Heat Losses: A Case Study Approach

    Science.gov (United States)

    Li, Yu; Rezgui, Yacine

    2018-01-01

    District heating (DH) is a promising energy pathway to alleviate environmental negative impacts induced by fossil fuels. Improving the performance of DH systems is one of the major challenges facing its wide adoption. This paper discusses the heat losses of the next generation DH based on the constructed Simulink model. Results show that lower distribution temperature and advanced insulation technology greatly reduce network heat losses. Also, the network heat loss can be further minimized by a reduction of heat demand in buildings.

  5. Robust network oscillations during mammalian respiratory rhythm generation driven by synaptic dynamics

    Science.gov (United States)

    Guerrier, Claire; Hayes, John A.; Fortin, Gilles; Holcman, David

    2015-01-01

    How might synaptic dynamics generate synchronous oscillations in neuronal networks? We address this question in the preBötzinger complex (preBötC), a brainstem neural network that paces robust, yet labile, inspiration in mammals. The preBötC is composed of a few hundred neurons that alternate bursting activity with silent periods, but the mechanism underlying this vital rhythm remains elusive. Using a computational approach to model a randomly connected neuronal network that relies on short-term synaptic facilitation (SF) and depression (SD), we show that synaptic fluctuations can initiate population activities through recurrent excitation. We also show that a two-step SD process allows activity in the network to synchronize (bursts) and generate a population refractory period (silence). The model was validated against an array of experimental conditions, which recapitulate several processes the preBötC may experience. Consistent with the modeling assumptions, we reveal, by electrophysiological recordings, that SF/SD can occur at preBötC synapses on timescales that influence rhythmic population activity. We conclude that nondeterministic neuronal spiking and dynamic synaptic strengths in a randomly connected network are sufficient to give rise to regular respiratory-like rhythmic network activity and lability, which may play an important role in generating the rhythm for breathing and other coordinated motor activities in mammals. PMID:26195782

  6. Generation of artificial accelerograms using neural networks for data of Iran

    International Nuclear Information System (INIS)

    Bargi, Kh.; Loux, C.; Rohani, H.

    2002-01-01

    A new method for generation of artificial earthquake accelerograms from response spectra is proposed by Ghaboussi and Lin in 1997 using neural networks. In this paper the methodology has been extended and enhanced for data of Iran. For this purpose, first 40 records of Iran acceleration is chosen, then an RBF neural network which called generalized regression neural network learn the inverse mapping directly from the response spectrum to the Discrete Cosine Transform of accelerograms. Discrete Cosine Transform has been used as an assisting device to extract the content of frequency domain. Learning of network is reasonable and a generalized regression neural network learns it in a few second. Outputs are presented to demonstrate the performance of this method and show its capabilities

  7. A Comparative Study of Multiplexing Schemes for Next Generation Optical Access Networks

    Science.gov (United States)

    Imtiaz, Waqas A.; Khan, Yousaf; Shah, Pir Mehar Ali; Zeeshan, M.

    2014-09-01

    Passive optical network (PON) is a high bandwidth, economical solution which can provide the necessary bandwidth to end-users. Wavelength division multiplexed passive optical networks (WDM PONs) and time division multiplexed passive optical networks (TDM PONs) are considered as an evolutionary step for next-generation optical access (NGOA) networks. However they fail to provide highest transmission capacity, efficient bandwidth access, and robust dispersion tolerance. Thus future PONs are considered on simpler, efficient and potentially scalable, optical code division multiplexed (OCDM) PONs. This paper compares the performance of existing PONs with OCDM PON to determine a suitable scheme for NGOA networks. Two system parameter are used in this paper: fiber length, and bit rate. Performance analysis using Optisystem shows that; for a sufficient system performance parameters i.e. bit error rate (BER) ≤ 10-9, and maximum quality factor (Q) ≥ 6, OCDMA PON efficiently performs upto 50 km with 10 Gbit/s per ONU.

  8. Effect of placement of droop based generators in distribution network on small signal stability margin and network loss

    DEFF Research Database (Denmark)

    Dheer, D.K.; Doolla, S.; Bandyopadhyay, S.

    2017-01-01

    loss and stability margin is further investigated by identifying the Pareto fronts for modified IEEE 13 bus, IEEE 33 and practical 22-bus radial distribution network with application of Reference point based Non-dominated Sorting Genetic Algorithm (R-NSGA). Results were validated by time domain......For a utility-connected system, issues related to small signal stability with Distributed Generators (DGs) are insignificant due to the presence of a very strong grid. Optimally placed sources in utility connected microgrid system may not be optimal/stable in islanded condition. Among others issues......, small signal stability margin is on the fore. The present research studied the effect of location of droop-controlled DGs on small signal stability margin and network loss on a modified IEEE 13 bus system, an IEEE 33-bus distribution system and a practical 22-bus radial distribution network. A complete...

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

    International Nuclear Information System (INIS)

    Kinzel, Wolfgang; Kanter, Ido

    2003-01-01

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

  10. Carrier ethernet network control plane based on the Next Generation Network

    DEFF Research Database (Denmark)

    Fu, Rong; Wang, Yanmeng; Berger, Michael Stubert

    2008-01-01

    architecture. The approaches to QoS mapping, label distribution and connection and admission control (CAC) are specified here. At last, a simple T-MPLS based Carrier Ethernet network model with three kinds of users (VoIP, VoD and HTTP) and a RACE based control module is simulated in OPNET. The model is aiming...

  11. Minimum-block-generated flexible-grouping-based spectrum assignment for flex-grid optical networks

    Science.gov (United States)

    Qiu, Yang; Xu, Jing

    2017-11-01

    We investigate the spectrum fragmentation issue in flex-grid optical networks and propose a minimum-block-generated flexible-grouping-based spectrum assignment algorithm. By dividing the spectrum resources into several flexible groups according to the bandwidth requirements of service requests for their accommodation and minimizing the generated isolated spectrum blocks inside each spectrum group, the proposed algorithm can not only reduce spectrum fragments but also enhance networking performance (e.g. blocking probability) due to the improved spectrum contiguity inside each spectrum group with no traffic disruption or any extra components. The simulation results verify that the proposed algorithm can remarkably reduce spectrum fragments with a low blocking probability.

  12. Assessment of energy supply and continuity of service in distribution network with renewable distributed generation

    International Nuclear Information System (INIS)

    Abdullah, M.A.; Agalgaonkar, A.P.; Muttaqi, K.M.

    2014-01-01

    Highlights: • Difficulties in assessing distribution network adequacy with DG are addressed. • Indices are proposed to assess adequacy of energy supply and service continuity. • Analytical methodology is developed to assess the proposed indices. • Concept of joint probability distribution of demand and generation is applied. - Abstract: Continuity of electricity supply with renewable distributed generation (DG) is a topical issue for distribution system planning and operation, especially due to the stochastic nature of power generation and time varying load demand. The conventional adequacy and reliability analysis methods related to bulk generation systems cannot be applied directly for the evaluation of adequacy criteria such as ‘energy supply’ and ‘continuity of service’ for distribution networks embedded with renewable DG. In this paper, new indices highlighting ‘available supply capacity’ and ‘continuity of service’ are proposed for ‘energy supply’ and ‘continuation of service’ evaluation of generation-rich distribution networks, and analytical techniques are developed for their quantification. A probability based analytical method has been developed using the joint probability of the demand and generation, and probability distributions of the proposed indices have been used to evaluate the network adequacy in energy supply and service continuation. A data clustering technique has been used to evaluate the joint probability between coincidental demand and renewable generation. Time sequential Monte Carlo simulation has been used to compare the results obtained using the proposed analytical method. A standard distribution network derived from Roy Billinton test system and a practical radial distribution network have been used to test the proposed method and demonstrate the estimation of the well-being of a system for hosting renewable DG units. It is found that renewable DG systems improve the ‘energy supply’ and

  13. The Global Seismographic Network (GSN): Deployment of Next Generation VBB Borehole Sensors and Improving Overall Network Noise Performance

    Science.gov (United States)

    Hafner, K.; Davis, P.; Wilson, D.; Sumy, D.

    2017-12-01

    The Global Seismographic Network (GSN) recently received delivery of the next generation Very Broadband (VBB) borehole sensors purchased through funding from the DOE. Deployment of these sensors will be underway during the end of summer and fall of 2017 and they will eventually replace the aging KS54000 sensors at approximately one-third of the GSN network stations. We will present the latest methods of deploying these sensors in the existing deep boreholes. To achieve lower noise performance at some sites, emplacement in shallow boreholes might result in lower noise performance for the existing site conditions. In some cases shallow borehole installations may be adapted to vault stations (which make up two thirds of the network), as a means of reducing tilt-induced signals on the horizontal components. The GSN is creating a prioritized list of equipment upgrades at selected stations with the ultimate goal of optimizing overall network data availability and noise performance. For an overview of the performance of the current GSN relative to selected set of metrics, we are utilizing data quality metrics and Probability Density Functions (PDFs)) generated by the IRIS Data Management Centers' (DMC) MUSTANG (Modular Utility for Statistical Knowledge Gathering) and LASSO (Latest Assessment of Seismic Station Observations) tools. We will present our metric analysis of GSN performance in 2016, and show the improvements at GSN sites resulting from recent instrumentation and infrastructure upgrades.

  14. Modeling generator power plant portfolios and pollution taxes in electric power supply chain networks: a transportation network equilibrium transformation

    International Nuclear Information System (INIS)

    Kai Wu; Nagurney, A.; University of Massachusetts, Amherst, MA; Zugang Liu; Stranlund, J.K.

    2006-01-01

    Global climate change and fuel security risks have encouraged international and regional adoption of pollution/carbon taxes. A major portion of such policy interventions is directed at the electric power industry with taxes applied according to the type of fuel used by the power generators in their power plants. This paper proposes an electric power supply chain network model that captures the behavior of power generators faced with a portfolio of power plant options and subject to pollution taxes. We demonstrate that this general model can be reformulated as a transportation network equilibrium model with elastic demands and qualitatively analyzed and solved as such. The connections between these two different modeling schemas is done through finite-dimensional variational inequality theory. The numerical examples illustrate how changes in the pollution/carbon taxes affect the equilibrium electric power supply chain network production outputs, the transactions between the various decision-makers the demand market prices, as well as the total amount of carbon emissions generated. (author)

  15. Wind-generator influence to the power quality in the coupling point to the distribution network

    Directory of Open Access Journals (Sweden)

    Kostić Branka B.

    2011-01-01

    Full Text Available The paper presents the results of analysis of wind-generator and their influence to the power quality parameters in the coupling point to the distribution network. The specified results should be used as a starting point for distribution system operators (DSO for issuing permit for connecting renewable sources, mainly for wind-generators. As the case study, the results of measurements at the only one wind generator installed in Serbia, near town of Tutin, are used. The cases of wind-generator start and stop during low wind and consequently smaller value of the energy delivered to the network are particularly analyzed. Taking into consideration that law regulations in this field are not yet defined, EU standards and guidelines are used along with the newly adopted Technical recommendation No. 16 of Public Enterprise Electric Power Industry of Serbia.

  16. Lewis Research Center studies of multiple large wind turbine generators on a utility network

    Science.gov (United States)

    Gilbert, L. J.; Triezenberg, D. M.

    1979-01-01

    A NASA-Lewis program to study the anticipated performance of a wind turbine generator farm on an electric utility network is surveyed. The paper describes the approach of the Lewis Wind Energy Project Office to developing analysis capabilities in the area of wind turbine generator-utility network computer simulations. Attention is given to areas such as, the Lewis Purdue hybrid simulation, an independent stability study, DOE multiunit plant study, and the WEST simulator. Also covered are the Lewis mod-2 simulation including analog simulation of a two wind turbine system and comparison with Boeing simulation results, and gust response of a two machine model. Finally future work to be done is noted and it is concluded that the study shows little interaction between the generators and between the generators and the bus.

  17. Characterisation of Large Disturbance Rotor Angle and Voltage Stability in Interconnected Power Networks with Distributed Wind Generation

    OpenAIRE

    Meegahapola, Lasantha; Littler, Timothy

    2015-01-01

    Wind generation in highly interconnected power networks creates local and centralised stability issues based on their proximity to conventional synchronous generators and load centres. This paper examines the large disturbance stability issues (i.e. rotor angle and voltage stability) in power networks with geographically distributed wind resources in the context of a number of dispatch scenarios based on profiles of historical wind generation for a real power network. Stability issues have be...

  18. Quality of Service for Real-Time Applications Over Next Generation Data Networks

    Science.gov (United States)

    Atiquzzaman, Mohammed; Jain, Raj

    2001-01-01

    This project, which started on January 1, 2000, was funded by the NASA Glenn Research Center for duration of one year. The deliverables of the project included the following tasks: (1) Study of QoS mapping between the edge and core networks envisioned in the Next Generation networks will provide us with the QoS guarantees that can be obtained from next generation networks; (2) Buffer management techniques to provide strict guarantees to real-time end-to-end applications through preferential treatment to packets belonging to real-time applications. In particular, use of ECN to help reduce the loss on high bandwidth-delay product satellite networks needs to be studied; (3) Effect of Prioritized Packet Discard to increase goodput of the network and reduce the buffering requirements in the ATM switches; (4) Provision of new IP circuit emulation services over Satellite IP backbones using MPLS will be studied; and (5) Determine the architecture and requirements for internetworking ATN and the Next Generation Internet for real-time applications. The project has been completed on time. All the objectives and deliverables of the project have been completed. Research results obtained from this project have been published in a number of papers in journals, conferences, and technical reports, included in this document.

  19. Two critical brain networks for generation and combination of remote associations.

    Science.gov (United States)

    Bendetowicz, David; Urbanski, Marika; Garcin, Béatrice; Foulon, Chris; Levy, Richard; Bréchemier, Marie-Laure; Rosso, Charlotte; Thiebaut de Schotten, Michel; Volle, Emmanuelle

    2018-01-01

    Recent functional imaging findings in humans indicate that creativity relies on spontaneous and controlled processes, possibly supported by the default mode and the fronto-parietal control networks, respectively. Here, we examined the ability to generate and combine remote semantic associations, in relation to creative abilities, in patients with focal frontal lesions. Voxel-based lesion-deficit mapping, disconnection-deficit mapping and network-based lesion-deficit approaches revealed critical prefrontal nodes and connections for distinct mechanisms related to creative cognition. Damage to the right medial prefrontal region, or its potential disrupting effect on the default mode network, affected the ability to generate remote ideas, likely by altering the organization of semantic associations. Damage to the left rostrolateral prefrontal region and its connections, or its potential disrupting effect on the left fronto-parietal control network, spared the ability to generate remote ideas but impaired the ability to appropriately combine remote ideas. Hence, the current findings suggest that damage to specific nodes within the default mode and fronto-parietal control networks led to a critical loss of verbal creative abilities by altering distinct cognitive mechanisms. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. Probing Rubber Cross-Linking Generation of Industrial Polymer Networks at Nanometer Scale.

    Science.gov (United States)

    Gabrielle, Brice; Gomez, Emmanuel; Korb, Jean-Pierre

    2016-06-23

    We present improved analyses of rheometric torque measurements as well as (1)H double-quantum (DQ) nuclear magnetic resonance (NMR) buildup data on polymer networks of industrial compounds. This latter DQ NMR analysis allows finding the distribution of an orientation order parameter (Dres) resulting from the noncomplete averaging of proton dipole-dipole couplings within the cross-linked polymer chains. We investigate the influence of the formulation (filler and vulcanization systems) as well as the process (curing temperature) ending to the final polymer network. We show that DQ NMR follows the generation of the polymer network during the vulcanization process from a heterogeneous network to a very homogeneous one. The time variations of microscopic Dres and macroscopic rheometric torques present power-law behaviors above a threshold time scale with characteristic exponents of the percolation theory. We observe also a very good linear correlation between the kinetics of Dres and rheometric data routinely performed in industry. All these observations confirm the description of the polymer network generation as a critical phenomenon. On the basis of all these results, we believe that DQ NMR could become a valuable tool for investigating in situ the cross-linking of industrial polymer networks at the nanometer scale.

  1. Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

    DEFF Research Database (Denmark)

    Soares, Tiago; Faria, Pedro; Vale, Zita

    2014-01-01

    The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...

  2. Modeling the video distribution link in the Next Generation Optical Access Networks

    DEFF Research Database (Denmark)

    Amaya, F.; Cárdenas, A.; Tafur Monroy, Idelfonso

    2011-01-01

    In this work we present a model for the design and optimization of the video distribution link in the next generation optical access network. We analyze the video distribution performance in a SCM-WDM link, including the noise, the distortion and the fiber optic nonlinearities. Additionally, we...

  3. On the Potential of PUF for Pseudonym Generation in Vehicular Networks

    NARCIS (Netherlands)

    Petit, Jonathan; Bösch, C.T.; Feiri, Michael; Kargl, Frank

    2012-01-01

    Most proposals for security of vehicular networks foresee the generation of a comparatively large number of changing pseudonyms to prevent vehicles from being identified or tracked. Most proposals rely on communication with backend pseudonym providers to refill a vehicle’s pseudonym pool which

  4. Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    Sloep, P. B. (2009). Innovation as a distributed, collaborative process of knowledge generation: open, networked innovation. In V. Hornung-Prähauser & M. Luckmann (Eds.), Kreativität und Innovationskompetenz im digitalen Netz - Creativity and Innovation Competencies in the Web, Sammlung von

  5. Challenges to the Learning Organization in the Context of Generational Diversity and Social Networks

    Science.gov (United States)

    Kaminska, Renata; Borzillo, Stefano

    2018-01-01

    Purpose: The purpose of this paper is to gain a better understanding of the challenges to the emergence of a learning organization (LO) posed by a context of generational diversity and an enterprise social networking system (ESNS). Design/methodology/approach: This study uses a qualitative methodology based on an analysis of 20 semi-structured…

  6. Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing

    Science.gov (United States)

    Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.

    2006-05-01

    Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.

  7. Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

    Science.gov (United States)

    Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

    2018-02-01

    Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

  8. Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

    DEFF Research Database (Denmark)

    Soares, Tiago; Faria, Pedro; Vale, Zita

    2014-01-01

    The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...

  9. Methodology for calculating the impact of distributed generation on energy losses in a distribution network

    Directory of Open Access Journals (Sweden)

    Perić Jelena

    2013-01-01

    Full Text Available This paper is the result of the Master's final project 'Methodology for calculating the impact of distributed generation on energy losses in distribution network'. The question is whether, for estimation of the impact of the power plant on energy losses in the distribution network, it is necessary to analyze each hour value of small power plant engagement and its effect, or it is sufficient to analyze a small number of states, and the extent to which it is possible to reduce the number of states that will be analyzed in order to review adequately the impact of the power plant on the change of energy losses in the network. To answer this question, an algorithm consisting of two steps is performed, annual production diagrams are obtained and, on the basis of calculated specific discrete values, the impact of the small power plant on energy losses in the distribution network to which it is connected is evaluated.

  10. Comprehensive evaluation of impacts of distributed generation integration in distribution network

    Science.gov (United States)

    Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu

    2018-04-01

    All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.

  11. A Network Traffic Generator Model for Fast Network-on-Chip Simulation

    DEFF Research Database (Denmark)

    Mahadevan, Shankar; Angiolini, Frederico; Storgaard, Michael

    2005-01-01

    For Systems-on-Chip (SoCs) development, a predominant part of the design time is the simulation time. Performance evaluation and design space exploration of such systems in bit- and cycle-true fashion is becoming prohibitive. We propose a traffic generation (TG) model that provides a fast...

  12. Network Regulation and Support Schemes - How Policy Interactions Affect the Integration of Distributed Generation

    DEFF Research Database (Denmark)

    Ropenus, Stephanie; Jacobsen, Henrik; Schröder, Sascha Thorsten

    2011-01-01

    This article seeks to investigate the interactions between the policy dimensions of support schemes and network regulation and how they affect distributed generation. Firstly, the incentives of distributed generators and distribution system operators are examined. Frequently there exists a trade......-off between the incentives for these two market agents to facilitate the integration of distributed generation. Secondly, the interaction of these policy dimensions is analyzed, including case studies based on five EU Member States. Aspects of operational nature and investments in grid and distributed...

  13. Reconstruction of three-dimensional porous media using generative adversarial neural networks

    Science.gov (United States)

    Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J.

    2017-10-01

    To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

  14. Reconstruction of three-dimensional porous media using generative adversarial neural networks.

    Science.gov (United States)

    Mosser, Lukas; Dubrule, Olivier; Blunt, Martin J

    2017-10-01

    To evaluate the variability of multiphase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the variability in the inherent material properties is often experimentally not feasible. We present a method to reconstruct the solid-void structure of porous media by applying a generative neural network that allows an implicit description of the probability distribution represented by three-dimensional image data sets. We show, by using an adversarial learning approach for neural networks, that this method of unsupervised learning is able to generate representative samples of porous media that honor their statistics. We successfully compare measures of pore morphology, such as the Euler characteristic, two-point statistics, and directional single-phase permeability of synthetic realizations with the calculated properties of a bead pack, Berea sandstone, and Ketton limestone. Results show that generative adversarial networks can be used to reconstruct high-resolution three-dimensional images of porous media at different scales that are representative of the morphology of the images used to train the neural network. The fully convolutional nature of the trained neural network allows the generation of large samples while maintaining computational efficiency. Compared to classical stochastic methods of image reconstruction, the implicit representation of the learned data distribution can be stored and reused to generate multiple realizations of the pore structure very rapidly.

  15. Pricing of embedded generation: Incorporation of externalities and avoided network losses

    International Nuclear Information System (INIS)

    Rodrigo, Asanka S.; Wijayatunga, Priyantha D.C.

    2007-01-01

    Traditionally, the electricity purchase tariff of embedded generators reflected only the cost of production and delivery of electricity to the consumers, which includes the costs of labor, capital, operation, taxes and insurance. However, the production of electricity causes adverse impacts on the environment. At present, this issue has not been widely addressed by the existing pricing methodologies. This paper proposes a pricing methodology for renewable energy based embedded electricity generation, incorporating the cost of externalities with a case study on the Sri Lanka power system. It recommends that the embedded generation tariff be based on the principle of 'avoided cost', considering the cost of energy production, cost of externalities and the cost of network losses. While the 'impact path way' approach is proposed for calculation of the cost of externalities of energy, the nodal-based cost calculation is proposed for the avoided cost of network losses calculation. The pricing methodology proposed in the paper provides important information for investors when choosing the most economical site for their development. It can also be used to optimize the network use. These will allow the developers of embedded generation facilities and the utilities operating the national grid to maximize the potential of embedded generation. (author)

  16. Power Electronic Systems for Switched Reluctance Generator based Wind Farms and DC Networks

    DEFF Research Database (Denmark)

    Park, Kiwoo

    . Under these circumstances, research on dc network connection with a novel wind power generator system is presented in this thesis, which mainly consists of two major parts: control of a Switched Reluctance Generator (SRG) system and development of dc-dc converters for a dc network system in a wind farm...... for generators in wind turbine systems. However, despite all these advantageous features, the SRG has not been widely employed in wind energy applications. The most renowned technical disadvantages of the SRG are its nonlinearity and high torque ripples, which should be overcome to promote the application...... are presented to verify the feasibility and operational principles of the proposed converters. Finally, modelling and control of a dc-grid wind farm using one of the proposed dc-dc converters are presented. An average model provides insight into the overall performance of the system. Meanwhile, a switching...

  17. Fatigue damage of steam turbine shaft at asynchronous connections of turbine generator to electrical network

    Science.gov (United States)

    Bovsunovsky, A. P.

    2015-07-01

    The investigations of cracks growth in the fractured turbine rotors point out at theirs fatigue nature. The main reason of turbine shafts fatigue damage is theirs periodical startups which are typical for steam turbines. Each startup of a turbine is accompanied by the connection of turbine generator to electrical network. During the connection because of the phase shift between the vector of electromotive force of turbine generator and the vector of supply-line voltage the short-term but powerful reactive shaft torque arises. This torque causes torsional vibrations and fatigue damage of turbine shafts of different intensity. Based on the 3D finite element model of turbine shaft of the steam turbine K-200-130 and the mechanical properties of rotor steel there was estimated the fatigue damage of the shaft at its torsional vibrations arising as a result of connection of turbine generator to electric network.

  18. Complex network structure of musical compositions: Algorithmic generation of appealing music

    Science.gov (United States)

    Liu, Xiao Fan; Tse, Chi K.; Small, Michael

    2010-01-01

    In this paper we construct networks for music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurring connections. We analyze classical music from Bach, Mozart, Chopin, as well as other types of music such as Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. We conjecture that preserving the universal network properties is a necessary step in artificial composition of music. Power-law exponents of node degree, node strength and/or edge weight distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be composed artificially using a controlled random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. By generating a large number of compositions, we find that this algorithm generates music which has the necessary qualities to be subjectively judged as appealing.

  19. Exploiting Mobile Ad Hoc Networking and Knowledge Generation to Achieve Ambient Intelligence

    Directory of Open Access Journals (Sweden)

    Anna Lekova

    2012-01-01

    Full Text Available Ambient Intelligence (AmI joins together the fields of ubiquitous computing and communications, context awareness, and intelligent user interfaces. Energy, fault-tolerance, and mobility are newly added dimensions of AmI. Within the context of AmI the concept of mobile ad hoc networks (MANETs for “anytime and anywhere” is likely to play larger roles in the future in which people are surrounded and supported by small context-aware, cooperative, and nonobtrusive devices that will aid our everyday life. The connection between knowledge generation and communication ad hoc networking is symbiotic—knowledge generation utilizes ad hoc networking to perform their communication needs, and MANETs will utilize the knowledge generation to enhance their network services. The contribution of the present study is a distributed evolving fuzzy modeling framework (EFMF to observe and categorize relationships and activities in the user and application level and based on that social context to take intelligent decisions about MANETs service management. EFMF employs unsupervised online one-pass fuzzy clustering method to recognize nodes' mobility context from social scenario traces and ubiquitously learn “friends” and “strangers” indirectly and anonymously.

  20. UK scenario of islanded operation of active distribution networks with renewable distributed generators

    Energy Technology Data Exchange (ETDEWEB)

    Chowdhury, S.P.; Chowdhury, S.; Gaunt, C.T. [Electrical Engineering Department, University of Cape Town, Private Bag X3, Rondebosch, Cape Town 7701, Western Cape (South Africa); Crossley, P.A. [Joule Centre for Energy Research, The University of Manchester, M60 1QD (United Kingdom)

    2009-12-15

    This paper reports on the current UK scenario of islanded operation of active distribution networks with renewable distributed generators (RDGs). Different surveys indicate that the present scenario does not economically justify islanding operation of active distribution networks with RDGs. Anti-islanding protection schemes currently enforce the renewable distributed generators (RDGs) to disconnect immediately and stop generation for grid faults through loss of grid (LOG) protection system. This greatly reduces the benefits of RDG deployment. With rising RDG penetration, much benefit would be lost if the RDGs are not allowed to island only due to conventional operational requirement of utilities. For preventing disconnection of RDGs during LOG, several islanding operation, control and protection schemes are being developed. Technical studies clearly indicate the need to review parts of the ESQCR (Electricity Safety, Quality and Continuity Regulations) for successful islanded operations. Commercial viability of islanding operation must be assessed in relation to enhancement of power quality, system reliability and supply of potential ancillary services through network support. Demonstration projects under Registered Power Zone and Technical Architecture Projects should be initiated to investigate the usefulness of DG islanding. However these efforts should be compounded with a realistic judgement of the associated technical and economic issues for the development of future power networks. (author)

  1. Imaging the Where and When of Tic Generation and Resting State Networks in Adult Tourette Patients

    Directory of Open Access Journals (Sweden)

    Irene eNeuner

    2014-05-01

    Full Text Available Introduction: Tourette syndrome (TS is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs via functional magnetic resonance imaging (fMRI.Methods: Tic-related activity and the underlying resting state networks in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of one second duration each to detect prior activation. RSN were identified by independent component analysis (ICA and correlated to disease severity by the means of dual regression.Results: Two seconds before a tic, the supplementary motor area (SMA, ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; one second before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS scores.Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal resting state network activity might contribute to the generation of tics in SMA.

  2. Change in network connectivity during fictive-gasping generation in hypoxia: Prevention by a metabolic intermediate

    Directory of Open Access Journals (Sweden)

    Andrés eNieto-Posadas

    2014-07-01

    Full Text Available The neuronal circuit in charge of generating the respiratory rhythms, localized in the pre-Bötzinger complex (preBötC, is configured to produce fictive-eupnea during normoxia and reconfigures to produce fictive-gasping during hypoxic conditions in vitro. The mechanisms involved in such reconfiguration have been extensively investigated by cell-focused studies, but the actual changes at the network level remain elusive. Since a failure to generate gasping has been linked to Sudden Infant Death Syndrome, the study of gasping generation and pharmacological approaches to promote it may have clinical relevance. Here, we study the changes in network dynamics and circuit reconfiguration that occur during the transition to fictive-gasping generation in the brainstem slice preparation by recording the preBötC with multi-electrode arrays and assessing correlated firing among respiratory neurons or clusters of respiratory neurons (multiunits. We studied whether the respiratory network reconfiguration in hypoxia involves changes in either the number of active respiratory elements, the number of functional connections among elements, or the strength of these connections. Moreover, we tested the influence of isocitrate, a Krebs cycle intermediate that has recently been shown to promote breathing, on the configuration of the preBötC circuit during normoxia and on its reconfiguration during hypoxia. We found that, in contrast to previous suggestions based on cell-focused studies, the number and the overall activity of respiratory neurons change only slightly during hypoxia. However, hypoxia induces a reduction in the strength of functional connectivity within the circuit without reducing the number of connections. Isocitrate prevented this reduction during hypoxia while increasing the strength of network connectivity. In conclusion, we provide an overview of the configuration of the respiratory network under control conditions and how it is reconfigured

  3. Facilitating efficient augmentation of transmission networks to connect renewable energy generation: the Australian experience

    International Nuclear Information System (INIS)

    Wright, Glen

    2012-01-01

    Australia is heavily dependent on coal for electricity generation. The Renewable Energy Target has spurred growth in the utilization of renewable energy sources, with further growth expected into the future. Australia's strongest renewable energy sources are generally distant from the transmission network in resource ‘basins’. Investment is needed to augment the transmission network to enable delivery of electricity from these sources to consumers. Considerable economies of scale flow from anticipating the connection of numerous generators in an area over time and sizing augmentations accordingly. Following a lengthy rulemaking process, the National Electricity Rules were recently amended by a new rule, designed to facilitate the construction of such efficiently sized augmentations. However, the new rule is more conservative than initially envisaged, making little substantive change to the current frameworks for augmentation and connection. This paper outlines these frameworks and the rulemaking process and identifies the key debates surrounding the rule change are identified. This paper then provides a detailed analysis of the new rule, concluding that it is defective in a number of respects and is unlikely to result in the efficient and timely augmentation of the network needed to unlock the potential of Australia's strongest renewable energy resources. - Highlights: ► Remoteness of renewable energy sources is a barrier to greater renewable energy utilization. ► Significant economies of scale flow from efficiently-sized transmission network augmentation. ► Current frameworks in Australia do not incentivise efficiently-sized network augmentations. ► The lack of property rights in an augmentation is particularly problematic. ► The new Scale Efficient Network Extensions rule is not apt to facilitate efficiently-sized network augmentations.

  4. Fluid power network for centralized electricity generation in offshore wind farms

    International Nuclear Information System (INIS)

    Jarquin-Laguna, A

    2014-01-01

    An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network

  5. History of electricity network control and distributed generation in the UK and Western Denmark

    International Nuclear Information System (INIS)

    Lehtonen, Markku; Nye, Sheridan

    2009-01-01

    Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently-largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets-emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives.

  6. History of electricity network control and distributed generation in the UK and Western Denmark

    Energy Technology Data Exchange (ETDEWEB)

    Lehtonen, Markku [Sussex Energy Group, SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom); Nye, Sheridan [SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom)

    2009-06-15

    Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently - largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets - emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives. (author)

  7. State of the art of the virtual utility: the smart distributed generation network

    International Nuclear Information System (INIS)

    Coll-Mayor, D.; Picos, R.; Garcia-Moreno, E.

    2004-01-01

    The world of energy has lately experienced a revolution, and new rules are being defined. The climate change produced by the greenhouse gases, the inefficiency of the energy system or the lack of power supply infrastructure in most of the poor countries, the liberalization of the energy market and the development of new technologies in the field of distributed generation (DG) are the key factors of this revolution. It seems clear that the solution at the moment is the DG. The advantage of DG is the energy generation close to the demand point. It means that DG can lower costs, reduce emissions, or expand the energy options of the consumers. DG may add redundancy that increases grid security even while powering emergency lighting or other critical systems and reduces power losses in the electricity distribution. After the development of the different DG and high efficiency technologies such as co-generation and tri-generation, the next step in the DG world is the interconnection of different small distributed generation facilities which act together in a DG network as a large power plant controlled by a centralized energy management system (EMS). The main aim of the EMS is to reach the targets of low emissions and high efficiency. The EMS gives priority to renewable energy sources instead of the use of fossil fuels. This new concept of energy infrastructure is referred to as virtual utility (VU). The VU can be defined as a new model of energy infrastructure which consists of integrating different kind of distributed generation utilities in an energy (electricity and heat) generation network controlled by a central energy management system (EMS). The electricity production in the network is subordinated to the heat necessity of every user. The thermal energy is consumed on site; the electricity is generated and distributed in the entire network. The network is composed of one centralized control with the EMS and different clusters of distributed generation utilities

  8. 100 Gigabit-per-second: Ultra-high transmission bitrate for next generation optical transport networks

    Science.gov (United States)

    Veith, Gustav; Lach, Eugen; Schuh, Karsten

    2008-11-01

    Modern telecommunication networks have to provide enormous data transport capacity in order to enable the dramatic annual internet traffic growth rates. As an illustration, today some internet exchange nodes partly exhibit annual peak traffic growth rates of more than 200% due to strongly emerging data and broadband video services. This explosion of internet data and video traffic can only be assured by the implementation of the most advanced optical metro and core transport network technologies. It is likely that next generation telecommunication transport networks will be based on 100 Gigabit/s Ethernet (100 GbE) interconnections. Here we will report on the technical challenges and achievements associated with the development of ultra-high speed components and systems for serial 100 Gbit/s optical transmission. To cite this article: G. Veith et al., C. R. Physique 9 (2008).

  9. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks.

    Science.gov (United States)

    Segler, Marwin H S; Kogej, Thierry; Tyrchan, Christian; Waller, Mark P

    2018-01-24

    In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active toward a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target. Against Staphylococcus aureus , the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria), it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecules for drug discovery.

  10. Timetable-based simulation method for choice set generation in large-scale public transport networks

    DEFF Research Database (Denmark)

    Rasmussen, Thomas Kjær; Anderson, Marie Karen; Nielsen, Otto Anker

    2016-01-01

    The composition and size of the choice sets are a key for the correct estimation of and prediction by route choice models. While existing literature has posed a great deal of attention towards the generation of path choice sets for private transport problems, the same does not apply to public...... transport problems. This study proposes a timetable-based simulation method for generating path choice sets in a multimodal public transport network. Moreover, this study illustrates the feasibility of its implementation by applying the method to reproduce 5131 real-life trips in the Greater Copenhagen Area...... and to assess the choice set quality in a complex multimodal transport network. Results illustrate the applicability of the algorithm and the relevance of the utility specification chosen for the reproduction of real-life path choices. Moreover, results show that the level of stochasticity used in choice set...

  11. Robust transient stabilisation problem for a synchronous generator in a power network

    Science.gov (United States)

    Verrelli, C. M.; Damm, G.

    2010-04-01

    The robust transient stabilisation problem (with stability proof€) of a synchronous generator in an uncertain power network with transfer conductances is rigorously formulated and solved. The generator angular speed and electrical power are required to be kept close, when mechanical and electrical perturbations occur, to the synchronous speed and mechanical input power, respectively, while the generator terminal voltage is to be regulated, when perturbations are removed, to its pre-fault reference constant value. A robust adaptive nonlinear feedback control algorithm is designed on the basis of a third-order model of the synchronous machine: only two system parameters (synchronous machine damping and inertia constants) along with upper and lower bounds on the remaining uncertain ones are supposed to be known. The conditions to be satisfied by the remote network dynamics for guaranteeing ℒ2 and ℒ∞ robustness and asymptotic relative speed and voltage regulation to zero are weaker than those required by the single machine-infinite bus approximation: dynamic interactions between the local deviations of the generator states from the corresponding equilibrium values and the remote generators states are allowed.

  12. Migraine generator network and spreading depression dynamics as neuromodulation targets in episodic migraine

    Science.gov (United States)

    Dahlem, Markus A.

    2013-12-01

    Migraine is a common disabling headache disorder characterized by recurrent episodes sometimes preceded or accompanied by focal neurological symptoms called aura. The relation between two subtypes, migraine without aura (MWoA) and migraine with aura (MWA), is explored with the aim to identify targets for neuromodulation techniques. To this end, a dynamically regulated control system is schematically reduced to a network of the trigeminal nerve, which innervates the cranial circulation, an associated descending modulatory network of brainstem nuclei, and parasympathetic vasomotor efferents. This extends the idea of a migraine generator region in the brainstem to a larger network and is still simple and explicit enough to open up possibilities for mathematical modeling in the future. In this study, it is suggested that the migraine generator network (MGN) is driven and may therefore respond differently to different spatio-temporal noxious input in the migraine subtypes MWA and MWoA. The noxious input is caused by a cortical perturbation of homeostasis, known as spreading depression (SD). The MGN might even trigger SD in the first place by a failure in vasomotor control. As a consequence, migraine is considered as an inherently dynamical disease to which a linear course from upstream to downstream events would not do justice. Minimally invasive and noninvasive neuromodulation techniques are briefly reviewed and their rational is discussed in the context of the proposed mechanism.

  13. Next-Generation Environment-Aware Cellular Networks: Modern Green Techniques and Implementation Challenges

    KAUST Repository

    Ghazzai, Hakim

    2016-09-16

    Over the last decade, mobile communications have been witnessing a noteworthy increase of data traffic demand that is causing an enormous energy consumption in cellular networks. The reduction of their fossil fuel consumption in addition to the huge energy bills paid by mobile operators is considered as the most important challenges for the next-generation cellular networks. Although most of the proposed studies were focusing on individual physical layer power optimizations, there is a growing necessity to meet the green objective of fifth-generation cellular networks while respecting the user\\'s quality of service. This paper investigates four important techniques that could be exploited separately or together in order to enable wireless operators achieve significant economic benefits and environmental savings: 1) the base station sleeping strategy; 2) the optimized energy procurement from the smart grid; 3) the base station energy sharing; and 4) the green networking collaboration between competitive mobile operators. The presented simulation results measure the gain that could be obtained using these techniques compared with that of traditional scenarios. Finally, this paper discusses the issues and challenges related to the implementations of these techniques in real environments. © 2016 IEEE.

  14. Universal Intelligent Small Cell (UnISCell for next generation cellular networks

    Directory of Open Access Journals (Sweden)

    Mohammad Patwary

    2016-11-01

    Full Text Available Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.

  15. Adaptive protection coordination scheme for distribution network with distributed generation using ABC

    Directory of Open Access Journals (Sweden)

    A.M. Ibrahim

    2016-09-01

    Full Text Available This paper presents an adaptive protection coordination scheme for optimal coordination of DOCRs in interconnected power networks with the impact of DG, the used coordination technique is the Artificial Bee Colony (ABC. The scheme adapts to system changes; new relays settings are obtained as generation-level or system-topology changes. The developed adaptive scheme is applied on the IEEE 30-bus test system for both single- and multi-DG existence where results are shown and discussed.

  16. Generating social capital in globalised networks for growth and development in nascent entrepreneurial ventures

    OpenAIRE

    Simba, A

    2016-01-01

    Global markets are no longer dominated by multinational enterprises (MNEs) alone, international new ventures (INVs) or born globals are increasingly becoming serious contenders in terms of employment & wealth creation as well as revenue generation. In seeking to penetrate global markets they often rely on their entrepreneurial behaviours. Specifically, these nascent but entrepreneurial firms often take advantage of existing and newly developed networks, both domestically and internationally, ...

  17. eCommerceGAN : A Generative Adversarial Network for E-commerce

    OpenAIRE

    Kumar, Ashutosh; Biswas, Arijit; Sanyal, Subhajit

    2018-01-01

    E-commerce companies such as Amazon, Alibaba and Flipkart process billions of orders every year. However, these orders represent only a small fraction of all plausible orders. Exploring the space of all plausible orders could help us better understand the relationships between the various entities in an e-commerce ecosystem, namely the customers and the products they purchase. In this paper, we propose a Generative Adversarial Network (GAN) for orders made in e-commerce websites. Once trained...

  18. Establishment of a Standard Analytical Model of Distribution Network with Distributed Generators and Development of Multi Evaluation Method for Network Configuration Candidates

    Science.gov (United States)

    Hayashi, Yasuhiro; Kawasaki, Shoji; Matsuki, Junya; Matsuda, Hiroaki; Sakai, Shigekazu; Miyazaki, Teru; Kobayashi, Naoki

    Since a distribution network has many sectionalizing switches, there are huge radial network configuration candidates by states (opened or closed) of sectionalizing switches. Recently, the total number of distributed generation such as photovoltaic generation system and wind turbine generation system connected to the distribution network is drastically increased. The distribution network with the distributed generators must be operated keeping reliability of power supply and power quality. Therefore, the many configurations of the distribution network with the distributed generators must be evaluated multiply from various viewpoints such as distribution loss, total harmonic distortion, voltage imbalance and so on. In this paper, the authors propose a multi evaluation method to evaluate the distribution network configuration candidates satisfied with constraints of voltage and line current limit from three viewpoints ((1) distribution loss, (2) total harmonic distortion and (3) voltage imbalance). After establishing a standard analytical model of three sectionalized and three connected distribution network configuration with distributed generators based on the practical data, the multi evaluation for the established model is carried out by using the proposed method based on EMTP (Electro-Magnetic Transients Programs).

  19. Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

    Directory of Open Access Journals (Sweden)

    J. C. Ochoa-Rivera

    2002-01-01

    Full Text Available A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain, while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2 model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series..

  20. Establishing a National Knowledge Translation and Generation Network in Kidney Disease: The CAnadian KidNey KNowledge TraNslation and GEneration NeTwork

    Directory of Open Access Journals (Sweden)

    Braden Manns

    2014-04-01

    Full Text Available Patients with chronic kidney disease (CKD do not always receive care consistent with guidelines, in part due to complexities in CKD management, lack of randomized trial data to inform care, and a failure to disseminate best practice. At a 2007 conference of key Canadian stakeholders in kidney disease, attendees noted that the impact of Canadian Society of Nephrology (CSN guidelines was attenuated given limited formal linkages between the CSN Clinical Practice Guidelines Group, kidney researchers, decision makers and knowledge users, and that further knowledge was required to guide care in patients with kidney disease. The idea for the Canadian Kidney Knowledge Translation and Generation Network (CANN-NET developed from this meeting. CANN-NET is a pan-Canadian network established in partnership with CSN, the Kidney Foundation of Canada and other professional societies to improve the care and outcomes of patients with and at risk for kidney disease. The initial priority areas for knowledge translation include improving optimal timing of dialysis initiation, and increasing the appropriate use of home dialysis. Given the urgent need for new knowledge, CANN-NET has also brought together a national group of experienced Canadian researchers to address knowledge gaps by encouraging and supporting multicentre randomized trials in priority areas, including management of cardiovascular disease in patients with kidney failure.

  1. Macroporous Double-Network Hydrogel for High-Efficiency Solar Steam Generation Under 1 sun Illumination.

    Science.gov (United States)

    Yin, Xiangyu; Zhang, Yue; Guo, Qiuquan; Cai, Xiaobing; Xiao, Junfeng; Ding, Zhifeng; Yang, Jun

    2018-04-04

    Solar steam generation is one of the most promising solar-energy-harvesting technologies to address the issue of water shortage. Despite intensive efforts to develop high-efficiency solar steam generation devices, challenges remain in terms of the relatively low solar thermal efficiency, complicated fabrications, high cost, and difficulty in scaling up. Herein, a double-network hydrogel with a porous structure (p-PEGDA-PANi) is demonstrated for the first time as a flexible, recyclable, and efficient photothermal platform for low-cost and scalable solar steam generation. As a novel photothermal platform, the p-PEGDA-PANi involves all necessary properties of efficient broadband solar absorption, exceptional hydrophilicity, low heat conductivity, and porous structure for high-efficiency solar steam generation. As a result, the hydrogel-based solar steam generator exhibits a maximum solar thermal efficiency of 91.5% with an evaporation rate of 1.40 kg m -2 h -1 under 1 sun illumination, which is comparable to state-of-the-art solar steam generation devices. Furthermore, the good durability and environmental stability of the p-PEGDA-PANi hydrogel enables a convenient recycling and reusing process toward real-life applications. The present research not only provides a novel photothermal platform for solar energy harvest but also opens a new avenue for the application of the hydrogel materials in solar steam generation.

  2. Latest developments in advanced network management and cross-sharing of next-generation flux stations

    Science.gov (United States)

    Burba, George; Johnson, Dave; Velgersdyk, Michael; Begashaw, Israel; Allyn, Douglas

    2016-04-01

    In recent years, spatial and temporal flux data coverage improved significantly and on multiple scales, from a single station to continental networks, due to standardization, automation, and management of the data collection, and better handling of the extensive amounts of generated data. However, operating budgets for flux research items, such as labor, travel, and hardware, are becoming more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are required to effectively and efficiently handle the entire process, including sharing data among collaborative groups. On one hand, such tools can maximize time dedicated to publications answering research questions, and minimize time and expenses spent on data acquisition, processing, quality control and overall station management. On the other hand, cross-sharing the stations with external collaborators may help leverage available funding, and promote data analyses and publications. A new low-cost, advanced system, FluxSuite, utilizes a combination of hardware, software and web-services to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: (i) The system can be easily incorporated into a new flux station, or as un upgrade to many presently operating flux stations, via weatherized remotely-accessible microcomputer, SmartFlux 2, with fully digital inputs (ii) Each next-generation station will measure all parameters needed for flux computations in a digital and PTP time-synchronized mode, accepting digital signals from a number of anemometers and data loggers (iii) The field microcomputer will calculate final fully-processed flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. (iv) Final fluxes, radiation, weather and soil data will

  3. Comparison by sex between thrombin generation and fibrin network characteristics in a healthy population.

    Science.gov (United States)

    Marchi, R; Marcos, L; Paradisi, I

    2015-02-20

    The aim of the present work was to compare sex differences in thrombin generation and fibrin network characteristics in a young healthy population, and correlate thrombin generation parameters with fibrin network characteristics. Sixty individuals aged 21 y (18-26), 50% men and 50% women were selected. Thrombin generation was performed with the Technothrombin TGA kit. Plasma fibrin formation kinetic was followed by turbidity at 350 nm, and the fibrin elastic modulus was measured with the Hemodyne. In addition, the prothrombin polymorphism G20210A was assessed. Thrombin generation in men was: lag time (LT): 12.5 ± 3.0 min, peak thrombin: 257 ± 135 nmol/l, and endogenous thrombin potential (ETP): 3459 ± 449 nmol/l·min, while in women the LT was shortened (9.7 ± 2.8 min, pgeneration between women and men were not related to prothrombin concentration, prothrombin polymorphism G20210A or fibrinogen concentration. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. A priori data-driven multi-clustered reservoir generation algorithm for echo state network.

    Directory of Open Access Journals (Sweden)

    Xiumin Li

    Full Text Available Echo state networks (ESNs with multi-clustered reservoir topology perform better in reservoir computing and robustness than those with random reservoir topology. However, these ESNs have a complex reservoir topology, which leads to difficulties in reservoir generation. This study focuses on the reservoir generation problem when ESN is used in environments with sufficient priori data available. Accordingly, a priori data-driven multi-cluster reservoir generation algorithm is proposed. The priori data in the proposed algorithm are used to evaluate reservoirs by calculating the precision and standard deviation of ESNs. The reservoirs are produced using the clustering method; only the reservoir with a better evaluation performance takes the place of a previous one. The final reservoir is obtained when its evaluation score reaches the preset requirement. The prediction experiment results obtained using the Mackey-Glass chaotic time series show that the proposed reservoir generation algorithm provides ESNs with extra prediction precision and increases the structure complexity of the network. Further experiments also reveal the appropriate values of the number of clusters and time window size to obtain optimal performance. The information entropy of the reservoir reaches the maximum when ESN gains the greatest precision.

  5. Energy Management Optimization for Cellular Networks under Renewable Energy Generation Uncertainty

    KAUST Repository

    Rached, Nadhir B.

    2017-03-28

    The integration of renewable energy (RE) as an alternative power source for cellular networks has been deeply investigated in literature. However, RE generation is often assumed to be deterministic; an impractical assumption for realistic scenarios. In this paper, an efficient energy procurement strategy for cellular networks powered simultaneously by the smart grid (SG) and locally deployed RE sources characterized by uncertain processes is proposed. For a one-day operation cycle, the mobile operator aims to reduce its total energy cost by optimizing the amounts of energy to be procured from the local RE sources and SG at each time period. Additionally, it aims to determine the amount of extra generated RE to be sold back to SG. A chance constrained optimization is first proposed to deal with the RE generation uncertainty. Then, two convex approximation approaches: Chernoff and Chebyshev methods, characterized by different levels of knowledge about the RE generation, are developed to determine the energy procurement strategy for different risk levels. In addition, their performances are analyzed for various daily scenarios through selected simulation results. It is shown that the higher complex Chernoff method outperforms the Chebyshev one for different risk levels set by the operator.

  6. Imaging the where and when of tic generation and resting state networks in adult Tourette patients

    Science.gov (United States)

    Neuner, Irene; Werner, Cornelius J.; Arrubla, Jorge; Stöcker, Tony; Ehlen, Corinna; Wegener, Hans P.; Schneider, Frank; Shah, N. Jon

    2014-01-01

    Introduction: Tourette syndrome (TS) is a neuropsychiatric disorder with the core phenomenon of tics, whose origin and temporal pattern are unclear. We investigated the When and Where of tic generation and resting state networks (RSNs) via functional magnetic resonance imaging (fMRI). Methods: Tic-related activity and the underlying RSNs in adult TS were studied within one fMRI session. Participants were instructed to lie in the scanner and to let tics occur freely. Tic onset times, as determined by video-observance were used as regressors and added to preceding time-bins of 1 s duration each to detect prior activation. RSN were identified by independent component analysis (ICA) and correlated to disease severity by the means of dual regression. Results: Two seconds before a tic, the supplementary motor area (SMA), ventral primary motor cortex, primary sensorimotor cortex and parietal operculum exhibited activation; 1 s before a tic, the anterior cingulate, putamen, insula, amygdala, cerebellum and the extrastriatal-visual cortex exhibited activation; with tic-onset, the thalamus, central operculum, primary motor and somatosensory cortices exhibited activation. Analysis of resting state data resulted in 21 components including the so-called default-mode network. Network strength in those regions in SMA of two premotor ICA maps that were also active prior to tic occurrence, correlated significantly with disease severity according to the Yale Global Tic Severity Scale (YGTTS) scores. Discussion: We demonstrate that the temporal pattern of tic generation follows the cortico-striato-thalamo-cortical circuit, and that cortical structures precede subcortical activation. The analysis of spontaneous fluctuations highlights the role of cortical premotor structures. Our study corroborates the notion of TS as a network disorder in which abnormal RSN activity might contribute to the generation of tics in SMA. PMID:24904391

  7. Impact of Distributed Generation Grid Code Requirements on Islanding Detection in LV Networks

    Directory of Open Access Journals (Sweden)

    Fabio Bignucolo

    2017-01-01

    Full Text Available The recent growing diffusion of dispersed generation in low voltage (LV distribution networks is entailing new rules to make local generators participate in network stability. Consequently, national and international grid codes, which define the connection rules for stability and safety of electrical power systems, have been updated requiring distributed generators and electrical storage systems to supply stabilizing contributions. In this scenario, specific attention to the uncontrolled islanding issue has to be addressed since currently required anti-islanding protection systems, based on relays locally measuring voltage and frequency, could no longer be suitable. In this paper, the effects on the interface protection performance of different LV generators’ stabilizing functions are analysed. The study takes into account existing requirements, such as the generators’ active power regulation (according to the measured frequency and reactive power regulation (depending on the local measured voltage. In addition, the paper focuses on other stabilizing features under discussion, derived from the medium voltage (MV distribution network grid codes or proposed in the literature, such as fast voltage support (FVS and inertia emulation. Stabilizing functions have been reproduced in the DIgSILENT PowerFactory 2016 software environment, making use of its native programming language. Later, they are tested both alone and together, aiming to obtain a comprehensive analysis on their impact on the anti-islanding protection effectiveness. Through dynamic simulations in several network scenarios the paper demonstrates the detrimental impact that such stabilizing regulations may have on loss-of-main protection effectiveness, leading to an increased risk of unintentional islanding.

  8. An improved scheme of IPI-based entity identifier generation for securing body sensor networks.

    Science.gov (United States)

    Hong, Tian; Bao, Shu-Di; Zhang, Yuan-Ting; Li, Ye; Yang, Ping

    2011-01-01

    Securing body sensor network (BSN) in an efficient manner is very important for preserving the privacy of medical data. Protecting data confidentiality, integrity and to authenticate the communicating nodes are basic requirements to secure BSN. The existing method to generate entity identifier (EI) from inter-pulse intervals (IPIs) of heartbeats has its advantages in authenticating and identifying nodes, which however was found in this study that such generated EIs are not so resistant to attacks because of potential error patterns. This paper presents an improved scheme of IPI-based EI generation to eliminate the error patterns. The performance of randomness and node identification, i.e. false acceptance rate and false rejection rate, is experimentally evaluated. The results indicate that compared with the existing one, the new scheme is effective to eliminate the error patterns and thus more tolerant to attacks, while there is no compromise on the randomness level and identification performance.

  9. Independent power producer parallel operation modeling in transient network simulations for interconnected distributed generation studies

    Energy Technology Data Exchange (ETDEWEB)

    Moura, Fabricio A.M.; Camacho, Jose R. [Universidade Federal de Uberlandia, School of Electrical Engineering, Rural Electricity and Alternative Sources Lab, PO Box 593, 38400.902 Uberlandia, MG (Brazil); Chaves, Marcelo L.R.; Guimaraes, Geraldo C. [Universidade Federal de Uberlandia, School of Electrical Engineering, Power Systems Dynamics Group, PO Box: 593, 38400.902 Uberlandia, MG (Brazil)

    2010-02-15

    The main task in this paper is to present a performance analysis of a distribution network in the presence of an independent power producer (IP) synchronous generator with its speed governor and voltage regulator modeled using TACS -Transient Analysis of Control Systems, for distributed generation studies. Regulators were implemented through their transfer functions in the S domain. However, since ATP-EMTP (Electromagnetic Transient Program) works in the time domain, a discretization is necessary to return the TACS output to time domain. It must be highlighted that this generator is driven by a steam turbine, and the whole system with regulators and the equivalent of the power authority system at the common coupling point (CCP) are modeled in the ''ATP-EMTP -Alternative Transients Program''. (author)

  10. Engineering applications of fpgas chaotic systems, artificial neural networks, random number generators, and secure communication systems

    CERN Document Server

    Tlelo-Cuautle, Esteban; de la Fraga, Luis Gerardo

    2016-01-01

    This book offers readers a clear guide to implementing engineering applications with FPGAs, from the mathematical description to the hardware synthesis, including discussion of VHDL programming and co-simulation issues. Coverage includes FPGA realizations such as: chaos generators that are described from their mathematical models; artificial neural networks (ANNs) to predict chaotic time series, for which a discussion of different ANN topologies is included, with different learning techniques and activation functions; random number generators (RNGs) that are realized using different chaos generators, and discussions of their maximum Lyapunov exponent values and entropies. Finally, optimized chaotic oscillators are synchronized and realized to implement a secure communication system that processes black and white and grey-scale images. In each application, readers will find VHDL programming guidelines and computer arithmetic issues, along with co-simulation examples with Active-HDL and Simulink. Readers will b...

  11. Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

    Science.gov (United States)

    Islam, Mujahidul

    A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable

  12. A neural network driving curve generation method for the heavy-haul train

    Directory of Open Access Journals (Sweden)

    Youneng Huang

    2016-05-01

    Full Text Available The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. First, in order to describe the nonlinear characteristics of train braking, the neural network model is constructed and trained by practical driving data. In the neural network model, various nonlinear neurons are interconnected to work for information processing and transmission. The target value of train braking pressure reduction and release time is achieved by modeling the braking process. The equation of train motion is computed to obtain the driving curve. Finally, in four typical operation scenarios, comparing the curve data generated by the method with corresponding practical data of the Shuohuang heavy-haul railway line, the results show that the method is effective.

  13. Policy and network regulation for the integration of distribution generation and renewables for electricity supply

    International Nuclear Information System (INIS)

    Ten Donkelaar, M.; Van Oostvoorn, F.

    2005-08-01

    This study has analysed the existing policy and regulation aimed at the integration of an increased share of Distributed Generation (DG) in electricity supply systems in the European Union. It illustrates the state of the art and progress in the development of support mechanisms and network regulation for large-scale integration of DG. Through a benchmark study a systematic comparison has been made of different DG support schemes and distribution network regulation in EU Member States to a predefined standard, the level playing field. This level playing field has been defined as the situation where energy markets, policy and regulation provide neutral incentives to central versus distributed generation, which results in an economically more efficient electricity supply to the consumer. In current regulation and policy a certain discrepancy can be noticed between the actual regulation and policy support systems in a number of countries, the medium to long term targets and the ideal situation described according to the level playing field objective. Policies towards DG and RES are now mainly aimed at removing short-term barriers, increasing the production share of DG/RES, but often ignoring the more complex barriers of integrating DG/RES that is created by the economic network regulation in current electricity markets

  14. Distributed generation of shared RSA keys in mobile ad hoc networks

    Science.gov (United States)

    Liu, Yi-Liang; Huang, Qin; Shen, Ying

    2005-12-01

    Mobile Ad Hoc Networks is a totally new concept in which mobile nodes are able to communicate together over wireless links in an independent manner, independent of fixed physical infrastructure and centralized administrative infrastructure. However, the nature of Ad Hoc Networks makes them very vulnerable to security threats. Generation and distribution of shared keys for CA (Certification Authority) is challenging for security solution based on distributed PKI(Public-Key Infrastructure)/CA. The solutions that have been proposed in the literature and some related issues are discussed in this paper. The solution of a distributed generation of shared threshold RSA keys for CA is proposed in the present paper. During the process of creating an RSA private key share, every CA node only has its own private security. Distributed arithmetic is used to create the CA's private share locally, and that the requirement of centralized management institution is eliminated. Based on fully considering the Mobile Ad Hoc network's characteristic of self-organization, it avoids the security hidden trouble that comes by holding an all private security share of CA, with which the security and robustness of system is enhanced.

  15. Business opportunities and dynamic competition through distributed generation in primary electricity distribution networks

    International Nuclear Information System (INIS)

    Raineri, R.; Rios, S.; Vasquez, R.

    2005-01-01

    In this paper, for a real electricity distribution network, an assessment of business opportunities to invest in distributed generation (DG) is performed through a simulation based on a full representation of three medium voltage (12 kV) feeders. The three feeders representation includes 1062 sections of conductors with 13 different sizes. The economic assessment focuses on both, the incentives of the incumbent distribution company and those of a new entrant. The technical and economic impact on losses, reliability and voltage regulation in the network area are verified. The DG solution analyzed determines a business opportunity for new investors where end users are also benefited. This work calls in the debate on the need to reformulate the current regulation model on electricity distribution, by defining clear rules to incorporate DG to the existing network, and to enable any agent to develop the proposed business. DG success depends on the location of adequate sites to strategically establish few DG units being a substitute to network expansion

  16. A Rural Next Generation Network (R-NGN and Its Testbed

    Directory of Open Access Journals (Sweden)

    Armein Z. R. Langi

    2013-09-01

    Full Text Available Rural Next Generation Networks (R-NGN technology allows Internet protocol (IP based systems to be used in rural areas. This paper reports a testbed of R-NGN that uses low cost Ethernet radio links, combined with media gateways and a softswitch. The network consists of point-to-point IP Ethernet 2.4 GHz wireless link, IP switches and gateways in each community, standard copper wires and telephone sets for users. It uses low power consumption, and suitable for low density users. This combination allows low cost systems as well as multiservices (voice, data, and multimedia for rural communications. An infrastructure has been deployed in two communities in Cipicung Girang, a village 10 km outside Bandung city, Indonesia. Two towers link the communities with a network of Institut Teknologi Bandung (ITB campus. In addition, local wirelines connect community houses to the network. Currently there are four houses connected to each community node (for a total of eight house, upon which we can perform various tests and measurements.

  17. A Rural Next Generation Network (R-NGN and Its Testbed

    Directory of Open Access Journals (Sweden)

    Armein Z. R. Langi

    2007-05-01

    Full Text Available Rural Next Generation Networks (R-NGN technology allows Internet protocol (IP based systems to be used in rural areas. This paper reports a testbed of R-NGN that uses low cost Ethernet radio links, combined with media gateways and a softswitch. The network consists of point-to-point IP Ethernet 2.4 GHz wireless link, IP switches and gateways in each community, standard copper wires and telephone sets for users. It uses low power consumption, and suitable for low density users. This combination allows low cost systems as well as multiservices (voice, data, and multimedia for rural communications. An infrastructure has been deployed in two communities in Cipicung Girang, a village 10 km outside Bandung city, Indonesia. Two towers link the communities with a network of Institut Teknologi Bandung (ITB campus. In addition, local wirelines connect community houses to the network. Currently there are four houses connected to each community node (for a total of eight house, upon which we can perform various tests and measurements.

  18. Comparative Study of Neural Network Frameworks for the Next Generation of Adaptive Optics Systems.

    Science.gov (United States)

    González-Gutiérrez, Carlos; Santos, Jesús Daniel; Martínez-Zarzuela, Mario; Basden, Alistair G; Osborn, James; Díaz-Pernas, Francisco Javier; De Cos Juez, Francisco Javier

    2017-06-02

    Many of the next generation of adaptive optics systems on large and extremely large telescopes require tomographic techniques in order to correct for atmospheric turbulence over a large field of view. Multi-object adaptive optics is one such technique. In this paper, different implementations of a tomographic reconstructor based on a machine learning architecture named "CARMEN" are presented. Basic concepts of adaptive optics are introduced first, with a short explanation of three different control systems used on real telescopes and the sensors utilised. The operation of the reconstructor, along with the three neural network frameworks used, and the developed CUDA code are detailed. Changes to the size of the reconstructor influence the training and execution time of the neural network. The native CUDA code turns out to be the best choice for all the systems, although some of the other frameworks offer good performance under certain circumstances.

  19. Physical Layer Secret-Key Generation Scheme for Transportation Security Sensor Network.

    Science.gov (United States)

    Yang, Bin; Zhang, Jianfeng

    2017-06-28

    Wireless Sensor Networks (WSNs) are widely used in different disciplines, including transportation systems, agriculture field environment monitoring, healthcare systems, and industrial monitoring. The security challenge of the wireless communication link between sensor nodes is critical in WSNs. In this paper, we propose a new physical layer secret-key generation scheme for transportation security sensor network. The scheme is based on the cooperation of all the sensor nodes, thus avoiding the key distribution process, which increases the security of the system. Different passive and active attack models are analyzed in this paper. We also prove that when the cooperative node number is large enough, even when the eavesdropper is equipped with multiple antennas, the secret-key is still secure. Numerical results are performed to show the efficiency of the proposed scheme.

  20. Tri Band Dual Polarized Patch Antenna System For Next Generation Cellular Networks

    Directory of Open Access Journals (Sweden)

    Syed Daniyal Ali Shah

    2017-12-01

    Full Text Available In fifth generation networks much emphasis is given to reduce the handset and base station sizes while incorporating even more features for ubiquitous connectivity. Polarization diversity is one of the methods in which a single multi-polarized antenna brings the advantages of antenna diversity. The multiband handset antennas can be made dual-polarized for improved compensation of fading effects of propagation environment especially in terrestrial bands. This paper focuses on the outcomes of the development of a horizontal and vertical polarized patch antenna scheme that operates on 3 bands 900 MHz 1.8 GHz and 2.4 GHz. The antenna system is tested for gain directivity reflection loss polarization radiation pattern and other parameters. The results are published and found are found to satisfy the requirements of cellular and data communication networks in the specified bands.

  1. Battery-free Wireless Sensor Network For Advanced Fossil-Fuel Based Power Generation

    Energy Technology Data Exchange (ETDEWEB)

    Yi Jia

    2011-02-28

    This report summarizes technical progress achieved during the project supported by the Department of Energy under Award Number DE-FG26-07NT4306. The aim of the project was to conduct basic research into battery-free wireless sensing mechanism in order to develop novel wireless sensors and sensor network for physical and chemical parameter monitoring in a harsh environment. Passive wireless sensing platform and five wireless sensors including temperature sensor, pressure sensor, humidity sensor, crack sensor and networked sensors developed and demonstrated in our laboratory setup have achieved the objective for the monitoring of various physical and chemical parameters in a harsh environment through remote power and wireless sensor communication, which is critical to intelligent control of advanced power generation system. This report is organized by the sensors developed as detailed in each progress report.

  2. Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Zhi He

    2017-10-01

    Full Text Available Classification of hyperspectral image (HSI is an important research topic in the remote sensing community. Significant efforts (e.g., deep learning have been concentrated on this task. However, it is still an open issue to classify the high-dimensional HSI with a limited number of training samples. In this paper, we propose a semi-supervised HSI classification method inspired by the generative adversarial networks (GANs. Unlike the supervised methods, the proposed HSI classification method is semi-supervised, which can make full use of the limited labeled samples as well as the sufficient unlabeled samples. Core ideas of the proposed method are twofold. First, the three-dimensional bilateral filter (3DBF is adopted to extract the spectral-spatial features by naturally treating the HSI as a volumetric dataset. The spatial information is integrated into the extracted features by 3DBF, which is propitious to the subsequent classification step. Second, GANs are trained on the spectral-spatial features for semi-supervised learning. A GAN contains two neural networks (i.e., generator and discriminator trained in opposition to one another. The semi-supervised learning is achieved by adding samples from the generator to the features and increasing the dimension of the classifier output. Experimental results obtained on three benchmark HSI datasets have confirmed the effectiveness of the proposed method , especially with a limited number of labeled samples.

  3. Flexibility of the axial central pattern generator network for locomotion in the salamander.

    Science.gov (United States)

    Ryczko, D; Knüsel, J; Crespi, A; Lamarque, S; Mathou, A; Ijspeert, A J; Cabelguen, J M

    2015-03-15

    In tetrapods, limb and axial movements are coordinated during locomotion. It is well established that inter- and intralimb coordination show considerable variations during ongoing locomotion. Much less is known about the flexibility of the axial musculoskeletal system during locomotion and the neural mechanisms involved. Here we examined this issue in the salamander Pleurodeles waltlii, which is capable of locomotion in both aquatic and terrestrial environments. Kinematics of the trunk and electromyograms from the mid-trunk epaxial myotomes were recorded during four locomotor behaviors in freely moving animals. A similar approach was used during rhythmic struggling movements since this would give some insight into the flexibility of the axial motor system. Our results show that each of the forms of locomotion and the struggling behavior is characterized by a distinct combination of mid-trunk motor patterns and cycle durations. Using in vitro electrophysiological recordings in isolated spinal cords, we observed that the spinal networks activated with bath-applied N-methyl-d-aspartate could generate these axial motor patterns. In these isolated spinal cord preparations, the limb motor nerve activities were coordinated with each mid-trunk motor pattern. Furthermore, isolated mid-trunk spinal cords and hemicords could generate the mid-trunk motor patterns. This indicates that each side of the cord comprises a network able to generate coordinated axial motor activity. The roles of descending and sensory inputs in the behavior-related changes in axial motor coordination are discussed. Copyright © 2015 the American Physiological Society.

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

    Directory of Open Access Journals (Sweden)

    Gwinn Marta

    2007-06-01

    web-based prototype capable of creating domain-specific investigator networks based on an application that accurately generates detailed investigator profiles from PubMed abstracts combined with robust standard vocabularies. This approach could be used for other biomedical fields to efficiently establish domain-specific investigator networks.

  5. Multiple ECG Fiducial Points-Based Random Binary Sequence Generation for Securing Wireless Body Area Networks.

    Science.gov (United States)

    Zheng, Guanglou; Fang, Gengfa; Shankaran, Rajan; Orgun, Mehmet A; Zhou, Jie; Qiao, Li; Saleem, Kashif

    2017-05-01

    Generating random binary sequences (BSes) is a fundamental requirement in cryptography. A BS is a sequence of N bits, and each bit has a value of 0 or 1. For securing sensors within wireless body area networks (WBANs), electrocardiogram (ECG)-based BS generation methods have been widely investigated in which interpulse intervals (IPIs) from each heartbeat cycle are processed to produce BSes. Using these IPI-based methods to generate a 128-bit BS in real time normally takes around half a minute. In order to improve the time efficiency of such methods, this paper presents an ECG multiple fiducial-points based binary sequence generation (MFBSG) algorithm. The technique of discrete wavelet transforms is employed to detect arrival time of these fiducial points, such as P, Q, R, S, and T peaks. Time intervals between them, including RR, RQ, RS, RP, and RT intervals, are then calculated based on this arrival time, and are used as ECG features to generate random BSes with low latency. According to our analysis on real ECG data, these ECG feature values exhibit the property of randomness and, thus, can be utilized to generate random BSes. Compared with the schemes that solely rely on IPIs to generate BSes, this MFBSG algorithm uses five feature values from one heart beat cycle, and can be up to five times faster than the solely IPI-based methods. So, it achieves a design goal of low latency. According to our analysis, the complexity of the algorithm is comparable to that of fast Fourier transforms. These randomly generated ECG BSes can be used as security keys for encryption or authentication in a WBAN system.

  6. Biological oscillations for learning walking coordination: dynamic recurrent neural network functionally models physiological central pattern generator.

    Science.gov (United States)

    Hoellinger, Thomas; Petieau, Mathieu; Duvinage, Matthieu; Castermans, Thierry; Seetharaman, Karthik; Cebolla, Ana-Maria; Bengoetxea, Ana; Ivanenko, Yuri; Dan, Bernard; Cheron, Guy

    2013-01-01

    The existence of dedicated neuronal modules such as those organized in the cerebral cortex, thalamus, basal ganglia, cerebellum, or spinal cord raises the question of how these functional modules are coordinated for appropriate motor behavior. Study of human locomotion offers an interesting field for addressing this central question. The coordination of the elevation of the 3 leg segments under a planar covariation rule (Borghese et al., 1996) was recently modeled (Barliya et al., 2009) by phase-adjusted simple oscillators shedding new light on the understanding of the central pattern generator (CPG) processing relevant oscillation signals. We describe the use of a dynamic recurrent neural network (DRNN) mimicking the natural oscillatory behavior of human locomotion for reproducing the planar covariation rule in both legs at different walking speeds. Neural network learning was based on sinusoid signals integrating frequency and amplitude features of the first three harmonics of the sagittal elevation angles of the thigh, shank, and foot of each lower limb. We verified the biological plausibility of the neural networks. Best results were obtained with oscillations extracted from the first three harmonics in comparison to oscillations outside the harmonic frequency peaks. Physiological replication steadily increased with the number of neuronal units from 1 to 80, where similarity index reached 0.99. Analysis of synaptic weighting showed that the proportion of inhibitory connections consistently increased with the number of neuronal units in the DRNN. This emerging property in the artificial neural networks resonates with recent advances in neurophysiology of inhibitory neurons that are involved in central nervous system oscillatory activities. The main message of this study is that this type of DRNN may offer a useful model of physiological central pattern generator for gaining insights in basic research and developing clinical applications.

  7. Improving the network infeed accuracy of non-dispatchable generators with energy storage devices

    International Nuclear Information System (INIS)

    Koeppel, Gaudenz; Korpaas, Magnus

    2008-01-01

    The power output of generators based on renewable energy sources is often difficult to predict due to the non-deterministic behaviour of the energy source. Particularly in the case of wind turbines this leads to unpredicted line loading and requires balancing energy, at relatively high costs, depending on market structures. Consequently, the income from the production from such non-dispatchable generators can be significantly reduced by the penalty costs incurred. This paper investigates the potential of operating an energy storage device in parallel with the non-dispatchable generator in order to compensate the inaccuracies of the forecasted infeed and to avoid infeed deviations. A time series based simulation methodology is discussed, suitable for any type of non-dispatchable generator. The methodology contains a procedure for simulating different forecast errors, applying an exponentially weighted moving average approach. Analysis procedures and system performance indices are introduced for the evaluation of the configuration's performance. The applicability is shown in two case studies, using measurement data from a wind turbine and from a photovoltaic system. Both case studies show that the suggested configuration considerably improves the reliability or dependability of the network infeed, in turn reducing the demand for balancing energy and back-up generation. The relation between forecast error magnitude and required energy capacity is identified and the coherence of the time series analysis is discussed. (author)

  8. Efficient generation of connectivity in neuronal networks from simulator-independent descriptions

    Directory of Open Access Journals (Sweden)

    Mikael eDjurfeldt

    2014-04-01

    Full Text Available Simulator-independent descriptions of connectivity in neuronal networks promise greater ease of model sharing, improved reproducibility of simulation results, and reduced programming effort for computational neuroscientists. However, until now, enabling the use of such descriptions in a given simulator in a computationally efficient way has entailed considerable work for simulator developers, which must be repeated for each new connectivity-generating library that is developed.We have developed a generic connection generator interface that provides a standard way to connect a connectivity-generating library to a simulator, such that one library can easily be replaced by another, according to the modeller's needs. We have used the connection generator interface to connect C++ and Python implementations of the connection-set algebra to the NEST simulator. We also demonstrate how the simulator-independent modelling framework PyNN can transparently take advantage of this, passing a connection description through to the simulator layer for rapid processing in C++ where a simulator supports the connection generator interface and falling-back to slower iteration in Python otherwise. A set of benchmarks demonstrates the good performance of the interface.

  9. Wireless and wireline service convergence in next generation optical access networks - the FP7 WISCON project

    DEFF Research Database (Denmark)

    Vegas Olmos, Juan José; Pang, Xiaodan; Lebedev, Alexander

    2014-01-01

    . In this paper, we will present the Marie Curie Framework Program 7 project “Wireless and wireline service convergence in next generation optical access networks” (WISCON), which focuses on the conception and study of novel architectures for wavelength-division-multiplexing (WDM) optical multi-modulation format...... radio-over-fiber (RoF) systems; this is a promising solution to implement broadband seamless wireless -wireline access networks. This project successfully concluded in autumn 2013, and is being follow up by another Marie Curie project entitled “flexible edge nodes for dynamic optical interconnection...

  10. Advanced modelling of doubly fed induction generator wind turbine under network disturbance

    DEFF Research Database (Denmark)

    Seman, S.; Iov, Florin; Niiranen, J.

    This paper presents a variable speed wind turbine simulator. The simulator is used for a 2 MW wind turbine transient behavior study during a short-term symmetrical network disturbance. The mechanical part of wind turbine model consists of the rotor aerodynamic model, the wind turbine control...... and the drive train model. The Doubly Fed Induction Generator (DFIG) is represented by an analytical two-axis model with constant lumped parameters and by Finite Element Method (FEM) based model. The model of the DFIG is coupled with the model of the passive crowbar protected and DTC controlled frequency...

  11. Cross-Layer Handover Scheme for Multimedia Communications in Next Generation Wireless Networks

    Directory of Open Access Journals (Sweden)

    Lin Chun-Cheng

    2010-01-01

    Full Text Available In order to achieve seamless handover for real-time applications in the IP Multimedia Subsystem (IMS of next generation network, a multiprotocol combined handover mechanism is proposed in this paper. We combine SIP (Session Initiation Protocol, FMIP (Fast Mobile IPv6 Protocol, and MIH (Media Independent Handover protocols by cross-layer design and optimize those protocols' signaling flows to improve the performance of vertical handover. Theoretical analysis and simulation results illustrate that our proposed mechanism performs better than the original SIP and MIH combined handover mechanism in terms of service interruption time and packet loss.

  12. RFID of next generation network for enhancing customer relationship management in healthcare industries.

    Science.gov (United States)

    Alzahrani, Ahmed; Qureshi, Muhammad Shuaib; Thayananthan, Vijey

    2017-10-23

    This paper aims to analyze possible next generation of networked radio frequency identification (NGN-RFID) system for customer relationship management (CRM) in healthcare industries. Customer relationship and its management techniques in a specific healthcare industry are considered in this development. The key objective of using NGN-RFID scheme is to enhance the handling of patients' data to improve the CRM efficiency in healthcare industries. The proposed NGN-RFID system is one of the valid points to improve the ability of CRM by analyzing different prior and current traditional approaches. The legacy of customer relationship management will be improved by using this modern NGN-RFID technology without affecting the novelty.

  13. A neural network driving curve generation method for the heavy-haul train

    OpenAIRE

    Youneng Huang; Litian Tan; Lei Chen; Tao Tang

    2016-01-01

    The heavy-haul train has a series of characteristics, such as the locomotive traction properties, the longer length of train, and the nonlinear train pipe pressure during train braking. When the train is running on a continuous long and steep downgrade railway line, the safety of the train is ensured by cycle braking, which puts high demands on the driving skills of the driver. In this article, a driving curve generation method for the heavy-haul train based on a neural network is proposed. F...

  14. A Decentralized Framework for Real-Time Energy Trading in Distribution Networks with Load and Generation Uncertainty

    OpenAIRE

    Bahrami, Shahab; Amini, M. Hadi

    2017-01-01

    The proliferation of small-scale renewable generators and price-responsive loads makes it a challenge for distribution network operators (DNOs) to schedule the controllable loads of the load aggregators and the generation of the generators in real-time. Additionally, the high computational burden and violation of the entities' (i.e., load aggregators' and generators') privacy make a centralized framework impractical. In this paper, we propose a decentralized energy trading algorithm that can ...

  15. Investment dimensions in a universal service perspective: Next generation networks, alternative funding mechanisms and public-private partnerships

    DEFF Research Database (Denmark)

    Falch, Morten; Henten, Anders

    2008-01-01

    This paper seeks to examine the investment dimensions of next generation networks from a universal service perspective in a European context. The question is how new network infrastructures for providing access for everyone to communication, information and entertainment services in the present...

  16. Interference-Aware Spectrum Sharing Techniques for Next Generation Wireless Networks

    KAUST Repository

    Qaraqe, Marwa Khalid

    2011-11-20

    Background: Reliable high-speed data communication that supports multimedia application for both indoor and outdoor mobile users is a fundamental requirement for next generation wireless networks and requires a dense deployment of physically coexisting network architectures. Due to the limited spectrum availability, a novel interference-aware spectrum-sharing concept is introduced where networks that suffer from congested spectrums (secondary-networks) are allowed to share the spectrum with other networks with available spectrum (primary-networks) under the condition that limited interference occurs to primary networks. Objective: Multiple-antenna and adaptive rate can be utilized as a power-efficient technique for improving the data rate of the secondary link while satisfying the interference constraint of the primary link by allowing the secondary user to adapt its transmitting antenna, power, and rate according to the channel state information. Methods: Two adaptive schemes are proposed using multiple-antenna transmit diversity and adaptive modulation in order to increase the spectral-efficiency of the secondary link while maintaining minimum interference with the primary. Both the switching efficient scheme (SES) and bandwidth efficient scheme (BES) use the scan-and-wait combining antenna technique (SWC) where there is a secondary transmission only when a branch with an acceptable performance is found; else the data is buffered. Results: In both these schemes the constellation size and selected transmit branch are determined to minimized the average number of switches and achieve the highest spectral efficiency given a minimum bit-error-rate (BER), fading conditions, and peak interference constraint. For delayed sensitive applications, two schemes using power control are used: SES-PC and BES-PC. In these schemes the secondary transmitter sends data using a nominal power level, which is optimized to minimize the average delay. Several numerical examples show

  17. Report on the September 2011 Meeting of the Next Generation Safegaurds Professional Network

    Energy Technology Data Exchange (ETDEWEB)

    Gitau, Ernest TN; Benz, Jacob M.

    2011-12-19

    The Next Generation Safeguards Professional Network (NGSPN) was established in 2009 by Oak Ridge National Laboratory targeted towards the engagement of young professionals employed in safeguards across the many national laboratories. NGSPN focuses on providing a mechanism for young safeguards professionals to connect and foster professional relationships, facilitating knowledge transfer between current safeguards experts and the next generation of experts, and acting as an entity to represent the interests of the international community of young and mid-career safeguards professionals. This is accomplished in part with a yearly meeting held at a national laboratory site. In 2011, this meeting was held at Pacific Northwest National Laboratory. This report documents the events and results of that meeting.

  18. Accurate and fast replication on the generation of fractal network traffic using alternative probability models

    Science.gov (United States)

    Fernandes, Stenio; Kamienski, Carlos; Sadok, Djamel

    2003-08-01

    Synthetic self-similar traffic in computer networks simulation is of imperative significance for the capturing and reproducing of actual Internet data traffic behavior. A universally used procedure for generating self-similar traffic is achieved by aggregating On/Off sources where the active (On) and idle (Off) periods exhibit heavy tailed distributions. This work analyzes the balance between accuracy and computational efficiency in generating self-similar traffic and presents important results that can be useful to parameterize existing heavy tailed distributions such as Pareto, Weibull and Lognormal in a simulation analysis. Our results were obtained through the simulation of various scenarios and were evaluated by estimating the Hurst (H) parameter, which measures the self-similarity level, using several methods.

  19. Impact of distributed generators on the power loss and voltage profile of sub-transmission network

    Directory of Open Access Journals (Sweden)

    A.S.O. Ogunjuyigbe

    2016-05-01

    Full Text Available This paper presents the impact of distributed generator (DG on the power loss and voltage profile of sub-transmission network at different penetration levels (PLs. The various DG technologies are modeled based on their electrical output characteristics. Voltage profile index which allows a single value to represent how well the voltage matches the ideal value is developed. The index allows a fair comparison of the voltage profile obtained from different scenarios. The extent to which DGs affect power losses and voltage profile depend on the type of DG technology, PL and the location in which the DG is connected to the grid. The integration of DGs reduces power losses on the network, however, as the PL increases, the power losses begin to increase. A PL of 50–75% is achieved on 69 kV voltage level and 25–50% penetration on 13.8 kV voltage level without an increase in the power loss. Also more DG can be integrated into the network at point of common connection of higher voltage level compared to the low voltage level.

  20. A FD/DAMA network architecture for the first generation land mobile satellite services

    Science.gov (United States)

    Yan, T.-Y.; Wang, C.; Cheng, U.; Dessouky, K.; Rafferty, W.

    1989-01-01

    A frequency division/demand assigned multiple access (FD/DAMA) network architecture for the first-generation land mobile satellite services is presented. Rationales and technical approaches are described. In this architecture, each mobile subscriber must follow a channel access protocol to make a service request to the network management center before transmission for either open-end or closed-end services. Open-end service requests will be processed on a blocked call cleared basis, while closed-end requests will be processed on a first-come-first-served basis. Two channel access protocols are investigated, namely, a recently proposed multiple channel collision resolution scheme which provides a significantly higher useful throughput, and the traditional slotted Aloha scheme. The number of channels allocated for either open-end or closed-end services can be adaptively changed according to aggregated traffic requests. Both theoretical and simulation results are presented. Theoretical results have been verified by simulation on the JPL network testbed.

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

    Directory of Open Access Journals (Sweden)

    Tingsong Du

    2015-01-01

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

  2. A mathematical model for generating bipartite graphs and its application to protein networks

    International Nuclear Information System (INIS)

    Nacher, J C; Ochiai, T; Hayashida, M; Akutsu, T

    2009-01-01

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  3. Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking

    Directory of Open Access Journals (Sweden)

    Alireza Taravat

    2015-02-01

    Full Text Available A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 μm with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.

  4. Informative sensor selection and learning for prediction of lower limb kinematics using generative stochastic neural networks.

    Science.gov (United States)

    Eunsuk Chong; Taejin Choi; Hyungmin Kim; Seung-Jong Kim; Yoha Hwang; Jong Min Lee

    2017-07-01

    We propose a novel approach of selecting useful input sensors as well as learning a mathematical model for predicting lower limb joint kinematics. We applied a feature selection method based on the mutual information called the variational information maximization, which has been reported as the state-of-the-art work among information based feature selection methods. The main difficulty in applying the method is estimating reliable probability density of input and output data, especially when the data are high dimensional and real-valued. We addressed this problem by applying a generative stochastic neural network called the restricted Boltzmann machine, through which we could perform sampling based probability estimation. The mutual informations between inputs and outputs are evaluated in each backward sensor elimination step, and the least informative sensor is removed with its network connections. The entire network is fine-tuned by maximizing conditional likelihood in each step. Experimental results are shown for 4 healthy subjects walking with various speeds, recording 64 sensor measurements including electromyogram, acceleration, and foot-pressure sensors attached on both lower limbs for predicting hip and knee joint angles. For test set of walking with arbitrary speed, our results show that our suggested method can select informative sensors while maintaining a good prediction accuracy.

  5. A mathematical model for generating bipartite graphs and its application to protein networks

    Energy Technology Data Exchange (ETDEWEB)

    Nacher, J C [Department of Complex Systems, Future University-Hakodate (Japan); Ochiai, T [Faculty of Engineering, Toyama Prefectural University (Japan); Hayashida, M; Akutsu, T [Bioinformatics Center, Institute for Chemical Research, Kyoto University (Japan)

    2009-12-04

    Complex systems arise in many different contexts from large communication systems and transportation infrastructures to molecular biology. Most of these systems can be organized into networks composed of nodes and interacting edges. Here, we present a theoretical model that constructs bipartite networks with the particular feature that the degree distribution can be tuned depending on the probability rate of fundamental processes. We then use this model to investigate protein-domain networks. A protein can be composed of up to hundreds of domains. Each domain represents a conserved sequence segment with specific functional tasks. We analyze the distribution of domains in Homo sapiens and Arabidopsis thaliana organisms and the statistical analysis shows that while (a) the number of domain types shared by k proteins exhibits a power-law distribution, (b) the number of proteins composed of k types of domains decays as an exponential distribution. The proposed mathematical model generates bipartite graphs and predicts the emergence of this mixing of (a) power-law and (b) exponential distributions. Our theoretical and computational results show that this model requires (1) growth process and (2) copy mechanism.

  6. Optimized Energy Procurement for Cellular Networks with Uncertain Renewable Energy Generation

    KAUST Repository

    Rached, Nadhir B.

    2017-02-07

    Renewable energy (RE) is an emerging solution for reducing carbon dioxide (CO2) emissions from cellular networks. One of the challenges of using RE sources is to handle its inherent uncertainty. In this paper, a RE powered cellular network is investigated. For a one-day operation cycle, the cellular network aims to reduce energy procurement costs from the smart grid by optimizing the amounts of energy procured from their locally deployed RE sources as well as from the smart grid. In addition to that, it aims to determine the extra amount of energy to be sold to the electrical grid at each time period. Chance constrained optimization is first proposed to deal with the randomness in the RE generation. Then, to make the optimization problem tractable, two well- know convex approximation methods, namely; Chernoff and Chebyshev based-approaches, are analyzed in details. Numerical results investigate the optimized energy procurement for various daily scenarios and compare between the performances of the employed convex approximation approaches.

  7. User-friendly Tool for Power Flow Analysis and Distributed Generation Optimisation in Radial Distribution Networks

    Directory of Open Access Journals (Sweden)

    M. F. Akorede

    2017-06-01

    Full Text Available The intent of power distribution companies (DISCOs is to deliver electric power to their customers in an efficient and reliable manner – with minimal energy loss cost. One major way to minimise power loss on a given power system is to install distributed generation (DG units on the distribution networks. However, to maximise benefits, it is highly crucial for a DISCO to ensure that these DG units are of optimal size and sited in the best locations on the network. This paper gives an overview of a software package developed in this study, called Power System Analysis and DG Optimisation Tool (PFADOT. The main purpose of the graphical user interface-based package is to guide a DISCO in finding the optimal size and location for DG placement in radial distribution networks. The package, which is also suitable for load flow analysis, employs the GUI feature of MATLAB. Three objective functions are formulated into a single optimisation problem and solved with fuzzy genetic algorithm to simultaneously obtain DG optimal size and location. The accuracy and reliability of the developed tool was validated using several radial test systems, and the results obtained are evaluated against the existing similar package cited in the literature, which are impressive and computationally efficient.

  8. U-tube steam generator empirical model development and validation using neural networks

    International Nuclear Information System (INIS)

    Parlos, A.G.; Chong, K.T.; Atiya, A.

    1992-01-01

    Empirical modeling techniques that use model structures motivated from neural networks research have proven effective in identifying complex process dynamics. A recurrent multilayer perception (RMLP) network was developed as a nonlinear state-space model structure along with a static learning algorithm for estimating the parameter associated with it. The methods developed were demonstrated by identifying two submodels of a U-tube steam generator (UTSG), each valid around an operating power level. A significant drawback of this approach is the long off-line training times required for the development of even a simplified model of a UTSG. Subsequently, a dynamic gradient descent-based learning algorithm was developed as an accelerated alternative to train an RMLP network for use in empirical modeling of power plants. The two main advantages of this learning algorithm are its ability to consider past error gradient information for future use and the two forward passes associated with its implementation. The enhanced learning capabilities provided by the dynamic gradient descent-based learning algorithm were demonstrated via the case study of a simple steam boiler power plant. In this paper, the dynamic gradient descent-based learning algorithm is used for the development and validation of a complete UTSG empirical model

  9. Next Generation RFID-Based Medical Service Management System Architecture in Wireless Sensor Network

    Science.gov (United States)

    Tolentino, Randy S.; Lee, Kijeong; Kim, Yong-Tae; Park, Gil-Cheol

    Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide unlimited future potentials most especially in healthcare systems. RFID is used to detect presence and location of objects while WSN is used to sense and monitor the environment. Integrating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. However, there isn't any flexible and robust communication infrastructure to integrate these devices into an emergency care setting. An efficient wireless communication substrate for medical devices that addresses ad hoc or fixed network formation, naming and discovery, transmission efficiency of data, data security and authentication, as well as filtration and aggregation of vital sign data need to be study and analyze. This paper proposed an efficient next generation architecture for RFID-based medical service management system in WSN that possesses the essential elements of each future medical application that are integrated with existing medical practices and technologies in real-time, remote monitoring, in giving medication, and patient status tracking assisted by embedded wearable wireless sensors which are integrated in wireless sensor network.

  10. Heterogeneous next-generation wireless network interference model-and its applications

    KAUST Repository

    Mahmood, Nurul Huda

    2014-04-01

    Next-generation wireless systems facilitating better utilisation of the scarce radio spectrum have emerged as a response to inefficient and rigid spectrum assignment policies. These are comprised of intelligent radio nodes that opportunistically operate in the radio spectrum of existing primary systems, yet unwanted interference at the primary receivers is unavoidable. In order to design efficient next-generation systems and to minimise the adverse effect of their interference, it is necessary to realise how the resulting interference impacts the performance of the primary systems. In this work, a generalised framework for the interference analysis of such a next-generation system is presented where the nextgeneration transmitters may transmit randomly with different transmit powers. The analysis is built around a model developed for the statistical representation of the interference at the primary receivers, which is then used to evaluate various performance measures of the primary system. Applications of the derived interference model in designing the next-generation network system parameters are also demonstrated. Such approach provides a unified and generalised framework, the use of which allows a wide range of performance metrics can be evaluated. Findings of the analytical performance analyses are confirmed through extensive computer-based Monte-Carlo simulations. © 2012 John Wiley & Sons, Ltd.

  11. Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks

    Directory of Open Access Journals (Sweden)

    Marwin H. S. Segler

    2017-12-01

    Full Text Available In de novo drug design, computational strategies are used to generate novel molecules with good affinity to the desired biological target. In this work, we show that recurrent neural networks can be trained as generative models for molecular structures, similar to statistical language models in natural language processing. We demonstrate that the properties of the generated molecules correlate very well with the properties of the molecules used to train the model. In order to enrich libraries with molecules active toward a given biological target, we propose to fine-tune the model with small sets of molecules, which are known to be active against that target. Against Staphylococcus aureus, the model reproduced 14% of 6051 hold-out test molecules that medicinal chemists designed, whereas against Plasmodium falciparum (Malaria, it reproduced 28% of 1240 test molecules. When coupled with a scoring function, our model can perform the complete de novo drug design cycle to generate large sets of novel molecules for drug discovery.

  12. Temporal evolution of a drainage fracture network into an elastic medium with internal fluid generation

    Science.gov (United States)

    Kobchenko, Maya; Hafver, Andreas; Dysthe, Dag Kristian; Renard, Francois

    2013-04-01

    Escape of internally generated fluids from low permeability rocks plays an important role in several geological systems. Primary migration of hydrocarbons, dehydration of sediments and hydrated mantellic rocks in subduction zones in the Earth's crust are geological examples where the existing permeability cannot accommodate transport of generated fluids in low permeability rocks and fluid pressure build-up may alter the permeability by fracturing. Fractures form and propagate in the rock due to internal pressure build-up. We develop an easy and reproducible analog experiment to simulate fracture formation in low permeability rock during internal fluid/gas production. This work aims to describe the physical mechanism of fracture network growth and temporal evolution of created fractures. A tight elastic gelatin matrix is used as a rock analog. The nucleation, propagation and coalescence of fractures within the solid matrix occurs due to CO2 production by yeast consuming sugar and is followed using optical means. We quantify first how an equilibrium fracture network self-develop, and then how the intermittent fluid transport is controlled by the dynamics of opening and closing of fractures, with a well-defined time frequency.

  13. Ab initio Algorithmic Causal Deconvolution of Intertwined Programs and Networks by Generative Mechanism

    KAUST Repository

    Zenil, Hector

    2018-02-18

    To extract and learn representations leading to generative mechanisms from data, especially without making arbitrary decisions and biased assumptions, is a central challenge in most areas of scientific research particularly in connection to current major limitations of influential topics and methods of machine and deep learning as they have often lost sight of the model component. Complex data is usually produced by interacting sources with different mechanisms. Here we introduce a parameter-free model-based approach, based upon the seminal concept of Algorithmic Probability, that decomposes an observation and signal into its most likely algorithmic generative mechanisms. Our methods use a causal calculus to infer model representations. We demonstrate the method ability to distinguish interacting mechanisms and deconvolve them, regardless of whether the objects produce strings, space-time evolution diagrams, images or networks. We numerically test and evaluate our method and find that it can disentangle observations from discrete dynamic systems, random and complex networks. We think that these causal inference techniques can contribute as key pieces of information for estimations of probability distributions complementing other more statistical-oriented techniques that otherwise lack model inference capabilities.

  14. An adaptive random search for short term generation scheduling with network constraints.

    Directory of Open Access Journals (Sweden)

    J A Marmolejo

    Full Text Available This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

  15. Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.

    Science.gov (United States)

    Adamović, Vladimir M; Antanasijević, Davor Z; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A; Pocajt, Viktor V

    2017-01-01

    This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population and economic development level. Proper modelling of MSW generation is essential for the planning of MSW management system as well as for the simulation of various environmental impact scenarios. The main objective of this work was to examine the potential influence of economy crisis (global or local) on the forecast of MSW generation obtained by the GRNN model. The existence of the so-called structural breaks that occur because of the economic crisis in the studied period (2000-2012) for each country was determined and confirmed using the Chow test and Quandt-Andrews test. Two GRNN models, one which did not take into account the influence of the economic crisis (GRNN) and another one which did (SB-GRNN), were developed. The novelty of the applied method is that it uses broadly available social, economic and demographic indicators and indicators of sustainability, together with GRNN and structural break testing for the prediction of MSW generation at the national level. The obtained results demonstrate that the SB-GRNN model provide more accurate predictions than the model which neglected structural breaks, with a mean absolute percentage error (MAPE) of 4.0 % compared to 6.7 % generated by the GRNN model. The proposed model enhanced with structural breaks can be a viable alternative for a more accurate prediction of MSW generation at the national level, especially for developing countries for which a lack of MSW data is notable.

  16. Estimates of hydroelectric generation using neural networks with the artificial bee colony algorithm for Turkey

    International Nuclear Information System (INIS)

    Uzlu, Ergun; Akpınar, Adem; Özturk, Hasan Tahsin; Nacar, Sinan; Kankal, Murat

    2014-01-01

    The primary objective of this study was to apply the ANN (artificial neural network) model with the ABC (artificial bee colony) algorithm to estimate annual hydraulic energy production of Turkey. GEED (gross electricity energy demand), population, AYT (average yearly temperature), and energy consumption were selected as independent variables in the model. The first part of the study compared ANN-ABC model performance with results of classical ANN models trained with the BP (back propagation) algorithm. Mean square and relative error were applied to evaluate model accuracy. The test set errors emphasized positive differences between the ANN-ABC and classical ANN models. After determining optimal configurations, three different scenarios were developed to predict future hydropower generation values for Turkey. Results showed the ANN-ABC method predicted hydroelectric generation better than the classical ANN trained with the BP algorithm. Furthermore, results indicated future hydroelectric generation in Turkey will range from 69.1 to 76.5 TWh in 2021, and the total annual electricity demand represented by hydropower supply rates will range from 14.8% to 18.0%. However, according to Vision 2023 agenda goals, the country plans to produce 30% of its electricity demand from renewable energy sources by 2023, and use 20% less energy than in 2010. This percentage renewable energy provision cannot be accomplished unless changes in energy policy and investments are not addressed and implemented. In order to achieve this goal, the Turkish government must reconsider and raise its own investments in hydropower, wind, solar, and geothermal energy, particularly hydropower. - Highlights: • This study is associated with predicting hydropower generation in Turkey. • Sensitivity analysis was performed to determine predictor variables. • GEED, population, energy consumption and AYT were used as predictor variables. • ANN-ABC predicted the hydropower generation more accurately

  17. The photovoltaic generators and the electric network; Los generadores fotovoltaicos y la red electrica

    Energy Technology Data Exchange (ETDEWEB)

    Arteaga Novoa, Oscar E.; Agredano Diaz, Jaime; Huacuz Villamar, Jorge M. [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1997-12-31

    The photovoltaic generators are analyzed as an option for the electricity supply. An analysis is made of the option that these systems be utilized in sites where it is difficult to extend the power lines an in sites where the electric service already exists, such as residences, commercial buildings, network support power stations, central power stations, all this in order that the photovoltaic systems interact with the electric network for the generation of part of the energy consumed in these sites. In order that the photovoltaic systems can be interconnected with the electric network it is required: energy quality, protection and safety of the systems and persons and normativity for the interconnection. Some of the national programs of countries like Japan, United States of America and some organs of the Commission of the European Community are described. In conclusion, it is expected that the costs of this technology decrease so these systems can be widely utilized [Espanol] Se analizan los generadores fotovoltaicos como una alternativa para el suministro electrico. Se analiza la opcion de que estos sistemas se utilicen en lugares en donde es dificil extender la red electrica y en sitios en donde el servicio electrico ya existe, tales como: residencias, edificios comerciales, estaciones de apoyo a la red, estaciones centrales, esto con la finalidad de que el sistema fotovoltaico interactue con la red electrica a fin de generar parte de la energia que se consume en estos sitios. Para que los sistemas fotovoltaicos puedan estar interconectados con la red electrica se requiere: calidad de la energia, proteccion y seguridad de los sistemas y personas, y normatividad para la interconexion. Se describen algunos programas nacionales de paises como Japon, Estados Unidos y algunos organismos de la Comision de Comunidades Europeas. En conclusion, se espera que los costos de esta tecnologia disminuyan para que estos sistemas puedan ser ampliamante utilizados

  18. SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

    Science.gov (United States)

    Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

    2013-01-01

    Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.

  19. Construction and testing of five 25 kW elektrOmat wind energy generators with network-controlled inverter for network parallel operation

    Energy Technology Data Exchange (ETDEWEB)

    Frees, H.H.

    1988-01-01

    It is planned to construct and test 5 WPP type elektrOmat (25 kW) with network-controlled inverter for network-parallel operation in various applications. The novel wind generators operate in pure isolated operation for power production without network connection. Control, excitation and wind tracking are effected independently without power supplied by either network or other stations. Synchronous generator excitation is controlled by a microprocessor. The three-phase current produced has variable frequency and voltage. A special wing profile allows to effect rotor start-up at wind speeds as low as 3.5 m/s at an output of 1.5 kWh. Hence, these converters are particularly suitable for weak wind regions. Power is supplied to a water works, an electrical company, a marzipan manufacturer, a utility and an industrial entreprise. (HWJ).

  20. Generate networks with power-law and exponential-law distributed degrees: with applications in link prediction of tumor pathways

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

    Full Text Available In present study I proposed a method for generating biological networks based on power-law (p(x=x^(-a and exponential-law (p(x=e^(-ax distribution functions. Given the parameter of power-law or exponential-law distribution function, a, the algorithm generates an expected frequency distribution according to the given parameter, thereafter creates an adjacency matrix in which (practical frequency distribution of node degrees matches the expected frequency distribution. The results showed that power-law distribution function performs much better than exponential-law distribution function in generating networks. Using the revised algorithm, tumor related networks (pathways are simulated and predicted. The results prove that the algorithm is overall effective in predicting network links (14.6%-21.2%of correctly predicted links against 0.1%-3.4% of that for random assignments. Matlab codes of the algorithms are given also.

  1. Learning-Related Changes in Adolescents' Neural Networks during Hypothesis-Generating and Hypothesis-Understanding Training

    Science.gov (United States)

    Lee, Jun-Ki; Kwon, Yongju

    2012-01-01

    Fourteen science high school students participated in this study, which investigated neural-network plasticity associated with hypothesis-generating and hypothesis-understanding in learning. The students were divided into two groups and participated in either hypothesis-generating or hypothesis-understanding type learning programs, which were…

  2. From spinal central pattern generators to cortical network: integrated BCI for walking rehabilitation.

    Science.gov (United States)

    Cheron, G; Duvinage, M; De Saedeleer, C; Castermans, T; Bengoetxea, A; Petieau, M; Seetharaman, K; Hoellinger, T; Dan, B; Dutoit, T; Sylos Labini, F; Lacquaniti, F; Ivanenko, Y

    2012-01-01

    Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs). Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG), upper limb electromyogram (EMG), or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs) or dynamic recurrent neural networks (DRNNs). Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

  3. From Spinal Central Pattern Generators to Cortical Network: Integrated BCI for Walking Rehabilitation

    Directory of Open Access Journals (Sweden)

    G. Cheron

    2012-01-01

    Full Text Available Success in locomotor rehabilitation programs can be improved with the use of brain-computer interfaces (BCIs. Although a wealth of research has demonstrated that locomotion is largely controlled by spinal mechanisms, the brain is of utmost importance in monitoring locomotor patterns and therefore contains information regarding central pattern generation functioning. In addition, there is also a tight coordination between the upper and lower limbs, which can also be useful in controlling locomotion. The current paper critically investigates different approaches that are applicable to this field: the use of electroencephalogram (EEG, upper limb electromyogram (EMG, or a hybrid of the two neurophysiological signals to control assistive exoskeletons used in locomotion based on programmable central pattern generators (PCPGs or dynamic recurrent neural networks (DRNNs. Plantar surface tactile stimulation devices combined with virtual reality may provide the sensation of walking while in a supine position for use of training brain signals generated during locomotion. These methods may exploit mechanisms of brain plasticity and assist in the neurorehabilitation of gait in a variety of clinical conditions, including stroke, spinal trauma, multiple sclerosis, and cerebral palsy.

  4. A compact bipolar pulse-forming network-Marx generator based on pulse transformers.

    Science.gov (United States)

    Zhang, Huibo; Yang, Jianhua; Lin, Jiajin; Yang, Xiao

    2013-11-01

    A compact bipolar pulse-forming network (PFN)-Marx generator based on pulse transformers is presented in this paper. The high-voltage generator consisted of two sets of pulse transformers, 6 stages of PFNs with ceramic capacitors, a switch unit, and a matched load. The design is characterized by the bipolar pulse charging scheme and the compact structure of the PFN-Marx. The scheme of bipolar charging by pulse transformers increased the withstand voltage of the ceramic capacitors in the PFNs and decreased the number of the gas gap switches. The compact structure of the PFN-Marx was aimed at reducing the parasitic inductance in the generator. When the charging voltage on the PFNs was 35 kV, the matched resistive load of 48 Ω could deliver a high-voltage pulse with an amplitude of 100 kV. The full width at half maximum of the load pulse was 173 ns, and its rise time was less than 15 ns.

  5. Generating Poetry Title Based on Semantic Relevance with Convolutional Neural Network

    Science.gov (United States)

    Li, Z.; Niu, K.; He, Z. Q.

    2017-09-01

    Several approaches have been proposed to automatically generate Chinese classical poetry (CCP) in the past few years, but automatically generating the title of CCP is still a difficult problem. The difficulties are mainly reflected in two aspects. First, the words used in CCP are very different from modern Chinese words and there are no valid word segmentation tools. Second, the semantic relevance of characters in CCP not only exists in one sentence but also exists between the same positions of adjacent sentences, which is hard to grasp by the traditional text summarization models. In this paper, we propose an encoder-decoder model for generating the title of CCP. Our model encoder is a convolutional neural network (CNN) with two kinds of filters. To capture the commonly used words in one sentence, one kind of filters covers two characters horizontally at each step. The other covers two characters vertically at each step and can grasp the semantic relevance of characters between adjacent sentences. Experimental results show that our model is better than several other related models and can capture the semantic relevance of CCP more accurately.

  6. A Flexible Experimental Laboratory for Distributed Generation Networks Based on Power Inverters

    Directory of Open Access Journals (Sweden)

    Jaume Miret

    2017-10-01

    Full Text Available In the recently deregulated electricity market, distributed generation based on renewable sources is becoming more and more relevant. In this area, two main distributed scenarios are focusing the attention of recent research: grid-connected mode, where the generation sources are connected to a grid mainly supplied by big power plants, and islanded mode, where the distributed sources, energy storage devices, and loads compose an autonomous entity that in its general form can be named a microgrid. To conduct a successful research in these two scenarios, it is essential to have a flexible experimental setup. This work deals with the description of a real laboratory setup composed of four nodes that can emulate both scenarios of a distributed generation network. A comprehensive description of the hardware and software setup will be done, focusing especially in the dual-core DSP used for control purposes, which is next to the industry standards and able to emulate real complexities. A complete experimental section will show the main features of the system.

  7. Recommendations for institutional policy and network regulatory frameworks towards distributed generation in EU Member States

    Energy Technology Data Exchange (ETDEWEB)

    Ten Donkelaar, M.; Van Oostvoorn, F. [ECN Policy Studies, Petten (Netherlands)

    2005-01-01

    Recommendations regarding the development of regulatory frameworks and institutional policies towards an optimal integration of distributed generation (DG) into electricity networks are presented. These recommendations are based on findings from a benchmarking study conducted in the framework of the ENIRDG-net project. The aim of the benchmarking exercise was to identify examples of well-defined pro-DG policies, with clear targets and adequate implementation mechanisms. In this study an adequate pro-DG policy is defined on the basis of a level playing field, a situation where distributed and centralised generation receive equal incentives and have equal access to the liberalised markets for electricity. The benchmark study includes the results of a similar study conducted in the framework of the SUSTELNET project. When comparing the results a certain discrepancy can be noticed between the actual regulation and policy in a number of countries, the medium to long-term targets and the ideal situation described by the level playing field objective. To overcome this discrepancy, a number of recommendations have been drafted for future policy and regulation towards distributed generation.

  8. Robust Power Supply Restoration for Self-Healing Active Distribution Networks Considering the Availability of Distributed Generation

    Directory of Open Access Journals (Sweden)

    Qiang Yang

    2018-01-01

    Full Text Available The increasing penetration of distributed generations (DGs with intermittent and stochastic characteristics into current power distribution networks can lead to increased fault levels and degradation in network protection. As one of the key requirements of active network management (ANM, efficient power supply restoration solution to guarantee network self-healing capability with full consideration of DG uncertainties is demanded. This paper presents a joint power supply restoration through combining the DG local restoration and switcher operation-based restoration to enhance the self-healing capability in active distribution networks considering the availability of distributed generation. The restoration algorithmic solution is designed to be able to carry out power restoration in parallel upon multiple simultaneous faults to maximize the load restoration while additionally minimizing power loss, topology variation and power flow changes due to switcher operations. The performance of the proposed solution is validated based on a 53-bus distribution network with wind power generators through extensive simulation experiments for a range of fault cases and DG scenarios generated based on Heuristic Moment Matching (HMM method to fully consider the DG randomness. The numerical result in comparison with the existing solutions demonstrates the effectiveness of the proposed power supply restoration solution.

  9. Modeling and Mangement of InterCell Interference in Future Generation Wireless Networks

    KAUST Repository

    Tabassum, Hina

    2012-12-01

    There has been a rapid growth in the data rate carried by cellular services, and this increase along with the emergence of new multimedia applications have motivated the 3rd Generation Partnership (3GPP) Project to launch Long-Term Evolution (LTE) [1]. LTE is the latest standard in the mobile network technology and is designed to meet the ubiquitous demands of next-generation mobile networks. LTE assures significant spectral and energy efficiency gains in both the uplink and down- link with low latency. Multiple access schemes such as Orthogonal Frequency Division Aultiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) which is a modified version of OFDMA have been recently adopted in 3GPP LTE downlink and uplink, respectively [1]. A typical feature of OFDMA is the decomposition of available bandwidth into multiple narrow orthogonal subcarriers. The orthogonality among subcarriers causes minimal intra-cell interference, however, the inter-cell interference (ICI) incurred on a given subcarrier is relatively impulsive and poses a fundamental challenge for the network designers. Moreover, as the number of interferers on a given subcarrier can be relatively limited it may not be accurate to model ICI as a Gaussian random variable by invoking the central limit theorem. The nature of ICI relies on a variety of indeterministic parameters which include frequency reuse factor, channel conditions, scheduling decisions, transmit power, and location of the interferers. This thesis presents a combination of algorithmic and theoretical studies for efficient modeling and management of ICI via radio resource management. In the preliminary phase, we focus on developing and analyzing the performance of several centralized and distributed interference mitigation and rate maximization algorithms. These algorithms relies on optimizing the spectrum allocation and user’s transmission powers to maximize the system capacity. Even though, the developed

  10. A Trustworthy Key Generation Prototype Based on DDR3 PUF for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Wenchao Liu

    2014-06-01

    Full Text Available Secret key leakage in wireless sensor networks (WSNs is a high security risk especially when sensor nodes are deployed in hostile environment and physically accessible to attackers. With nowadays semi/fully-invasive attack techniques attackers can directly derive the cryptographic key from non-volatile memory (NVM storage. Physically Unclonable Function (PUF is a promising technology to resist node capture attacks, and it also provides a low cost and tamper-resistant key provisioning solution. In this paper, we designed a PUF based on double-data-rate SDRAM Type 3 (DDR3 memory by exploring its memory decay characteristics. We also described a prototype of 128-bit key generation based on DDR3 PUF with integrated fuzzy extractor. Due to the wide adoption of DDR3 memory in WSN, our proposed DDR3 PUF technology with high security levels and no required hardware changes is suitable for a wide range of WSN applications.

  11. Applying a Cerebellar Model Articulation Controller Neural Network to a Photovoltaic Power Generation System Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Kuei-Hsiang Chao

    2013-01-01

    Full Text Available This study employed a cerebellar model articulation controller (CMAC neural network to conduct fault diagnoses on photovoltaic power generation systems. We composed a module array using 9 series and 2 parallel connections of SHARP NT-R5E3E 175 W photovoltaic modules. In addition, we used data that were outputted under various fault conditions as the training samples for the CMAC and used this model to conduct the module array fault diagnosis after completing the training. The results of the training process and simulations indicate that the method proposed in this study requires fewer number of training times compared to other methods. In addition to significantly increasing the accuracy rate of the fault diagnosis, this model features a short training duration because the training process only tunes the weights of the exited memory addresses. Therefore, the fault diagnosis is rapid, and the detection tolerance of the diagnosis system is enhanced.

  12. Control Architecture for Intentional Island Operation in Distribution Network with High Penetration of Distributed Generation

    DEFF Research Database (Denmark)

    Chen, Yu

    Currently, a high penetration level of Distributed Generations (DGs), such as Wind Turbines (WTs) and Combined Heat and Power plants (CHPs), has been observed in the Danish distribution systems, and even more DGs are foreseen to be present in the coming years. With adequate DGs available, how...... amount of DGs. As part of the NextGen project, this project focuses on the system modeling and simulation regarding the control architecture and recommends the development of a communication and information exchange system based on IEC 61850. This thesis starts with the background of this PhD project......, the feasibility of the application of Artificial Neural Network (ANN) to ICA is studied, in order to improve the computation efficiency for ISR calculation. Finally, the integration of ICA into Dynamic Security Assessment (DSA), the ICA implementation, and the development of ICA are discussed....

  13. Generating functional analysis of complex formation and dissociation in large protein interaction networks

    International Nuclear Information System (INIS)

    Coolen, A C C; Rabello, S

    2009-01-01

    We analyze large systems of interacting proteins, using techniques from the non-equilibrium statistical mechanics of disordered many-particle systems. Apart from protein production and removal, the most relevant microscopic processes in the proteome are complex formation and dissociation, and the microscopic degrees of freedom are the evolving concentrations of unbound proteins (in multiple post-translational states) and of protein complexes. Here we only include dimer-complexes, for mathematical simplicity, and we draw the network that describes which proteins are reaction partners from an ensemble of random graphs with an arbitrary degree distribution. We show how generating functional analysis methods can be used successfully to derive closed equations for dynamical order parameters, representing an exact macroscopic description of the complex formation and dissociation dynamics in the infinite system limit. We end this paper with a discussion of the possible routes towards solving the nontrivial order parameter equations, either exactly (in specific limits) or approximately.

  14. Optical stealth transmission based on super-continuum generation in highly nonlinear fiber over WDM network.

    Science.gov (United States)

    Zhu, Huatao; Wang, Rong; Pu, Tao; Fang, Tao; Xiang, Peng; Zheng, Jilin; Chen, Dalei

    2015-06-01

    In this Letter, the optical stealth transmission carried by super-continuum spectrum optical pulses generated in highly nonlinear fiber is proposed and experimentally demonstrated. In the proposed transmission scheme, super-continuum signals are reshaped in the spectral domain through a wavelength-selective switch and are temporally spread by a chromatic dispersion device to achieve the same noise-like characteristic as the noise in optical networks, so that in both the time domain and the spectral domain, the stealth signals are hidden in public channel. Our experimental results show that compared with existing schemes where stealth channels are carried by amplified spontaneous emission noise, super-continuum signal can increase the transmission performance and robustness.

  15. Agent-based reactive power management of power distribution networks with distributed energy generation

    International Nuclear Information System (INIS)

    Rahman, M.S.; Mahmud, M.A.; Oo, A.M.T.; Pota, H.R.; Hossain, M.J.

    2016-01-01

    Highlights: • A coordinated multi-agent system is proposed for reactive power management. • A linear quadratic regulator with a proportional integral controller is designed. • Proposed multi-agent scheme provides accurate estimation and control of the system. • Voltage stability is improved with proper power management for different scenarios. • Results obtained from the proposed scheme is compared to the traditional approach. - Abstract: In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

  16. Impact of Optimum Allocation of Renewable Distributed Generations on Distribution Networks Based on Different Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Tolba

    2018-01-01

    Full Text Available Integration of Renewable Distributed Generations (RDGs such as photovoltaic (PV systems and wind turbines (WTs in distribution networks can be considered a brilliant and efficient solution to the growing demand for energy. This article introduces new robust and effective techniques like hybrid Particle Swarm Optimization in addition to a Gravitational Search Algorithm (PSOGSA and Moth-Flame Optimization (MFO that are proposed to deduce the optimum location with convenient capacity of RDGs units for minimizing system power losses and operating cost while improving voltage profile and voltage stability. This paper describes two stages. First, the Loss Sensitivity Factors (LSFs are employed to select the most candidate buses for RDGs location. In the second stage, the PSOGSA and MFO are implemented to deduce the optimal location and capacity of RDGs from the elected buses. The proposed schemes have been applied on 33-bus and 69-bus IEEE standard radial distribution systems. To insure the suggested approaches validity, the numerical results have been compared with other techniques like Backtracking Search Optimization Algorithm (BSOA, Genetic Algorithm (GA, Particle Swarm Algorithm (PSO, Novel combined Genetic Algorithm and Particle Swarm Optimization (GA/PSO, Simulation Annealing Algorithm (SA, and Bacterial Foraging Optimization Algorithm (BFOA. The evaluated results have been confirmed the superiority with high performance of the proposed MFO technique to find the optimal solutions of RDGs units’ allocation. In this regard, the MFO is chosen to solve the problems of Egyptian Middle East distribution network as a practical case study with the optimal integration of RDGs.

  17. Educating the next generation of atmospheric scientists within a European Network of Excellence

    Science.gov (United States)

    Schuepbach, E.; Uherek, E.; Ladstätter-Weissenmayer, A.; Jacob, M. J.

    In order to promote the next generation of atmospheric scientists, the task Training and Education (T&E) in ACCENT, the European Network of Excellence in Atmospheric Composition Change ( www.accent-network.org) has developed and implemented an Integrated Learning Environment (ILE). For school teachers and their students, the Internet-based "Global Change Magazine" provides up-to-date and freely accessible scientific material in English and five other languages. Additionally, T&E has produced online teaching material for early-career scientists. These e-learning modules are now being used in University Master's courses across Europe. T&E also organised training events for early-career scientists, combining scientific content with development in transferable skills, to focus on interdisciplinary collaboration, interaction with senior scientists, communication with stakeholders, and dissemination to the general public. Evaluation based on participant feedback evidences the effectiveness of these events, e.g., in terms of motivation to remain in the field. Methodologies and materials from T&E are being published in a Handbook on Best Practice, intended for both educators and scientists around the globe who are involved in education in the field of air quality and climate change science.

  18. Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

    Directory of Open Access Journals (Sweden)

    Yuanpeng Tan

    2018-01-01

    Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

  19. Thermoelectric generator experimental performance testing for wireless sensor network application in smart buildings

    Directory of Open Access Journals (Sweden)

    Al Musleh Mohamed

    2017-01-01

    Full Text Available In order to make a conventional building more efficient or smarter, systems feedbacks are essential. Such feedbacks can include real-time or logged data from various systems, such as temperature, humidity, lighting and CO2 levels. This is only possible by the use of a network of sensors which report to the building management system. Conventional sensors are limited due to wiring and infrastructure requirements. Wireless Sensor Networks (WSN however, eliminates the wiring limitations but still in certain cases require periodical battery changes and maintenance. A suitable solution for WSN limitations is to use different types of ambient energy harvesters to power battery-less sensors or alternatively to charge existing batteries so as to reduce their changing requirements. Such systems are already in place using various energy harvesting techniques. Thermoelectric Generators (TEG are one of them where the temperature gradient is used to generate electricity which is conditioned and used for WSN powering applications. Researchers in this field often face difficulty in estimating the TEG output at the low-temperature difference as manufacturers’ datasheets and performance data are not following the same standards and in most cases cover the high-temperature difference (more than 200C°. This is sufficient for industrial applications but not for WSN systems in the built environment where the temperature difference is much smaller (1-20C° is covered in this study. This paper presents a TEG experimental test setup using a temperature controlled hotplate in order to provide accurate TEG performance data at the low-temperature difference range.

  20. Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors

    Directory of Open Access Journals (Sweden)

    Holschneider Matthias

    2007-05-01

    deactivated filters, and hence, metabolomic networks should be generated without the filter. In addition, Bayesian likelihoods facilitate the detection of multiple linear dependencies between two variables. This property of the algorithm enables its use as a discovery tool and to generate novel hypotheses of the existence of otherwise hidden biological factors.

  1. Generative adversarial network based telecom fraud detection at the receiving bank.

    Science.gov (United States)

    Zheng, Yu-Jun; Zhou, Xiao-Han; Sheng, Wei-Guo; Xue, Yu; Chen, Sheng-Yong

    2018-06-01

    Recently telecom fraud has become a serious problem especially in developing countries such as China. At present, it can be very difficult to coordinate different agencies to prevent fraud completely. In this paper we study how to detect large transfers that are sent from victims deceived by fraudsters at the receiving bank. We propose a new generative adversarial network (GAN) based model to calculate for each large transfer a probability that it is fraudulent, such that the bank can take appropriate measures to prevent potential fraudsters to take the money if the probability exceeds a threshold. The inference model uses a deep denoising autoencoder to effectively learn the complex probabilistic relationship among the input features, and employs adversarial training that establishes a minimax game between a discriminator and a generator to accurately discriminate between positive samples and negative samples in the data distribution. We show that the model outperforms a set of well-known classification methods in experiments, and its applications in two commercial banks have reduced losses of about 10 million RMB in twelve weeks and significantly improved their business reputation. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multilayer Calorimeters

    Science.gov (United States)

    Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin

    2018-01-01

    Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of particle collisions to build expectations of what experimental data may look like under different theoretical modeling assumptions. Petabytes of simulated data are needed to develop analysis techniques, though they are expensive to generate using existing algorithms and computing resources. The modeling of detectors and the precise description of particle cascades as they interact with the material in the calorimeter are the most computationally demanding steps in the simulation pipeline. We therefore introduce a deep neural network-based generative model to enable high-fidelity, fast, electromagnetic calorimeter simulation. There are still challenges for achieving precision across the entire phase space, but our current solution can reproduce a variety of particle shower properties while achieving speedup factors of up to 100 000 × . This opens the door to a new era of fast simulation that could save significant computing time and disk space, while extending the reach of physics searches and precision measurements at the LHC and beyond.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

  4. A structural analysis of the Minas da Panasqueira vein network and related fracture generations

    Science.gov (United States)

    Jacques, Dominique; Vieira, Romeu; Muchez, Philippe; Sintubin, Manuel

    2014-05-01

    The Minas da Panasqueira is a world-class W-Cu-Sn vein-type deposit, situated within the Central Iberian Zone of the Palaeozoic Iberian Massif (Portugal). The deposit consists of a network of subhorizontal, sill-like massive quartz veins situated above the southwestern extremity of a greisen cupola, within regionally metamorphosed, isoclinally folded, lower-greenschist slates and greywackes. The greisen cupola is part of a larger intrusive complex, emplaced during the late- to post-tectonic stage of the Variscan orogeny. The late-Variscan granitoid(s) underlying the Panasqueira deposit is considered to have served as a major metal source. The structure of the network of subhorizontal extension veins, consists of numerous planar vein lobes that are separated by host-rock bridges and merge at branch-points. A structural analysis demonstrates that not only within the Panasqueira mine, but also on a more regional scale, one or more generations of flat-lying fractures are present. The veins clearly exploited these pre-existing discontinuities, as confirmed by (1) the vein geometry being directly influenced by variations in the orientation of the initial fracture sets and (2) the geometry of the rock bridges and overlapping vein morphologies, consistently showing straight-line propagating crack tips. If veining is governed by a preferential, strongly developed anisotropy in the host rock, the hypothesis of vein lobes and rock bridges forming during propagation of the parent crack by tip-line bifurcation and confinement processes (Foxford et al., 2000) does not seem plausible. Instead, we propose that the rock bridges formed from several, initially separate and small veinlets that eventually overlapped in an en echelon arrangement during progressive propagation and inflation. Bending of the rock bridges and incipient vein rotation indicate that veining occurred near the brittle-ductile transition. Using a quantitative analysis of bridge orientations, vein aspect ratios

  5. Comprehensive Cost Minimization in Distribution Networks Using Segmented-time Feeder Reconfiguration and Reactive Power Control of Distributed Generators

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Chen, Zhe

    2016-01-01

    In this paper, an efficient methodology is proposed to deal with segmented-time reconfiguration problem of distribution networks coupled with segmented-time reactive power control of distributed generators. The target is to find the optimal dispatching schedule of all controllable switches...... (FAHPSO) is implemented in VC++ 6.0 program language. A modified version of the typical 70-node distribution network and several real distribution networks are used to test the performance of the proposed method. Numerical results show that the proposed methodology is an efficient method for comprehensive...

  6. Interaction of the IoT Traffic Generated by a Smart City Segment with SDN Core Network

    OpenAIRE

    Volkov, Artem; Khakimov, Abdukodir; Muthanna, Ammar; Kirichek, Ruslan; Vladyko, Andrei; Koucheryavy, Andrey

    2017-01-01

    Part 3: Network Design and Planning; International audience; The main purpose of this article is to test IoT management system based on SDN core network, as well as interaction IoT traffic with SDN-switches. To conduct investigation of management system and network infrastructure behavior we carried out several IoT traffic tests, which were generated based on partnership project oneM2M specification. In this work, we considered “Smart city” model for Central district of Saint-Petersburg (Russ...

  7. k-Same-Net: k-Anonymity with Generative Deep Neural Networks for Face Deidentification

    Directory of Open Access Journals (Sweden)

    Blaž Meden

    2018-01-01

    Full Text Available Image and video data are today being shared between government entities and other relevant stakeholders on a regular basis and require careful handling of the personal information contained therein. A popular approach to ensure privacy protection in such data is the use of deidentification techniques, which aim at concealing the identity of individuals in the imagery while still preserving certain aspects of the data after deidentification. In this work, we propose a novel approach towards face deidentification, called k-Same-Net, which combines recent Generative Neural Networks (GNNs with the well-known k-Anonymitymechanism and provides formal guarantees regarding privacy protection on a closed set of identities. Our GNN is able to generate synthetic surrogate face images for deidentification by seamlessly combining features of identities used to train the GNN model. Furthermore, it allows us to control the image-generation process with a small set of appearance-related parameters that can be used to alter specific aspects (e.g., facial expressions, age, gender of the synthesized surrogate images. We demonstrate the feasibility of k-Same-Net in comprehensive experiments on the XM2VTS and CK+ datasets. We evaluate the efficacy of the proposed approach through reidentification experiments with recent recognition models and compare our results with competing deidentification techniques from the literature. We also present facial expression recognition experiments to demonstrate the utility-preservation capabilities of k-Same-Net. Our experimental results suggest that k-Same-Net is a viable option for facial deidentification that exhibits several desirable characteristics when compared to existing solutions in this area.

  8. Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

    Science.gov (United States)

    Karpatne, A.; Kumar, V.

    2017-12-01

    Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

  9. Generation and quality assessment of route choice sets in public transport networks by means of RP data analysis

    DEFF Research Database (Denmark)

    Larsen, Marie Karen; Nielsen, Otto Anker; Prato, Carlo Giacomo

    2010-01-01

    discrete choice models, this paper focuses on the issue of choice set generation in public transport networks. Specifically, this paper describes the generation of choice sets for users of the Greater Copenhagen public transport system by applying a doubly stochastic path generation algorithm......Literature in route choice modelling shows that a lot of attention has been devoted to route choices of car drivers, but much less attention has been dedicated to route choices of public transport users. As modelling route choice behaviour consists of generating relevant routes and estimating...... and evaluating the ability to reproduce choices collected in the Danish Travel Survey....

  10. Photovoltaic generator. Estimate of the energy produced by neural networks; Generador fotovoltaico. Estimacion de la energia producida mediante redes neuronales

    Energy Technology Data Exchange (ETDEWEB)

    Almonacid, F.; Rus, C.; Perez-Higueras, P.; Hontoria, L.

    2010-07-01

    Despite the great technological advances in photovoltaic and in particular in network-connected systems, efforts are still required in research, technological development and innovation (i + d + i) must be aimed primarily at addressing the different system parts. one aspect that can help achieve this goal is majorette estimation methods of energy produced by photovoltaic generators. There are a number of cases resulting in a decrease of the expected energy. In this paper we will compare a standard method widely used in the estimation of the power of the photovoltaic generator with another novel method, developed at the University of Jaen, based on artificial neural networks (ANN). (Author) 9 refs.

  11. Is the "I"generation a "We" Generation? Social Networking Use among 9- to 13-Year-Olds and Belonging

    Science.gov (United States)

    Quinn, Sally; Oldmeadow, Julian A.

    2013-01-01

    Research suggests that online communication is associated with increased closeness to friends and friendship quality. Children under 13 years of age are increasingly using social networking sites (SNSs), but research with this younger age group is scarce. This study examined the relationship between SNS use and feelings of belonging among children…

  12. 3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

    Science.gov (United States)

    Ross, Muriel D.; Meyer, Glenn; Lam, Tony; Cutler, Lynn; Vaziri, Parshaw

    1990-01-01

    Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

  13. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Science.gov (United States)

    Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

    2014-01-01

    In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

  14. Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

    Directory of Open Access Journals (Sweden)

    Ana eBengoetxea

    2014-09-01

    Full Text Available In this study we employed a dynamic recurrent neural network (DRNN in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane. We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others patterns of reciprocal activation operating in orthogonal

  15. Comparison of a spiking neural network and an MLP for robust identification of generator dynamics in a multimachine power system.

    Science.gov (United States)

    Johnson, Cameron; Venayagamoorthy, Ganesh Kumar; Mitra, Pinaki

    2009-01-01

    The application of a spiking neural network (SNN) and a multi-layer perceptron (MLP) for online identification of generator dynamics in a multimachine power system are compared in this paper. An integrate-and-fire model of an SNN which communicates information via the inter-spike interval is applied. The neural network identifiers are used to predict the speed and terminal voltage deviations one time-step ahead of generators in a multimachine power system. The SNN is developed in two steps: (i) neuron centers determined by offline k-means clustering and (ii) output weights obtained by online training. The sensitivity of the SNN to the neuron centers determined in the first step is evaluated on generators of different ratings and parameters. Performances of the SNN and MLP are compared to evaluate robustness on the identification of generator dynamics under small and large disturbances, and to illustrate that SNNs are capable of learning nonlinear dynamics of complex systems.

  16. PROVISIONING RESTORABLE VIRTUAL PRIVATE NETWORKS USING BARABASI AND WAXMAN TOPOLOGY GENERATION MODEL

    Directory of Open Access Journals (Sweden)

    R. Ravi

    2010-12-01

    Full Text Available As internet usage grows exponentially, network security issues become increasingly important. Network security measures are needed to protect data during transmission. Various security controls are used to prevent the access of hackers in networks. They are firewall, virtual private networks and encryption algorithms. Out of these, the virtual private network plays a vital role in preventing hackers from accessing the networks. A Virtual Private Network (VPN provides end users with a way to privately access information on their network over a public network infrastructure such as the internet. Using a technique called “Tunneling”, data packets are transmitted across a public routed network, such as the internet that simulates a point-to-point connection. Virtual private networks provide customers with a secure and low-cost communication environment. The basic structure of the virtual circuit is to create a logical path from the source port to the destination port. This path may incorporate many hops between routers for the formation of the circuit. The final, logical path or virtual circuit acts in the same way as a direct connection between the two ports. Our proposed Provisioning Restorable Virtual Private Networks Algorithm (PRA is used to combine the provisioning and restoration algorithms to achieve better results than the ones obtained by independent restoration and provisioning. In order to ensure service quality and availability in Virtual Private Networks, seamless recovery from failures is essential. The quality of service of the Virtual Private Networks is also improved due to the combination of provisioning and restoration. The bandwidth sharing concept is also applied in link to improve the quality of service in the Virtual Private Network. The performance analysis of the proposed algorithm is carried out in terms of cost, the number of nodes, the number of VPN nodes, delay, asymmetric ratio and delay with constraints with

  17. Generation of a superposition of odd photon number states for quantum information networks

    DEFF Research Database (Denmark)

    Neergaard-Nielsen, Jonas Schou; Nielsen, B.; Hettich, C.

    2006-01-01

    Quantum information networks, quantum memories, quantum repeaters, linear optics quantum computers Udgivelsesdato: 25 August......Quantum information networks, quantum memories, quantum repeaters, linear optics quantum computers Udgivelsesdato: 25 August...

  18. Low-cost design of next generation SONET/SDH networks with multiple constraints

    CSIR Research Space (South Africa)

    Karem, TR

    2007-07-01

    Full Text Available on constraints programming satisfaction technology is proposed. The algorithm is tested in OPNET simulation environment using different network models derived from a hypothetical case study of an optical network design for Bellville area in Cape Town, South...

  19. Neuropeptidomics Mass Spectrometry Reveals Signaling Networks Generated by Distinct Protease Pathways in Human Systems

    Science.gov (United States)

    Hook, Vivian; Bandeira, Nuno

    2015-12-01

    Neuropeptides regulate intercellular signaling as neurotransmitters of the central and peripheral nervous systems, and as peptide hormones in the endocrine system. Diverse neuropeptides of distinct primary sequences of various lengths, often with post-translational modifications, coordinate and integrate regulation of physiological functions. Mass spectrometry-based analysis of the diverse neuropeptide structures in neuropeptidomics research is necessary to define the full complement of neuropeptide signaling molecules. Human neuropeptidomics has notable importance in defining normal and dysfunctional neuropeptide signaling in human health and disease. Neuropeptidomics has great potential for expansion in translational research opportunities for defining neuropeptide mechanisms of human diseases, providing novel neuropeptide drug targets for drug discovery, and monitoring neuropeptides as biomarkers of drug responses. In consideration of the high impact of human neuropeptidomics for health, an observed gap in this discipline is the few published articles in human neuropeptidomics compared with, for example, human proteomics and related mass spectrometry disciplines. Focus on human neuropeptidomics will advance new knowledge of the complex neuropeptide signaling networks participating in the fine control of neuroendocrine systems. This commentary review article discusses several human neuropeptidomics accomplishments that illustrate the rapidly expanding diversity of neuropeptides generated by protease processing of pro-neuropeptide precursors occurring within the secretory vesicle proteome. Of particular interest is the finding that human-specific cathepsin V participates in producing enkephalin and likely other neuropeptides, indicating unique proteolytic mechanisms for generating human neuropeptides. The field of human neuropeptidomics has great promise to solve new mechanisms in disease conditions, leading to new drug targets and therapeutic agents for human

  20. On Study of Construction of New Generation Intelligent Communication Network for Distribution System

    Science.gov (United States)

    Wu, Dan; Zhang, Xueyan

    2017-09-01

    many new technological means are integrated in the new network of smart electricity distribution including electric power technology, control technology and information technology, and in this area, people carry out profound research to the construction of communication network and power distribution network. This paper analyzes specific structures of the communication network for distribution system, discusses the development trend of it, explores its technical system in depth, and finally proposes some concrete constructive strategies, hoping to be a valuable reference for related research persons.

  1. Estimating Route Choice Models from Stochastically Generated Choice Sets on Large-Scale Networks Correcting for Unequal Sampling Probability

    DEFF Research Database (Denmark)

    Vacca, Alessandro; Prato, Carlo Giacomo; Meloni, Italo

    2015-01-01

    is the dependency of the parameter estimates from the choice set generation technique. Bias introduced in model estimation has been corrected only for the random walk algorithm, which has problematic applicability to large-scale networks. This study proposes a correction term for the sampling probability of routes...

  2. From 1D to 3D: A new route to fabricate tridimensional structures via photo-generation of silver networks

    NARCIS (Netherlands)

    Wang, Zhanhua; Shen, Huaizhong; Wu, Yuxin; Fang, Liping; Ye, Shunsheng; Wang, Zhaoyi; Liu, Wendong; Cheng, Zhongkai; Zhang, Junhu; Yang, Bai

    2015-01-01

    A rapid and cost effective method has been developed to fabricate 3 dimensional (3D) ordered structures by photo-generating silver networks inside a 1D layered heterogeneous laminate composed of poly(vinyl alcohol) (PVA) and poly(methyl methacrylate) (PMMA). By designing the photo-mask meticulously,

  3. Three-phase Unbalanced Interval Power Flow Calculation of Low-voltage Distribution Network with Distributed PV Power Generation

    Science.gov (United States)

    Yuan, Yan; Shunjiang, Lin; Yuan, Lu

    2017-05-01

    Low-voltage distribution network is a three-phase unbalanced system due to the integration of single-phase loads and single-phase distributed PV arrays. In this paper, three-phase unbalanced interval power flow calculation model of three-phase four-wire low voltage distribution network with distributed PV power generation is established. In the model, intensity of illumination and battery temperature which influence the power output of distributed PV power generation is described as intervals. Then, through the affine interval algorithm, the interval power flow problem is transformed into a deterministic power flow problem and two linear optimization problems. By solving the above problems, the interval power flow solution can be obtained. Finally, the proposed algorithm is applied to an actual 22-bus low-voltage distribution network, and the solution of the affine interval algorithm is compared to the solution of the Monte Carlo sampling method, which verifies the correctness and effectiveness of the proposed algorithm.

  4. Neural networks for the generation of sea bed models using airborne lidar bathymetry data

    Directory of Open Access Journals (Sweden)

    Kogut Tomasz

    2016-06-01

    Full Text Available Various sectors of the economy such as transport and renewable energy have shown great interest in sea bed models. The required measurements are usually carried out by ship-based echo sounding, but this method is quite expensive. A relatively new alternative is data obtained by airborne lidar bathymetry. This study investigates the accuracy of these data, which was obtained in the context of the project ‘Investigation on the use of airborne laser bathymetry in hydrographic surveying’. A comparison to multi-beam echo sounding data shows only small differences in the depths values of the data sets. The IHO requirements of the total horizontal and vertical uncertainty for laser data are met. The second goal of this paper is to compare three spatial interpolation methods, namely Inverse Distance Weighting (IDW, Delaunay Triangulation (TIN, and supervised Artificial Neural Networks (ANN, for the generation of sea bed models. The focus of our investigation is on the amount of required sampling points. This is analyzed by manually reducing the data sets. We found that the three techniques have a similar performance almost independently of the amount of sampling data in our test area. However, ANN are more stable when using a very small subset of points.

  5. Frequency interleaving towards spectrally efficient directly detected optical OFDM for next-generation optical access networks.

    Science.gov (United States)

    Mehedy, Lenin; Bakaul, Masuduzzaman; Nirmalathas, Ampalavanapillai

    2010-10-25

    In this paper, we theoretically analyze and demonstrate that spectral efficiency of a conventional direct detection based optical OFDM system (DDO-OFDM) can be improved significantly using frequency interleaving of adjacent DDO-OFDM channels where OFDM signal band of one channel occupies the spectral gap of other channel and vice versa. We show that, at optimum operating condition, the proposed technique can effectively improve the spectral efficiency of the conventional DDO-OFDM system as much as 50%. We also show that such a frequency interleaved DDO-OFDM system, with a bit rate of 48 Gb/s within 25 GHz bandwidth, achieves sufficient power budget after transmission over 25 km single mode fiber to be used in next-generation time-division-multiplexed passive optical networks (TDM-PON). Moreover, by applying 64- quadrature amplitude modulation (QAM), the system can be further scaled up to 96 Gb/s with a power budget sufficient for 1:16 split TDM-PON.

  6. Energy Efficiency in TDMA-Based Next-Generation Passive Optical Access Networks

    KAUST Repository

    Dhaini, Ahmad R.

    2014-06-01

    Next-generation passive optical network (PON) has been considered in the past few years as a cost-effective broadband access technology. With the ever-increasing power saving concern, energy efficiency has been an important issue in its operations. In this paper, we propose a novel sleep-time sizing and scheduling framework for the implementation of green bandwidth allocation (GBA) in TDMA-PONs. The proposed framework leverages the batch-mode transmission feature of GBA to minimize the overhead due to frequent ONU on-off transitions. The optimal sleeping time sequence of each ONU is determined in every cycle without violating the maximum delay requirement. With multiple ONUs possibly accessing the shared media simultaneously, a collision may occur. To address this problem, we propose a new sleep-time sizing mechanism, namely Sort-And-Shift (SAS), in which the ONUs are sorted according to their expected transmission start times, and their sleep times are shifted to resolve any possible collision while ensuring maximum energy saving. Results show the effectiveness of the proposed framework and highlight the merits of our solutions.

  7. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    International Nuclear Information System (INIS)

    AlRashidi, M.R.; AlHajri, M.F.

    2011-01-01

    Highlights: → A new hybrid PSO for optimal DGs placement and sizing. → Statistical analysis to fine tune PSO parameters. → Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  8. Nanostructured Bulk Thermoelectric Generator for Efficient Power Harvesting for Self-powered Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yanliang [Idaho National Lab. (INL), Idaho Falls, ID (United States); Butt, Darryl [Idaho National Lab. (INL), Idaho Falls, ID (United States); Agarwal, Vivek [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-07-01

    The objective of this Nuclear Energy Enabling Technology research project is to develop high-efficiency and reliable thermoelectric generators for self-powered wireless sensors nodes utilizing thermal energy from nuclear plant or fuel cycle. The power harvesting technology has crosscutting significance to address critical technology gaps in monitoring nuclear plants and fuel cycle. The outcomes of the project will lead to significant advancement in sensors and instrumentation technology, reducing cost, improving monitoring reliability and therefore enhancing safety. The self-powered wireless sensor networks could support the long-term safe and economical operation of all the reactor designs and fuel cycle concepts, as well as spent fuel storage and many other nuclear science and engineering applications. The research is based on recent breakthroughs in high-performance nanostructured bulk (nanobulk) thermoelectric materials that enable high-efficiency direct heat-to-electricity conversion over a wide temperature range. The nanobulk thermoelectric materials that the research team at Boise State University and University of Houston has developed yield up to a 50% increase in the thermoelectric figure of merit, ZT, compared with state-of-the-art bulk counterparts. This report focuses on the selection of optimal thermoelectric materials for this project. The team has performed extensive study on two thermoelectric materials systems, i.e. the half-Heusler materials, and the Bismuth-Telluride materials. The report contains our recent research results on the fabrication, characterization and thermoelectric property measurements of these two materials.

  9. Opinion Mining for User Generated Design By Social Networking Service and Japanese Manga

    Directory of Open Access Journals (Sweden)

    Anak Agung Gede Dharma

    2011-12-01

    Full Text Available The growth of Social Networking Service (SNS has created a new potential in marketing. While users communicate and interact via SNS, the list of their conversation, which is called casual data can be used to determine their needs or aspirations. SNS can be very useful for product/service developers, especially when developing new ideas or simply evaluating the feasibility of their existing products/services. Furthermore, SNS provides a unique system that enables expressive and two-way communication between its users. SNS is known for its effectiveness in delivering fresh news and information, thus it can be used as promotional media. Although several online services that utilize SNS and casual data have been provided, the purpose of those services is still unclear and ineffective. In those services, users were only asked for their opinions without receiving sufficient feedbacks. Therefore, to solve these problems we propose an innovative way of utilizing SNS and casual data in designing user generated design. In our proposed system, users can directly contribute to the product/service development process in an interesting way. We designed an online service, which allows users to posts manga that describes their original idea. While contributing to the product/service development, they can also benefit from expressing their hobbies and receiving feedbacks from other users.

  10. PSFGAN: a generative adversarial network system for separating quasar point sources and host galaxy light

    Science.gov (United States)

    Stark, Dominic; Launet, Barthelemy; Schawinski, Kevin; Zhang, Ce; Koss, Michael; Turp, M. Dennis; Sartori, Lia F.; Zhang, Hantian; Chen, Yiru; Weigel, Anna K.

    2018-03-01

    The study of unobscured active galactic nuclei (AGN) and quasars depends on the reliable decomposition of the light from the AGN point source and the extended host galaxy light. The problem is typically approached using parametric fitting routines using separate models for the host galaxy and the point spread function (PSF). We present a new approach using a Generative Adversarial Network (GAN) trained on galaxy images. We test the method using Sloan Digital Sky Survey (SDSS) r-band images with artificial AGN point sources added which are then removed using the GAN and with parametric methods using GALFIT. When the AGN point source PS is more than twice as bright as the host galaxy, we find that our method, PSFGAN, can recover PS and host galaxy magnitudes with smaller systematic error and a lower average scatter (49%). PSFGAN is more tolerant to poor knowledge of the PSF than parametric methods. Our tests show that PSFGAN is robust against a broadening in the PSF width of ±50% if it is trained on multiple PSF's. We demonstrate that while a matched training set does improve performance, we can still subtract point sources using a PSFGAN trained on non-astronomical images. While initial training is computationally expensive, evaluating PSFGAN on data is more than 40 times faster than GALFIT fitting two components. Finally, PSFGAN it is more robust and easy to use than parametric methods as it requires no input parameters.

  11. Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

    Science.gov (United States)

    Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

    2011-12-01

    The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response.

  12. Batch Image Encryption Using Generated Deep Features Based on Stacked Autoencoder Network

    Directory of Open Access Journals (Sweden)

    Fei Hu

    2017-01-01

    Full Text Available Chaos-based algorithms have been widely adopted to encrypt images. But previous chaos-based encryption schemes are not secure enough for batch image encryption, for images are usually encrypted using a single sequence. Once an encrypted image is cracked, all the others will be vulnerable. In this paper, we proposed a batch image encryption scheme into which a stacked autoencoder (SAE network was introduced to generate two chaotic matrices; then one set is used to produce a total shuffling matrix to shuffle the pixel positions on each plain image, and another produces a series of independent sequences of which each is used to confuse the relationship between the permutated image and the encrypted image. The scheme is efficient because of the advantages of parallel computing of SAE, which leads to a significant reduction in the run-time complexity; in addition, the hybrid application of shuffling and confusing enhances the encryption effect. To evaluate the efficiency of our scheme, we compared it with the prevalent “logistic map,” and outperformance was achieved in running time estimation. The experimental results and analysis show that our scheme has good encryption effect and is able to resist brute-force attack, statistical attack, and differential attack.

  13. Optimal planning of multiple distributed generation sources in distribution networks: A new approach

    Energy Technology Data Exchange (ETDEWEB)

    AlRashidi, M.R., E-mail: malrash2002@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait); AlHajri, M.F., E-mail: mfalhajri@yahoo.com [Department of Electrical Engineering, College of Technological Studies, Public Authority for Applied Education and Training (PAAET) (Kuwait)

    2011-10-15

    Highlights: {yields} A new hybrid PSO for optimal DGs placement and sizing. {yields} Statistical analysis to fine tune PSO parameters. {yields} Novel constraint handling mechanism to handle different constraints types. - Abstract: An improved particle swarm optimization algorithm (PSO) is presented for optimal planning of multiple distributed generation sources (DG). This problem can be divided into two sub-problems: the DG optimal size (continuous optimization) and location (discrete optimization) to minimize real power losses. The proposed approach addresses the two sub-problems simultaneously using an enhanced PSO algorithm capable of handling multiple DG planning in a single run. A design of experiment is used to fine tune the proposed approach via proper analysis of PSO parameters interaction. The proposed algorithm treats the problem constraints differently by adopting a radial power flow algorithm to satisfy the equality constraints, i.e. power flows in distribution networks, while the inequality constraints are handled by making use of some of the PSO features. The proposed algorithm was tested on the practical 69-bus power distribution system. Different test cases were considered to validate the proposed approach consistency in detecting optimal or near optimal solution. Results are compared with those of Sequential Quadratic Programming.

  14. Optimization based on benefit of regional energy suppliers of distributed generation in active distribution network

    Science.gov (United States)

    Huo, Xianxu; Li, Guodong; Jiang, Ling; Wang, Xudong

    2017-08-01

    With the development of electricity market, distributed generation (DG) technology and related policies, regional energy suppliers are encouraged to build DG. Under this background, the concept of active distribution network (ADN) is put forward. In this paper, a bi-level model of intermittent DG considering benefit of regional energy suppliers is proposed. The objective of the upper level is the maximization of benefit of regional energy suppliers. On this basis, the lower level is optimized for each scene. The uncertainties of DG output and load of users, as well as four active management measures, which include demand-side management, curtailing the output power of DG, regulating reactive power compensation capacity and regulating the on-load tap changer, are considered. Harmony search algorithm and particle swarm optimization are combined as a hybrid strategy to solve the model. This model and strategy are tested with IEEE-33 node system, and results of case study indicate that the model and strategy successfully increase the capacity of DG and benefit of regional energy suppliers.

  15. Photoelectrochemical water splitting and hydrogen generation by a spontaneously formed InGaN nanowall network

    Energy Technology Data Exchange (ETDEWEB)

    Alvi, N. H., E-mail: nhalvi@isom.upm.es, E-mail: r.noetzel@isom.upm.es; Soto Rodriguez, P. E. D.; Kumar, Praveen; Gómez, V. J.; Aseev, P.; Nötzel, R., E-mail: nhalvi@isom.upm.es, E-mail: r.noetzel@isom.upm.es [ISOM Institute for Systems Based on Optoelectronics and Microtechnology, ETSI Telecomunicación, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); Alvi, A. H. [Department of Physics, Government College University, Faisalabad (Pakistan); Alvi, M. A. [Department of Chemistry, Government College University, Faisalabad (Pakistan); Willander, M. [Department of Science and Technology (ITN), Campus Norrköping, Linköping University, 60174 Norrköping (Sweden)

    2014-06-02

    We investigate photoelectrochemical water splitting by a spontaneously formed In-rich InGaN nanowall network, combining the material of choice with the advantages of surface texturing for light harvesting by light scattering. The current density for the InGaN-nanowalls-photoelectrode at zero voltage versus the Ag/AgCl reference electrode is 3.4 mA cm{sup −2} with an incident-photon-to-current-conversion efficiency (IPCE) of 16% under 350 nm laser illumination with 0.075 W·cm{sup −2} power density. In comparison, the current density for a planar InGaN-layer-photoelectrode is 2 mA cm{sup −2} with IPCE of 9% at zero voltage versus the Ag/AgCl reference electrode. The H{sub 2} generation rates at zero externally applied voltage versus the Pt counter electrode per illuminated area are 2.8 and 1.61 μmol·h{sup −1}·cm{sup −2} for the InGaN nanowalls and InGaN layer, respectively, revealing ∼57% enhancement for the nanowalls.

  16. Contemporary Studies Network Roundtable: Responding to Robert Macfarlane’s ‘Generation Anthropocene’

    Directory of Open Access Journals (Sweden)

    Rachel Sykes

    2017-02-01

    Full Text Available In April 2016, 'The Guardian' published ‘Generation Anthropocene: How humans have altered the planet forever’ by the celebrated academic and nature writer Robert Macfarlane. Reflecting on the article’s importance as a critical experiment and, perhaps, a vital form of public engagement, Contemporary Studies Network (CSN asked six of its members, working across very different areas of literary and cultural studies, to respond to and extend Macfarlane’s article, mapping the different ways in which literary scholars might approach the age of the Anthropocene. Conducted via email, this roundtable conversation asks to what extent the Anthropocene marks a new era in literary criticism, how exactly it extends preexisting strands of ecocriticism and trauma studies, and what the global scope of the term might be beyond the confines of the Western literary canon. Discussion ranges from issues of temporality to genre and form and it also addresses Macfarlane’s rhetoric, his call to arms for those working in the humanities, for a more comprehensive investigation in to the roles of literature and art in responding to and representing what may become a new epoch.

  17. A Combination of Central Pattern Generator-based and Reflex-based Neural Networks for Dynamic, Adaptive, Robust Bipedal Locomotion

    DEFF Research Database (Denmark)

    Di Canio, Giuliano; Larsen, Jørgen Christian; Wörgötter, Florentin

    2016-01-01

    Robotic systems inspired from humans have always been lightening up the curiosity of engineers and scientists. Of many challenges, human locomotion is a very difficult one where a number of different systems needs to interact in order to generate a correct and balanced pattern. To simulate...... the interaction of these systems, implementations with reflexbased or central pattern generator (CPG)-based controllers have been tested on bipedal robot systems. In this paper we will combine the two controller types, into a controller that works with both reflex and CPG signals. We use a reflex-based neural...... network to generate basic walking patterns of a dynamic bipedal walking robot (DACBOT) and then a CPG-based neural network to ensure robust walking behavior...

  18. A neural network with central pattern generators entrained by sensory feedback controls walking of a bipedal model.

    Science.gov (United States)

    Li, Wei; Szczecinski, Nicholas S; Quinn, Roger D

    2017-10-16

    A neuromechanical simulation of a planar, bipedal walking robot has been developed. It is constructed as a simplified, planar musculoskeletal model of the biomechanics of the human lower body. The controller consists of a dynamic neural network with central pattern generators (CPGs) entrained by force and movement sensory feedback to generate appropriate muscle forces for walking. The CPG model is a two-level architecture, which consists of separate rhythm generator and pattern formation networks. The biped model walks stably in the sagittal plane without inertial sensors or a centralized posture controller or a 'baby walker' to help overcome gravity. Its gait is similar to humans' and it walks at speeds from 0.850 m s -1 up to 1.289 m s -1 with leg length of 0.84 m. The model walks over small unknown steps (6% of leg length) and up and down 5° slopes without any additional higher level control actions.

  19. Establishment of database and network for research of stream generator and state of the art technology review

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Jae Bong; Hur, Nam Su; Moon, Seong In; Seo, Hyeong Won; Park, Bo Kyu; Park, Sung Ho; Kim, Hyung Geun [Sungkyunkwan Univ., Seoul (Korea, Republic of)

    2004-02-15

    A significant number of steam generator tubes are defective and are removed from service or repaired world widely. This wide spread damage has been caused by diverse degradation mechanisms, some of which are difficult to detect and predict. Regarding domestic nuclear power plants, also, the increase of number of operating nuclear power plants and operating periods may result in the increase of steam generator tube failure. So, it is important to carry out the integrity evaluation process to prevent the steam generator tube damage. There are two objectives of this research. The one is to make database for the research of steam generator at domestic research institution. It will increase the efficiency and capability of limited domestic research resources by sharing data and information through network organization. Also, it will enhance the current standard of integrity evaluation procedure that is considerably conservative but can be more reasonable. The second objective is to establish the standard integrity evaluation procedure for steam generator tube by reviewing state of the art technology. The research resources related to steam generator tubes are managed by the established web-based database system. The following topics are covered in this project: development of web-based network for research on steam generator tubes review of state of the art technology.

  20. The Use of Enterprise Social Networks in Organizations from the Perspective of Generation Y in the Czech Republic

    Directory of Open Access Journals (Sweden)

    Becan Martin

    2016-03-01

    Full Text Available The article presents the views of the Czech Generation Y on the use of enterprise social networks and their expectations and ideas about the use of communication methods or tools in the context of communication and collaboration in an organization. Emphasis is placed on the possibility of using enterprise social networks in the organizational context. The questionnaire survey that was conducted (838 respondents completes the view of Czech managers on communication in organizations examined in the European Communication Monitor 2014. This research highlights the different ideas of representatives of Generation Y on personal and professional communication. The distinction lies between the communication methods they commonly use in private life or in the course of their studies and their perception of what methods are or will be used in organizational context for internal communication. Finally, the article discusses institutional resistance in implementing enterprise social networking in an organization. It follows from a broader discussion that an important determinant of success in implementing enterprise social networks is not only the willingness of ordinary employees to use them, but also that of managers. On the one hand, they want enterprise social networks to be used by their employees, but on the other hand, they do not want to use them themselves.

  1. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

    Directory of Open Access Journals (Sweden)

    Zhaoyuan Yu

    2015-12-01

    Full Text Available Passive infrared (PIR motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  2. Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

    Science.gov (United States)

    Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

    2015-12-30

    Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

  3. Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions.

    Science.gov (United States)

    Testolin, Alberto; Zorzi, Marco

    2016-01-01

    Connectionist models can be characterized within the more general framework of probabilistic graphical models, which allow to efficiently describe complex statistical distributions involving a large number of interacting variables. This integration allows building more realistic computational models of cognitive functions, which more faithfully reflect the underlying neural mechanisms at the same time providing a useful bridge to higher-level descriptions in terms of Bayesian computations. Here we discuss a powerful class of graphical models that can be implemented as stochastic, generative neural networks. These models overcome many limitations associated with classic connectionist models, for example by exploiting unsupervised learning in hierarchical architectures (deep networks) and by taking into account top-down, predictive processing supported by feedback loops. We review some recent cognitive models based on generative networks, and we point out promising research directions to investigate neuropsychological disorders within this approach. Though further efforts are required in order to fill the gap between structured Bayesian models and more realistic, biophysical models of neuronal dynamics, we argue that generative neural networks have the potential to bridge these levels of analysis, thereby improving our understanding of the neural bases of cognition and of pathologies caused by brain damage.

  4. Application of signal processing techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Raza, Safdar; Mokhlis, Hazlie; Arof, Hamzah; Laghari, J.A.; Wang, Li

    2015-01-01

    Highlights: • Pros & cons of conventional islanding detection techniques (IDTs) are discussed. • Signal processing techniques (SPTs) ability in detecting islanding is discussed. • SPTs ability in improving performance of passive techniques are discussed. • Fourier, s-transform, wavelet, HHT & tt-transform based IDTs are reviewed. • Intelligent classifiers (ANN, ANFIS, Fuzzy, SVM) application in SPT are discussed. - Abstract: High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system. However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equipment damage, grid protection interference, and personnel safety hazards. Islanding detection techniques are mainly classified into remote, passive, active, and hybrid techniques. From these, passive techniques are more advantageous due to lower power quality degradation, lower cost, and widespread usage by power utilities. However, the main limitations of these techniques are that they possess a large non detection zones and require threshold setting. Various signal processing techniques and intelligent classifiers have been used to overcome the limitations of passive islanding. Signal processing techniques, in particular, are adopted due to their versatility, stability, cost effectiveness, and ease of modification. This paper presents a comprehensive overview of signal processing techniques used to improve common passive islanding detection techniques. A performance comparison between the signal processing based islanding detection techniques with existing techniques are also provided. Finally, this paper outlines the relative advantages and limitations of the signal processing techniques in order to provide basic guidelines for researchers and field engineers in determining the best method for their system

  5. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Directory of Open Access Journals (Sweden)

    Paul Tonelli

    Full Text Available A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1 the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2 synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT. Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1 in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2 whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  6. On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks.

    Science.gov (United States)

    Tonelli, Paul; Mouret, Jean-Baptiste

    2013-01-01

    A major goal of bio-inspired artificial intelligence is to design artificial neural networks with abilities that resemble those of animal nervous systems. It is commonly believed that two keys for evolving nature-like artificial neural networks are (1) the developmental process that links genes to nervous systems, which enables the evolution of large, regular neural networks, and (2) synaptic plasticity, which allows neural networks to change during their lifetime. So far, these two topics have been mainly studied separately. The present paper shows that they are actually deeply connected. Using a simple operant conditioning task and a classic evolutionary algorithm, we compare three ways to encode plastic neural networks: a direct encoding, a developmental encoding inspired by computational neuroscience models, and a developmental encoding inspired by morphogen gradients (similar to HyperNEAT). Our results suggest that using a developmental encoding could improve the learning abilities of evolved, plastic neural networks. Complementary experiments reveal that this result is likely the consequence of the bias of developmental encodings towards regular structures: (1) in our experimental setup, encodings that tend to produce more regular networks yield networks with better general learning abilities; (2) whatever the encoding is, networks that are the more regular are statistically those that have the best learning abilities.

  7. Multi-Objective Distribution Network Operation Based on Distributed Generation Optimal Placement Using New Antlion Optimizer Considering Reliability

    Directory of Open Access Journals (Sweden)

    KHANBABAZADEH Javad

    2016-10-01

    Full Text Available Distribution network designers and operators are trying to deliver electrical energy with high reliability and quality to their subscribers. Due to high losses in the distribution systems, using distributed generation can improves reliability, reduces losses and improves voltage profile of distribution network. Therefore, the choice of the location of these resources and also determining the amount of their generated power to maximize the benefits of this type of resource is an important issue which is discussed from different points of view today. In this paper, a new multi-objective optimal location and sizing of distributed generation resources is performed to maximize its benefits on the 33 bus distribution test network considering reliability and using a new Antlion Optimizer (ALO. The benefits for DG are considered as system losses reduction, system reliability improvement and benefits from the sale electricity and voltage profile improvement. For each of the mentioned benefits, the ALO algorithm is used to optimize the location and sizing of distributed generation resources. In order to verify the proposed approach, the obtained results have been analyzed and compared with the results of particle swarm optimization (PSO algorithm. The results show that the ALO has shown better performance in optimization problem solution versus PSO.

  8. Using IP as Transport Technology in Third Generation and Beyond Radio Access Networks

    NARCIS (Netherlands)

    Bader, Attila; Westberg, Lars; Karagiannis, Georgios; de Meer, H; Bhatti, N.T.

    This paper discusses the motivation for developing a new QoS signaling protocol for IP-based Radio Access Networks. It describes the main characteristics of these networks and the special requirements imposed by these characteristics on QoS signaling solutions.

  9. A Generational Comparison of Social Networking Site Use: The Influence of Age and Social Identity

    Science.gov (United States)

    Barker, Valerie

    2012-01-01

    An online survey (N = 256) compared social networking site (SNS) use among younger (millennial: 18-29) and older (baby-boomer: 41-64) subscribers focusing on the influence of collective self-esteem and group identity on motives for SNS use. Younger participants reported higher positive collective self-esteem, social networking site use for peer…

  10. Response of pressurized water reactor (PWR) to network power generation demands

    International Nuclear Information System (INIS)

    Schreiner, L.A.

    1991-01-01

    The flexibility of the PWR type reactor in terms of response to the variations of the network power demands, is demonstrated. The factors that affect the transitory flexibility and some design prospects that allow the reactor fits the requirements of the network power demands, are also discussed. (M.J.A.)

  11. MobiHealth: Ambulant Patient Monitoring Over Next Generation Public Wireless Networks

    NARCIS (Netherlands)

    van Halteren, Aart; Konstantas, D.; Bults, Richard G.A.; Wac, K.E.; Dokovski, N.T.; Koprinkov, G.T.; Jones, Valerie M.; Widya, I.A.; Demiris, G.

    2004-01-01

    The wide availability of high bandwidth public wireless networks as well as the miniaturisation of medical sensors and network access hardware allows the development of advanced ambulant patient monitoring systems. The MobiHealth project developed a complete system and service that allows the

  12. Multiplexed entanglement generation over quantum networks using multi-qubit nodes

    Science.gov (United States)

    van Dam, Suzanne B.; Humphreys, Peter C.; Rozpędek, Filip; Wehner, Stephanie; Hanson, Ronald

    2017-09-01

    Quantum networks distributed over distances greater than a few kilometres will be limited by the time required for information to propagate between nodes. We analyse protocols that are able to circumvent this bottleneck by employing multi-qubit nodes and multiplexing. For each protocol, we investigate the key network parameters that determine its performance. We model achievable entangling rates based on the anticipated near-term performance of nitrogen-vacancy centres and other promising network platforms. This analysis allows us to compare the potential of the proposed multiplexed protocols in different regimes. Moreover, by identifying the gains that may be achieved by improving particular network parameters, our analysis suggests the most promising avenues for research and development of prototype quantum networks.

  13. Self-generation of controller of an underwater robot with neural network

    International Nuclear Information System (INIS)

    Suto, T.; Ura, T.

    1994-01-01

    A self-organizing controller system is constructed based on artificial neural networks and applied to constant altitude swimming of the autonomous underwater robot PTEROA 150. The system consists of a controller and a forward model which calculates the values for evaluation as a result of control. Some methods are introduced for quick and appropriate adjustment of the controller network. Modification of the controller network is executed based on error-back-propagation method utilizing the forward model network. The forward model is divided into three sub-networks which represent dynamics of the vehicle, estimation of relative position to the seabed and calculation of the altitude. The proposed adaptive system is demonstrated in computer simulations where objective of a vehicle is keeping a constant altitude from seabed which is constituted of triangular ridges

  14. AN IMPROVEMENT ON GEOMETRY-BASED METHODS FOR GENERATION OF NETWORK PATHS FROM POINTS

    Directory of Open Access Journals (Sweden)

    Z. Akbari

    2014-10-01

    Full Text Available Determining network path is important for different purposes such as determination of road traffic, the average speed of vehicles, and other network analysis. One of the required input data is information about network path. Nevertheless, the data collected by the positioning systems often lead to the discrete points. Conversion of these points to the network path have become one of the challenges which different researchers, presents many ways for solving it. This study aims at investigating geometry-based methods to estimate the network paths from the obtained points and improve an existing point to curve method. To this end, some geometry-based methods have been studied and an improved method has been proposed by applying conditions on the best method after describing and illustrating weaknesses of them.

  15. Location and Size Planning of Distributed Photovoltaic Generation in Distribution network System Based on K-means Clustering Analysis

    Science.gov (United States)

    Lu, Siqi; Wang, Xiaorong; Wu, Junyong

    2018-01-01

    The paper presents a method to generate the planning scenarios, which is based on K-means clustering analysis algorithm driven by data, for the location and size planning of distributed photovoltaic (PV) units in the network. Taken the power losses of the network, the installation and maintenance costs of distributed PV, the profit of distributed PV and the voltage offset as objectives and the locations and sizes of distributed PV as decision variables, Pareto optimal front is obtained through the self-adaptive genetic algorithm (GA) and solutions are ranked by a method called technique for order preference by similarity to an ideal solution (TOPSIS). Finally, select the planning schemes at the top of the ranking list based on different planning emphasis after the analysis in detail. The proposed method is applied to a 10-kV distribution network in Gansu Province, China and the results are discussed.

  16. PUFKEY: A High-Security and High-Throughput Hardware True Random Number Generator for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Dongfang Li

    2015-10-01

    Full Text Available Random number generators (RNG play an important role in many sensor network systems and applications, such as those requiring secure and robust communications. In this paper, we develop a high-security and high-throughput hardware true random number generator, called PUFKEY, which consists of two kinds of physical unclonable function (PUF elements. Combined with a conditioning algorithm, true random seeds are extracted from the noise on the start-up pattern of SRAM memories. These true random seeds contain full entropy. Then, the true random seeds are used as the input for a non-deterministic hardware RNG to generate a stream of true random bits with a throughput as high as 803 Mbps. The experimental results show that the bitstream generated by the proposed PUFKEY can pass all standard national institute of standards and technology (NIST randomness tests and is resilient to a wide range of security attacks.

  17. PUFKEY: a high-security and high-throughput hardware true random number generator for sensor networks.

    Science.gov (United States)

    Li, Dongfang; Lu, Zhaojun; Zou, Xuecheng; Liu, Zhenglin

    2015-10-16

    Random number generators (RNG) play an important role in many sensor network systems and applications, such as those requiring secure and robust communications. In this paper, we develop a high-security and high-throughput hardware true random number generator, called PUFKEY, which consists of two kinds of physical unclonable function (PUF) elements. Combined with a conditioning algorithm, true random seeds are extracted from the noise on the start-up pattern of SRAM memories. These true random seeds contain full entropy. Then, the true random seeds are used as the input for a non-deterministic hardware RNG to generate a stream of true random bits with a throughput as high as 803 Mbps. The experimental results show that the bitstream generated by the proposed PUFKEY can pass all standard national institute of standards and technology (NIST) randomness tests and is resilient to a wide range of security attacks.

  18. Distribution of networks generating and coordinating locomotor activity in the neonatal rat spinal cord in vitro: a lesion study

    DEFF Research Database (Denmark)

    Kjaerulff, O; Kiehn, O

    1996-01-01

    that the isolated ventral third of the spinal cord can generate normally coordinated rhythmic activity, whereas lateral fragments resulting from sagittal sections showed little or no rhythmogenic capability compared with intact control preparations. The ability to generate fast and regular rhythmic activity...... ventral root recordings to monitor neuronal activity and tested the ability of various isolated parts of the caudal thoraciclumbar cord to generate rhythmic bursting in a combination of 5-HT and NMDA. In addition, pathways mediating left/right and rostrocaudal burst alternation were localized. We found...... decreased in the caudal direction, but the rhythm-generating network was found to be distributed over the entire lumbar region and to extend into the caudal thoracic region. The pathways mediating left/ right alternation exist primarily in the ventral commissure. As with the rhythmogenic ability...

  19. Electrochemically Smart Bimetallic Materials Featuring Group 11 Metals: In-situ Conductive Network Generation and Its Impact on Cell Capacity

    Energy Technology Data Exchange (ETDEWEB)

    Takeuchi, Esther [Stony Brook Univ., NY (United States)

    2016-11-30

    Our results for this program “Electrochemically smart bimetallic materials featuring Group 11 metals: in-situ conductive matrix generation and its impact on battery capacity, power and reversibility” have been highly successful: 1) we demonstrated material structures which generated in-situ conductive networks through electrochemical activation with increases in conductivity up to 10,000 fold, 2) we pioneered in situ analytical methodology to map the cathodes at several stages of discharge through the use of Energy Dispersive X-ray Diffraction (EDXRD) to elucidate the kinetic dependence of the conductive network formation, and 3) we successfully designed synthetic methodology for direct control of material properties including crystallite size and surface area which showed significant impact on electrochemical behavior.

  20. Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

    KAUST Repository

    AlQuerm, Ismail A.

    2018-02-21

    There is a large demand for applications of high data rates in wireless networks. These networks are becoming more complex and challenging to manage due to the heterogeneity of users and applications specifically in sophisticated networks such as the upcoming 5G. Energy efficiency in the future 5G network is one of the essential problems that needs consideration due to the interference and heterogeneity of the network topology. Smart resource allocation, environmental adaptivity, user-awareness and energy efficiency are essential features in the future networks. It is important to support these features at different networks topologies with various applications. Cognitive radio has been found to be the paradigm that is able to satisfy the above requirements. It is a very interdisciplinary topic that incorporates flexible system architectures, machine learning, context awareness and cooperative networking. Mitola’s vision about cognitive radio intended to build context-sensitive smart radios that are able to adapt to the wireless environment conditions while maintaining quality of service support for different applications. Artificial intelligence techniques including heuristics algorithms and machine learning are the shining tools that are employed to serve the new vision of cognitive radio. In addition, these techniques show a potential to be utilized in an efficient resource allocation for the upcoming 5G networks’ structures such as heterogeneous multi-tier 5G networks and heterogeneous cloud radio access networks due to their capability to allocate resources according to real-time data analytics. In this thesis, we study cognitive radio from a system point of view focusing closely on architectures, artificial intelligence techniques that can enable intelligent radio resource allocation and efficient radio parameters reconfiguration. We propose a modular cognitive resource management architecture, which facilitates a development of flexible control for

  1. Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring.

    Science.gov (United States)

    Sun, Li; Wong, Ka Chun; Wei, Peng; Ye, Sheng; Huang, Hao; Yang, Fenhuan; Westerdahl, Dane; Louie, Peter K K; Luk, Connie W Y; Ning, Zhi

    2016-02-05

    This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.

  2. Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring

    Directory of Open Access Journals (Sweden)

    Li Sun

    2016-02-01

    Full Text Available This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO and nitrogen dioxide (NO2 pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.

  3. Soft Handoff Evaluation and Efficient Access Network Selection in Next Generation Cellular Systems

    Directory of Open Access Journals (Sweden)

    Moses Ekpenyong

    2017-08-01

    Full Text Available The increased motivation (by service providers to offer user-centric and seamless communication services – that satisfies users’ quality of experience (QoE, has manifested a myriad of challenges in the field of wireless communication; and given the increased traffic capacity and sudden explosion of cellular devices, communication systems are constantly threatened by performance related issues – including soft handoff. Although intelligent techniques have evolved to provide solutions to these issues, they are yet to flourish in the area of soft handoff. This contribution therefore proposes a framework that integrates two components: (i machine learning methodologies: self-organizing map (SOM and pattern classification – for robust performance evaluation of available soft handoff data; (ii multiple attribute decision making mechanisms (MADM: the Analytical Hierarchy Process (AHP – which result feeds the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS – for efficient access network selection. Implementation of component one of the design revealed that SOM enabled a precise visualization of handoff features that influenced the system performance; and the error levels of training, validation and test dataset, with number and percentage of correct and incorrect classifications, were obtained from our pattern classifier. Implementation of component two of the design for four heterogeneous (access networks indicated that although network two (N2 was selected as best access network by TOPSIS and network three (N3 by Synthetic Extent Analysis (SEA – a method adopted in a related paper, for a particular application; both TOPSIS and SEA selected N1 as second best alternative access network and network four (N4 as third best alternative network, despite the issue of ranking abnormality in TOPSIS. Further, AHP and TOPSIS can effectively be applied as MADM algorithms in handoff decision framework for selecting the

  4. Modeling urbanization patterns at a global scale with generative adversarial networks

    Science.gov (United States)

    Albert, A. T.; Strano, E.; Gonzalez, M.

    2017-12-01

    Current demographic projections show that, in the next 30 years, global population growth will mostly take place in developing countries. Coupled with a decrease in density, such population growth could potentially double the land occupied by settlements by 2050. The lack of reliable and globally consistent socio-demographic data, coupled with the limited predictive performance underlying traditional urban spatial explicit models, call for developing better predictive methods, calibrated using a globally-consistent dataset. Thus, richer models of the spatial interplay between the urban built-up land, population distribution and energy use are central to the discussion around the expansion and development of cities, and their impact on the environment in the context of a changing climate. In this talk we discuss methods for, and present an analysis of, urban form, defined as the spatial distribution of macroeconomic quantities that characterize a city, using modern machine learning methods and best-available remote-sensing data for the world's largest 25,000 cities. We first show that these cities may be described by a small set of patterns in radial building density, nighttime luminosity, and population density, which highlight, to first order, differences in development and land use across the world. We observe significant, spatially-dependent variance around these typical patterns, which would be difficult to model using traditional statistical methods. We take a first step in addressing this challenge by developing CityGAN, a conditional generative adversarial network model for simulating realistic urban forms. To guide learning and measure the quality of the simulated synthetic cities, we develop a specialized loss function for GAN optimization that incorporates standard spatial statistics used by urban analysis experts. Our framework is a stark departure from both the standard physics-based approaches in the literature (that view urban forms as fractals with a

  5. DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing.

    Science.gov (United States)

    Vidaki, Athina; Ballard, David; Aliferi, Anastasia; Miller, Thomas H; Barron, Leon P; Syndercombe Court, Denise

    2017-05-01

    The ability to estimate the age of the donor from recovered biological material at a crime scene can be of substantial value in forensic investigations. Aging can be complex and is associated with various molecular modifications in cells that accumulate over a person's lifetime including epigenetic patterns. The aim of this study was to use age-specific DNA methylation patterns to generate an accurate model for the prediction of chronological age using data from whole blood. In total, 45 age-associated CpG sites were selected based on their reported age coefficients in a previous extensive study and investigated using publicly available methylation data obtained from 1156 whole blood samples (aged 2-90 years) analysed with Illumina's genome-wide methylation platforms (27K/450K). Applying stepwise regression for variable selection, 23 of these CpG sites were identified that could significantly contribute to age prediction modelling and multiple regression analysis carried out with these markers provided an accurate prediction of age (R 2 =0.92, mean absolute error (MAE)=4.6 years). However, applying machine learning, and more specifically a generalised regression neural network model, the age prediction significantly improved (R 2 =0.96) with a MAE=3.3 years for the training set and 4.4 years for a blind test set of 231 cases. The machine learning approach used 16 CpG sites, located in 16 different genomic regions, with the top 3 predictors of age belonged to the genes NHLRC1, SCGN and CSNK1D. The proposed model was further tested using independent cohorts of 53 monozygotic twins (MAE=7.1 years) and a cohort of 1011 disease state individuals (MAE=7.2 years). Furthermore, we highlighted the age markers' potential applicability in samples other than blood by predicting age with similar accuracy in 265 saliva samples (R 2 =0.96) with a MAE=3.2 years (training set) and 4.0 years (blind test). In an attempt to create a sensitive and accurate age prediction test, a next

  6. Efficient Generation of Social Network Data from Computer-Mediated Communication Logs

    National Research Council Canada - National Science Library

    Yee, Jason W

    2005-01-01

    ... organization's leadership can intervene and prevent the attack. Previous studies have shown that the person's behavior will generally change, and it is possible that social network analysis could be used to observe those changes...

  7. Key enablers for user-centric advertising across next-generation networks

    CERN Document Server

    Simoes, J

    2012-01-01

    This new book provides a fascinating overview of this topic for telecommunications engineers, computer scientists, network design engineers, marketing professionals and other researchers working in the web and telecommunication industries.

  8. A generational comparison of social networking site use: the influence of age and social identity.

    Science.gov (United States)

    Barker, Valerie

    2012-01-01

    An online survey (N=256) compared social networking site (SNS) use among younger (millennial: 18-29) and older (baby-boomer: 41-64) subscribers focusing on the influence of collective self-esteem and group identity on motives for SNS use. Younger participants reported higher positive collective self-esteem, social networking site use for peer communication, and social compensation. Regardless of age, participants reporting high collective self-esteem and group identity were more likely to use social networking sites for peer communication and social identity gratifications, while those reporting negative collective self-esteem were more likely to use social networking sites for social compensation. The theoretical implications of the strong relationship between social identity gratifications and social compensation are discussed.

  9. Generating Secure Group Key Using m-ARY Based Key Tree Structure in Sensor Networks

    OpenAIRE

    P.Naga Jyothi,; M.Supraja,; S.Suresh

    2010-01-01

    In the security scenario , security became a critical concern in various applications of sensor networks like pay-perview, distribution of digital media, military, distributed information gathering, environment monitoring, patient monitoring and tracking etc., require Secure Group Communication (SGC) in sensor networks. A scalable SGC model ensures that whenever there is a membership change, new group key is computed and distributed to the remaining members in the group with minimal computati...

  10. BELIEF dashboard - a web-based curation interface to support generation of BEL networks

    OpenAIRE

    Madan, Sumit; Hodapp, Sven; Fluck, Juliane

    2015-01-01

    The relevance of network-based approaches in systems biology to achieve a better understanding of biological mechanisms has increased enormously. The Biological Expression Language (BEL) is well designed to collate findings from scientific literature into biological network models. To facilitate encoding and biocuration of such findings in BEL, a free and user-friendly web-based curation interface called BELIEF Dashboard has been developed. The interface incorporates an information extraction...

  11. The Y.E.S. Network: An IYPE legacy for engaging future generations of early-career geoscientists

    Science.gov (United States)

    Gonzales, L. M.; Govoni, D.; Micucci, L.; Gaines, S. M.; Venus, J.; Meng, W.

    2009-12-01

    The Y.E.S. Network, an association of early-career geoscientists who represent professional societies, geoscience companies, and geoscience departments from across the world, was formed as a direct result of the International Year of Planet Earth (IYPE). Currently the Y.E.S. Network has representatives in thirty-five countries from six continents. The goal of the network is to engage early-career representatives from geological associations and institutions, policy-makers, and delegates from administrative bodies to establish a worldwide network of future leaders, policy-makers and geoscientists who will work collaboratively to address the scientific challenges future generations will face. To this end, the Y.E.S. Network, in collaboration with IYPE and with the patronage of UNESCO, organized the first international Y.E.S. Congress which was hosted by the China University of Geosciences in Beijing. The conference focused on scientific and career challenges faced by early-career geoscientists, with a particular emphasis on how the Y.E.S. Network can work collaborative and internationally towards solving these challenges and furthering the IYPE motto of “Earth Sciences for Society”. The conference focused on the ten major themes of the IYPE (e.g. health, climate, groundwater, ocean, soils, deep earth, megacities, hazards, resources, and life) at its poster and oral sessions. Roundtable symposia engaged senior and early-career geoscientists via presentations, panel discussions, and working group sessions where strategies related to scientific challenges (i.e. climate change in the polar regions, natural hazards, natural resource sustainability) and academic and career pathway challenges (i.e. academic-industry linkages, gender parity in the geosciences, geoscience education sustainability, and international licensure issues) were developed. These strategies were then tasked to the Y.E.S. Network for further development and implementation. Future Y.E.S. Network

  12. Energy Efficient, Cross-Layer Enabled, Dynamic Aggregation Networks for Next Generation Internet

    Science.gov (United States)

    Wang, Michael S.

    Today, the Internet traffic is growing at a near exponential rate, driven predominately by data center-based applications and Internet-of-Things services. This fast-paced growth in Internet traffic calls into question the ability of the existing optical network infrastructure to support this continued growth. The overall optical networking equipment efficiency has not been able to keep up with the traffic growth, creating a energy gap that makes energy and cost expenditures scale linearly with the traffic growth. The implication of this energy gap is that it is infeasible to continue using existing networking equipment to meet the growing bandwidth demand. A redesign of the optical networking platform is needed. The focus of this dissertation is on the design and implementation of energy efficient, cross-layer enabled, dynamic optical networking platforms, which is a promising approach to address the exponentially growing Internet bandwidth demand. Chapter 1 explains the motivation for this work by detailing the huge Internet traffic growth and the unsustainable energy growth of today's networking equipment. Chapter 2 describes the challenges and objectives of enabling agile, dynamic optical networking platforms and the vision of the Center for Integrated Access Networks (CIAN) to realize these objectives; the research objectives of this dissertation and the large body of related work in this field is also summarized. Chapter 3 details the design and implementation of dynamic networking platforms that support wavelength switching granularity. The main contribution of this work involves the experimental validation of deep cross-layer communication across the optical performance monitoring (OPM), data, and control planes. The first experiment shows QoS-aware video streaming over a metro-scale test-bed through optical power monitoring of the transmission wavelength and cross-layer feedback control of the power level. The second experiment extends the performance

  13. Multi-Layer Artificial Neural Networks Based MPPT-Pitch Angle Control of a Tidal Stream Generator

    Directory of Open Access Journals (Sweden)

    Khaoula Ghefiri

    2018-04-01

    Full Text Available Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG systems aim to provide clean and reliable electrical power. However, the power captured from tidal currents is highly disturbed due to the swell effect and the periodicity of the tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT generated from the ANN block. In case of strong tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  14. Dynamic imaging of coherent sources reveals different network connectivity underlying the generation and perpetuation of epileptic seizures.

    Directory of Open Access Journals (Sweden)

    Lydia Elshoff

    Full Text Available The concept of focal epilepsies includes a seizure origin in brain regions with hyper synchronous activity (epileptogenic zone and seizure onset zone and a complex epileptic network of different brain areas involved in the generation, propagation, and modulation of seizures. The purpose of this work was to study functional and effective connectivity between regions involved in networks of epileptic seizures. The beginning and middle part of focal seizures from ictal surface EEG data were analyzed using dynamic imaging of coherent sources (DICS, an inverse solution in the frequency domain which describes neuronal networks and coherences of oscillatory brain activities. The information flow (effective connectivity between coherent sources was investigated using the renormalized partial directed coherence (RPDC method. In 8/11 patients, the first and second source of epileptic activity as found by DICS were concordant with the operative resection site; these patients became seizure free after epilepsy surgery. In the remaining 3 patients, the results of DICS / RPDC calculations and the resection site were discordant; these patients had a poorer post-operative outcome. The first sources as found by DICS were located predominantly in cortical structures; subsequent sources included some subcortical structures: thalamus, Nucl. Subthalamicus and cerebellum. DICS seems to be a powerful tool to define the seizure onset zone and the epileptic networks involved. Seizure generation seems to be related to the propagation of epileptic activity from the primary source in the seizure onset zone, and maintenance of seizures is attributed to the perpetuation of epileptic activity between nodes in the epileptic network. Despite of these promising results, this proof of principle study needs further confirmation prior to the use of the described methods in the clinical praxis.

  15. Simulation of the Application Layer in NarrowBand Networks with Conditional Data Injection XML Scheme Based on Universal Data Generator

    Directory of Open Access Journals (Sweden)

    Ondrej Vondrous

    2017-01-01

    Full Text Available In this article, we would like to deal with challenges and analysis approaches in the area of narrow band communication networks. Especially those networks which use TCP/IP protocol family. We also present a new universal data generator for OMNeT++ simulation environment. We created this generator to satisfy the evaluation, stress testing and benchmarking demands of more and more complex industrial and the Internet of Things networks. We also present the methods for evaluation and comparison of results obtained from simulated and real TCP/IP based networks in this article.

  16. Generating clustered scale-free networks using Poisson based localization of edges

    Science.gov (United States)

    Türker, İlker

    2018-05-01

    We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

  17. Frame-Aggregated Link Adaptation Protocol for Next Generation Wireless Local Area Networks

    Directory of Open Access Journals (Sweden)

    Feng Kai-Ten

    2010-01-01

    Full Text Available The performance of wireless networks is affected by channel conditions. Link Adaptation techniques have been proposed to improve the degraded network performance by adjusting the design parameters, for example, the modulation and coding schemes, in order to adapt to the dynamically changing channel conditions. Furthermore, due to the advancement of the IEEE 802.11n standard, the network goodput can be enhanced with the exploitation of its frame aggregation schemes. However, none of the existing link adaption algorithms are designed to consider the feasible number of aggregated frames that should be utilized for channel-changing environments. In this paper, a frame-aggregated link adaptation (FALA protocol is proposed to dynamically adjust system parameters in order to improve the network goodput under varying channel conditions. For the purpose of maximizing network goodput, both the optimal frame payload size and the modulation and coding schemes are jointly obtained according to the signal-to-noise ratio under specific channel conditions. The performance evaluation is conducted and compared to the existing link adaption protocols via simulations. The simulation results show that the proposed FALA protocol can effectively increase the goodput performance compared to other baseline schemes, especially under dynamically-changing environments.

  18. Regressive Prediction Approach to Vertical Handover in Fourth Generation Wireless Networks

    Directory of Open Access Journals (Sweden)

    Abubakar M. Miyim

    2014-11-01

    Full Text Available The over increasing demand for deployment of wireless access networks has made wireless mobile devices to face so many challenges in choosing the best suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE-A environment. The technique enables the system to predict signal quality between the UE and Radio Base Stations (RBS/Access Points (APs in two different networks. Prediction is achieved by employing the Markov Decision Process Model (MDPM where the movement of the UE is dynamically estimated and averaged to keep track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. The performances of various handover approaches influenced by different metrics (mobility velocities were evaluated. The results presented demonstrate good accuracy the proposed method was able to achieve in predicting the next signal level by reducing the total handover latency.

  19. Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Su, Chi

    2015-01-01

    A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove...... that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods....

  20. Cognitive Radio and its Application for Next Generation Cellular and Wireless Networks

    CERN Document Server

    Muntean, Gabriel-Miro

    2012-01-01

    This book provides a broad introduction to Cognitive Radio, which attempts to mimic human cognition and reasoning applied to Software Defined Radio and reconfigurable radio over wireless networks.  It provides readers with significant technical and practical insights into different aspects of Cognitive Radio, starting from a basic background, the principle behind the technology, the inter-related technologies and application to cellular and vehicular networks, the technical challenges, implementation and future trends.  The discussion balances theoretical concepts and practical implementation. Wherever feasible, the different concepts explained are linked to application of the corresponding scheme in a particular wireless standard.     This book has two sections: the first section begins with an introduction to cognitive radio and discusses in detail various, inter-dependent technologies such as network coding, software-based radio, dirty RF, etc. and their relation to cognitive radio. The second section ...

  1. Water mass control system based on artificial neural networks for the steam generator in a pressurized water reactor

    Science.gov (United States)

    Dong, Wei

    The control of water mass inventory and water level in the steam generator is important for nuclear power plant. Conventional control system designs attempt to maintain downcomer water level within a relatively narrow operational band. However, the water level measured in the downcomer can temporarily react in a manner opposite to water mass inventory changes, which is known as shrink and swell effects. As a result, automatic or manual control of water level can be difficult under these conditions and can lead to reactor trips. This research introduces a new feedwater control strategy for nuclear steam generators. By estimating the water mass inventory with neural networks, the new method directly controls water mass inventory by conventional PI controller. Since shrink and swell are eliminated in water mass control, theoretical analysis and simulation results show the new control strategy improves the operation of nuclear steam generators significantly. In the water mass control system design, the safety function of the system is still based on the Steam Generator Water Level. Thus, the conventional water level trips will protect the plant when the new control strategy fails to maintain the water level within the safety range. The water mass estimator can be embedded in the Instrumentation and Control System of a Nuclear Power Plant to open loop observe the Steam Generator water mass inventory, improving the safety of nuclear power plant operation. Closed loop water mass control for a Steam Generator can be implemented after the observed water mass shows good agreement with theoretical calculations and plant operation experiences.

  2. ACADEMIC PARTNERSHIP AND GENERATION OF SCIENTIFIC KNOWLEDGE: THE CASE OF THE INTERNATIONAL NETWORK OF RESEARCHERS ON COMPETITIVENESS

    Directory of Open Access Journals (Sweden)

    José Guadalupe Vargas Hernández

    2011-03-01

    Full Text Available This paper has the objective to demonstrate the contributions achieved by the International Network of Researchers in Competitiveness (INRCO in academic collaboration and scientific knowledge generation. Part of the assumption sustaining that economic globalization processes, information and communication technologies revolution lead to the increasing environmental complexity and uncertainty of a knowledge society. One answer is the study and analysis of competitiveness considered as the strategy to achieve higher levels of economic growth and socio-cultural development in all micro, meso and macro levels. The method used is the analytic-deductive based on the evidence of related data with the activity and results in publications of the International Network of Researchers in Competitiveness. Consequently, it has been adapted certain speculative notions in a theoretical analysis exploring the social dynamics of the scientific activities. It is concluded that the management of the researchers’ dynamic network is capable to generate, apply and recycle the critical knowledge and the assets of academic and scientific talent through a dynamic combination of resources that have a position inside the formal e informal borders and between these borders of participant academics and institutions.

  3. Augmenting a TV Broadcast with Synchronised User Generated Video and Relevant Social Network Content

    NARCIS (Netherlands)

    Stokking, H.M.; Veenhuizen, A.T.; Kaptein, A.M.; Niamut, O.A.

    2014-01-01

    As TNO, we have developed an Augmented Live Broadcast use case, using components from the FP7 STEER project. In this use case, a television broadcast of a live event is augmented with user generated content. This user generated content consists of videos made by users at the event, and also of

  4. Synaptic signal streams generated by ex vivo neuronal networks contain non-random, complex patterns.

    Science.gov (United States)

    Lee, Sangmook; Zemianek, Jill M; Shultz, Abraham; Vo, Anh; Maron, Ben Y; Therrien, Mikaela; Courtright, Christina; Guaraldi, Mary; Yanco, Holly A; Shea, Thomas B

    2014-11-01

    Cultured embryonic neurons develop functional networks that transmit synaptic signals over multiple sequentially connected neurons as revealed by multi-electrode arrays (MEAs) embedded within the culture dish. Signal streams of ex vivo networks contain spikes and bursts of varying amplitude and duration. Despite the random interactions inherent in dissociated cultures, neurons are capable of establishing functional ex vivo networks that transmit signals among synaptically connected neurons, undergo developmental maturation, and respond to exogenous stimulation by alterations in signal patterns. These characteristics indicate that a considerable degree of organization is an inherent property of neurons. We demonstrate herein that (1) certain signal types occur more frequently than others, (2) the predominant signal types change during and following maturation, (3) signal predominance is dependent upon inhibitory activity, and (4) certain signals preferentially follow others in a non-reciprocal manner. These findings indicate that the elaboration of complex signal streams comprised of a non-random distribution of signal patterns is an emergent property of ex vivo neuronal networks. Copyright © 2014. Published by Elsevier Ltd.

  5. Optimal control of electricity generation from μ-CHPs in a network

    NARCIS (Netherlands)

    Larsen, Gunn; van Foreest, Nicolaas; Scherpen, Jacquelien M.A.

    2012-01-01

    We have designed a model that describes the balance of electricity production and consumption in a multi-producer multi-consumer Smart Grid. A perfect balance between production and consumption is taken to be the control goal. One strategy to achieve balance in the network is to match production and

  6. An Efficient Mesh Generation Method for Fractured Network System Based on Dynamic Grid Deformation

    Directory of Open Access Journals (Sweden)

    Shuli Sun

    2013-01-01

    Full Text Available Meshing quality of the discrete model influences the accuracy, convergence, and efficiency of the solution for fractured network system in geological problem. However, modeling and meshing of such a fractured network system are usually tedious and difficult due to geometric complexity of the computational domain induced by existence and extension of fractures. The traditional meshing method to deal with fractures usually involves boundary recovery operation based on topological transformation, which relies on many complicated techniques and skills. This paper presents an alternative and efficient approach for meshing fractured network system. The method firstly presets points on fractures and then performs Delaunay triangulation to obtain preliminary mesh by point-by-point centroid insertion algorithm. Then the fractures are exactly recovered by local correction with revised dynamic grid deformation approach. Smoothing algorithm is finally applied to improve the quality of mesh. The proposed approach is efficient, easy to implement, and applicable to the cases of initial existing fractures and extension of fractures. The method is successfully applied to modeling of two- and three-dimensional discrete fractured network (DFN system in geological problems to demonstrate its effectiveness and high efficiency.

  7. Energy generation for an ad hoc wireless sensor network-based monitoring system using animal head movement

    DEFF Research Database (Denmark)

    S. Nadimi, Esmaeil; Blanes-Vidal, Victoria; Jørgensen, Rasmus Nyholm

    2011-01-01

    The supply of energy to electronics is an imperative constraining factor to be considered during the design process of mobile ad hoc wireless sensor networks (MANETs). This influence is especially important when the MANET is deployed unattended or the wireless modules within the MANET are not eas......The supply of energy to electronics is an imperative constraining factor to be considered during the design process of mobile ad hoc wireless sensor networks (MANETs). This influence is especially important when the MANET is deployed unattended or the wireless modules within the MANET...... are not easily accessible. Therefore, exploring novel sources of energy generation rather than operating electronics only on limited power supplies such as batteries is a major challenge. Monitoring free-ranging animal behavior is an application in which the entities (animals) within the MANET are not readily...

  8. Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

    Directory of Open Access Journals (Sweden)

    Yun-Hao Li

    2015-12-01

    Full Text Available This paper presents a flexible transmission network expansion planning (TNEP approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

  9. Generation of Realistic Social Network Datasets for Testing of Analysis and Simulation Tools

    National Research Council Canada - National Science Library

    Tsvetovat, Maksim; Carley, Kathleen M

    2005-01-01

    .... Testing the software on machine-generated data, as opposed to empirical data only, allows the user to conduct repeatable tests that stress certain aspects of the software and help in debugging...

  10. Differential Protection of Generator by Using Neural Network, Fuzzy Neural and Fuzzy Neural Petri Net

    OpenAIRE

    Prof. Dr. Abduladhem A. Ali; Prof. Dr. Abduladhem A. Ali; Ahmed Thamer Radhi

    2012-01-01

    This paper deals with the applications of Artificial Intelligence techniques for detecting internalfaults in Power generators. Three techniques are used which are Neural Net (NN), FuzzyNeural Net (FNN) and Fuzzy Neural Petri Net (FNPN) to implement differential protection ofgenerator. MATLAB toolbox has been used for simulations and generation of faults data fortraining the programs for different faults cases and to implement the relays. Results ofdifferent fault cases are presented and these...

  11. Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity

    Science.gov (United States)

    Hiratani, Naoki; Fukai, Tomoki

    2016-01-01

    In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance. PMID:27303271

  12. Temperature simulations in tissue with a realistic computer generated vessel network

    International Nuclear Information System (INIS)

    Van Leeuwen, G.M.J.; Kotte, A.N.T.J.; Raaymakers, B.W.; Lagendijk, J.J.W.

    2000-01-01

    The practical use of a discrete vessel thermal model for hyperthermia treatment planning requires a number of choices with respect to the unknown part of the patient's vasculature. This work presents a study of the thermal effects of blood flow in a simple tissue geometry with a detailed artificial vessel network. The simulations presented here demonstrate that an incomplete discrete description of the detailed network results in a better prediction of the temperature distribution than is obtained using the conventional bio-heatsink equation. Therefore, efforts to obtain information on the positions of the large vessels in an individual hyperthermia patient will be rewarded with a more accurate prediction of the temperature distribution. (author)

  13. Global-local feature attention network with reranking strategy for image caption generation

    Science.gov (United States)

    Wu, Jie; Xie, Si-ya; Shi, Xin-bao; Chen, Yao-wen

    2017-11-01

    In this paper, a novel framework, named as global-local feature attention network with reranking strategy (GLAN-RS), is presented for image captioning task. Rather than only adopting unitary visual information in the classical models, GLAN-RS explores the attention mechanism to capture local convolutional salient image maps. Furthermore, we adopt reranking strategy to adjust the priority of the candidate captions and select the best one. The proposed model is verified using the Microsoft Common Objects in Context (MSCOCO) benchmark dataset across seven standard evaluation metrics. Experimental results show that GLAN-RS significantly outperforms the state-of-the-art approaches, such as multimodal recurrent neural network (MRNN) and Google NIC, which gets an improvement of 20% in terms of BLEU4 score and 13 points in terms of CIDER score.

  14. Hebbian Wiring Plasticity Generates Efficient Network Structures for Robust Inference with Synaptic Weight Plasticity.

    Science.gov (United States)

    Hiratani, Naoki; Fukai, Tomoki

    2016-01-01

    In the adult mammalian cortex, a small fraction of spines are created and eliminated every day, and the resultant synaptic connection structure is highly nonrandom, even in local circuits. However, it remains unknown whether a particular synaptic connection structure is functionally advantageous in local circuits, and why creation and elimination of synaptic connections is necessary in addition to rich synaptic weight plasticity. To answer these questions, we studied an inference task model through theoretical and numerical analyses. We demonstrate that a robustly beneficial network structure naturally emerges by combining Hebbian-type synaptic weight plasticity and wiring plasticity. Especially in a sparsely connected network, wiring plasticity achieves reliable computation by enabling efficient information transmission. Furthermore, the proposed rule reproduces experimental observed correlation between spine dynamics and task performance.

  15. Erroneous energy-generating cycles in published genome scale metabolic networks: Identification and removal.

    Science.gov (United States)

    Fritzemeier, Claus Jonathan; Hartleb, Daniel; Szappanos, Balázs; Papp, Balázs; Lercher, Martin J

    2017-04-01

    Energy metabolism is central to cellular biology. Thus, genome-scale models of heterotrophic unicellular species must account appropriately for the utilization of external nutrients to synthesize energy metabolites such as ATP. However, metabolic models designed for flux-balance analysis (FBA) may contain thermodynamically impossible energy-generating cycles: without nutrient consumption, these models are still capable of charging energy metabolites (such as ADP→ATP or NADP+→NADPH). Here, we show that energy-generating cycles occur in over 85% of metabolic models without extensive manual curation, such as those contained in the ModelSEED and MetaNetX databases; in contrast, such cycles are rare in the manually curated models of the BiGG database. Energy generating cycles may represent model errors, e.g., erroneous assumptions on reaction reversibilities. Alternatively, part of the cycle may be thermodynamically feasible in one environment, while the remainder is thermodynamically feasible in another environment; as standard FBA does not account for thermodynamics, combining these into an FBA model allows erroneous energy generation. The presence of energy-generating cycles typically inflates maximal biomass production rates by 25%, and may lead to biases in evolutionary simulations. We present efficient computational methods (i) to identify energy generating cycles, using FBA, and (ii) to identify minimal sets of model changes that eliminate them, using a variant of the GlobalFit algorithm.

  16. Modulatory role of the prefrontal generator within the auditory M50 network.

    Science.gov (United States)

    Josef Golubic, Sanja; Aine, Cheryl J; Stephen, Julia M; Adair, John C; Knoefel, Janice E; Supek, Selma

    2014-05-15

    The amplitude variability of the M50 component of neuromagnetic responses is commonly used to explore the brain's ability to modulate its response to incoming repetitive or novel auditory stimuli, a process conceptualized as a gating mechanism. The goal of this study was to identify the spatial and temporal characteristics of the cortical sources underlying the M50 network evoked by tones in a passive oddball paradigm. Twenty elderly subjects [10 patients diagnosed with mild cognitive impairment (MCI) or probable Alzheimer disease (AD) and 10 age-matched controls] were examined using magnetoencephalographic (MEG) recordings and the multi-dipole Calibrated Start Spatio-Temporal (CSST) source localization method. We identified three cortical regions underlying the M50 network: prefrontal cortex (PF) in addition to bilateral activation of the superior temporal gyrus (STG). The cortical dynamics of the PF source within the 30-100 ms post-stimulus interval was characterized and was found to be comprised of two subcomponents, Mb1c and Mb2c. The PF source was localized for 10/10 healthy subjects, whereas 9/10 MCI/AD patients were lacking the PF source for both tone conditions. The selective activation of the PF source in healthy controls along with the inactivation of the PF region for MCI/AD patients, enabled us to examine the dynamics of this network of activity when it was functional and dysfunctional, respectively. We found significantly enhanced activity of the STG sources in response to both tone conditions for all subjects who lacked a PF source. The reported results provide novel insights into the topology and neurodynamics of the M50 auditory network, which suggest an inhibitory role of the PF source that normally suppresses activity of the STG sources. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. THE NEED AND KEYS FOR A NEW GENERATION NETWORK ADJUSTMENT SOFTWARE

    Directory of Open Access Journals (Sweden)

    I. Colomina

    2012-07-01

    Full Text Available Orientation and calibration of photogrammetric and remote sensing instruments is a fundamental capacity of current mapping systems and a fundamental research topic. Neither digital remote sensing acquisition systems nor direct orientation gear, like INS and GNSS technologies, made block adjustment obsolete. On the contrary, the continuous flow of new primary data acquisition systems has challenged the capacity of the legacy block adjustment systems – in general network adjustment systems – in many aspects: extensibility, genericity, portability, large data sets capacity, metadata support and many others. In this article, we concentrate on the extensibility and genericity challenges that current and future network systems shall face. For this purpose we propose a number of software design strategies with emphasis on rigorous abstract modeling that help in achieving simplicity, genericity and extensibility together with the protection of intellectual proper rights in a flexible manner. We illustrate our suggestions with the general design approach of GENA, the generic extensible network adjustment system of GeoNumerics.

  18. 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.

  19. CaloGAN: Simulating 3D high energy particle showers in multilayer electromagnetic calorimeters with generative adversarial networks

    Science.gov (United States)

    Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin

    2018-01-01

    The precise modeling of subatomic particle interactions and propagation through matter is paramount for the advancement of nuclear and particle physics searches and precision measurements. The most computationally expensive step in the simulation pipeline of a typical experiment at the Large Hadron Collider (LHC) is the detailed modeling of the full complexity of physics processes that govern the motion and evolution of particle showers inside calorimeters. We introduce CaloGAN, a new fast simulation technique based on generative adversarial networks (GANs). We apply these neural networks to the modeling of electromagnetic showers in a longitudinally segmented calorimeter and achieve speedup factors comparable to or better than existing full simulation techniques on CPU (100 ×-1000 × ) and even faster on GPU (up to ˜105× ). There are still challenges for achieving precision across the entire phase space, but our solution can reproduce a variety of geometric shower shape properties of photons, positrons, and charged pions. This represents a significant stepping stone toward a full neural network-based detector simulation that could save significant computing time and enable many analyses now and in the future.

  20. Performance assessment of electric power generations using an adaptive neural network algorithm and fuzzy DEA

    Energy Technology Data Exchange (ETDEWEB)

    Javaheri, Zahra

    2010-09-15

    Modeling, evaluating and analyzing performance of Iranian thermal power plants is the main goal of this study which is based on multi variant methods analysis. These methods include fuzzy DEA and adaptive neural network algorithm. At first, we determine indicators, then data is collected, next we obtained values of ranking and efficiency by Fuzzy DEA, Case study is thermal power plants In view of the fact that investment to establish on power plant is very high, and maintenance of power plant causes an expensive expenditure, moreover using fossil fuel effected environment hence optimum produce of current power plants is important.

  1. Agent-based approach for generation of a money-centered star network

    Science.gov (United States)

    Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

    2008-09-01

    The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

  2. Content Generation and Social Network Interaction within Academic Library Facebook Pages

    Science.gov (United States)

    Witte, Ginna Gauntner

    2014-01-01

    The use of Facebook to share resources and engage patrons continues to gain acceptance within academic libraries. While many studies have analyzed the types of content academic libraries share on Facebook, there has not yet been a full examination of how this content is generated. This article examined the posting methods, the user responses, and…

  3. Distributed Generation Management in Distribution Networks; Gestion de la production decentralisee dans les reseaux de distribution

    Energy Technology Data Exchange (ETDEWEB)

    Caire, R.

    2004-04-15

    Deregulations of the energy market, followed by many privatizations, and vertical disintegrations brought a complete reorganization of the electric sector. The opening of the energy markets as well as the technological developments of the means of production of small and average power strongly encourage this evolution. A systematic methodology to study the transmission of impacts between the Low and Medium Voltage is initially proposed, after a quick state of the art of the various possible impacts. The voltage deviation is then identified as the most critical impact. This criticality is supported by quantitative studies on French typical networks, and is confirmed by the related literature. In order to solve this impact, a research of the means of action within tension of the distribution network and their modeling is carried out. As the manipulated variables of the means of adjustment available are discrete or continuous, specific tools are then developed to coordinate them. This coordination is pressed on optimization algorithms developed by holding account of inherent specificity with the manipulated variables. A methodology for the choice or optimal location of the adjustment means associated with a management of the voltage deviation is presented. Lastly, 'decentralized' strategies of coordination for the means of adjustment and a proposal for an experimental validation are presented, thanks to a real time simulator, making it possible to test the strategies of coordination and the necessary means of communication. (author)

  4. The Middle Eastern Biodiversity Network: Generating and sharing knowledge for ecosystem management and conservation

    Directory of Open Access Journals (Sweden)

    Friedhelm Krupp

    2009-12-01

    Full Text Available Despite prevailing arid conditions, the diversity of terrestrial and freshwater biota in the Middle East is amazingly high and marine biodiversity is the second highest on Earth. Throughout the region, threats to the environment are moderate to severe. Despite the outstanding economic and ecological importance of biological diversity, the capacity in biodiversity-related research and education is inadequate in most parts of the Middle East. The ";;Middle Eastern Biodiversity Network";; (MEBN, founded in 2006 by six universities and research institutes in Iran, Jordan, Germany, Lebanon and Yemen was designed to fill this gap. An integrated approach is taken to upgrade biodiversity research and education to improve regional ecosystem conservation and management capacities. A wide range of activities are carried out in the framework of the Network, including capacity building in biological collection management and professional natural history curatorship, developing university curricula in biodiversity, conducting scientific research, organising workshops and conferences on Middle Eastern biodiversity, and translating the results of biodiversity research into conservation and sustainable development.

  5. Hydraulic Parameter Generation Technique Using a Discrete Fracture Network with Bedrock Heterogeneity in Korea

    Directory of Open Access Journals (Sweden)

    Jae-Yeol Cheong

    2017-12-01

    Full Text Available In instances of damage to engineered barriers containing nuclear waste material, surrounding bedrock is a natural barrier that retards radionuclide movement by way of adsorption and delay due to groundwater flow through highly tortuous fractured rock pathways. At the Gyeongju nuclear waste disposal site, groundwater mainly flows through granitic and sedimentary rock fractures. Therefore, to understand the nuclide migration path, it is necessary to understand discrete fracture networks based on heterogeneous fracture orientations, densities, and size characteristics. In this study, detailed heterogeneous fracture distribution, including the density and orientation of the fractures, was considered for a region that has undergone long periods of change from various geological activities at and around the Gyeongju site. A site-scale discrete fracture network (DFN model was constructed taking into account: (i regional fracture heterogeneity constrained by a multiple linear regression analysis of fracture intensity on faults and electrical resistivity; and (ii the connectivity of conductive fractures having fracture hydraulic parameters, using transient flow simulation. Geometric and hydraulic heterogeneity of the DFN was upscaled into equivalent porous media for flow and transport simulation for a large-scale model.

  6. c-Myc activates multiple metabolic networks to generate substrates for cell-cycle entry.

    Energy Technology Data Exchange (ETDEWEB)

    Morrish, Fionnuala M.; Isern, Nancy; Sadilek, Martin; Jeffrey, Mark; Hockenbery, David M.

    2009-05-18

    Cell proliferation requires the coordinated activity of cytosolic and mitochondrial metabolic pathways to provide ATP and building blocks for DNA, RNA, and protein synthesis. Many metabolic pathway genes are targets of the c-myc oncogene and cell cycle regulator. However, the contribution of c-Myc to the activation of cytosolic and mitochondrial metabolic networks during cell cycle entry is unknown. Here, we report the metabolic fates of [U-13C] glucose in serum-stimulated myc-/- and myc+/+ fibroblasts by 13C isotopomer NMR analysis. We demonstrate that endogenous c-myc increased 13C-labeling of ribose sugars, purines, and amino acids, indicating partitioning of glucose carbons into C1/folate and pentose phosphate pathways, and increased tricarboxylic acid cycle turnover at the expense of anaplerotic flux. Myc expression also increased global O-linked GlcNAc protein modification, and inhibition of hexosamine biosynthesis selectively reduced growth of Myc-expressing cells, suggesting its importance in Myc-induced proliferation. These data reveal a central organizing role for the Myc oncogene in the metabolism of cycling cells. The pervasive deregulation of this oncogene in human cancers may be explained by its role in directing metabolic networks required for cell proliferation.

  7. Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

    Science.gov (United States)

    Radziszewski, Kacper

    2017-10-01

    The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

  8. Fast Reliability Assessing Method for Distribution Network with Distributed Renewable Energy Generation

    Science.gov (United States)

    Chen, Fan; Huang, Shaoxiong; Ding, Jinjin; Ding, Jinjin; Gao, Bo; Xie, Yuguang; Wang, Xiaoming

    2018-01-01

    This paper proposes a fast reliability assessing method for distribution grid with distributed renewable energy generation. First, the Weibull distribution and the Beta distribution are used to describe the probability distribution characteristics of wind speed and solar irradiance respectively, and the models of wind farm, solar park and local load are built for reliability assessment. Then based on power system production cost simulation probability discretization and linearization power flow, a optimal power flow objected with minimum cost of conventional power generation is to be resolved. Thus a reliability assessment for distribution grid is implemented fast and accurately. The Loss Of Load Probability (LOLP) and Expected Energy Not Supplied (EENS) are selected as the reliability index, a simulation for IEEE RBTS BUS6 system in MATLAB indicates that the fast reliability assessing method calculates the reliability index much faster with the accuracy ensured when compared with Monte Carlo method.

  9. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    International Nuclear Information System (INIS)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-01-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing

  10. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule.

    Science.gov (United States)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin

    2015-11-01

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  11. Effects of bursting dynamic features on the generation of multi-clustered structure of neural network with symmetric spike-timing-dependent plasticity learning rule

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Hui; Song, Yongduan; Xue, Fangzheng; Li, Xiumin, E-mail: xmli@cqu.edu.cn [Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 400044 (China); College of Automation, Chongqing University, Chongqing 400044 (China)

    2015-11-15

    In this paper, the generation of multi-clustered structure of self-organized neural network with different neuronal firing patterns, i.e., bursting or spiking, has been investigated. The initially all-to-all-connected spiking neural network or bursting neural network can be self-organized into clustered structure through the symmetric spike-timing-dependent plasticity learning for both bursting and spiking neurons. However, the time consumption of this clustering procedure of the burst-based self-organized neural network (BSON) is much shorter than the spike-based self-organized neural network (SSON). Our results show that the BSON network has more obvious small-world properties, i.e., higher clustering coefficient and smaller shortest path length than the SSON network. Also, the results of larger structure entropy and activity entropy of the BSON network demonstrate that this network has higher topological complexity and dynamical diversity, which benefits for enhancing information transmission of neural circuits. Hence, we conclude that the burst firing can significantly enhance the efficiency of clustering procedure and the emergent clustered structure renders the whole network more synchronous and therefore more sensitive to weak input. This result is further confirmed from its improved performance on stochastic resonance. Therefore, we believe that the multi-clustered neural network which self-organized from the bursting dynamics has high efficiency in information processing.

  12. Fractal Branching in Vascular Trees and Networks by VESsel GENeration Analysis (VESGEN)

    Science.gov (United States)

    Parsons-Wingerter, Patricia A.

    2016-01-01

    Vascular patterning offers an informative multi-scale, fractal readout of regulatory signaling by complex molecular pathways. Understanding such molecular crosstalk is important for physiological, pathological and therapeutic research in Space Biology and Astronaut countermeasures. When mapped out and quantified by NASA's innovative VESsel GENeration Analysis (VESGEN) software, remodeling vascular patterns become useful biomarkers that advance out understanding of the response of biology and human health to challenges such as microgravity and radiation in space environments.

  13. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network

    International Nuclear Information System (INIS)

    Garcia, Gabe V.

    2005-01-01

    A major cause of failure in nuclear steam generators is degradation of their tubes. Although seven primary defect categories exist, one of the principal causes of tube failure is intergranular attack/stress corrosion cracking (IGA/SCC). This type of defect usually begins on the secondary side surface of the tubes and propagates both inwards and laterally. In many cases this defect is found at or near the tube support plates

  14. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network

    Energy Technology Data Exchange (ETDEWEB)

    Gabe V. Garcia

    2005-01-03

    A major cause of failure in nuclear steam generators is degradation of their tubes. Although seven primary defect categories exist, one of the principal causes of tube failure is intergranular attack/stress corrosion cracking (IGA/SCC). This type of defect usually begins on the secondary side surface of the tubes and propagates both inwards and laterally. In many cases this defect is found at or near the tube support plates.

  15. A New Regulatory Policy for FTTx-Based Next-Generation Access Networks

    Science.gov (United States)

    Makarovič, Boštjan

    2013-07-01

    This article critically assesses the latest European Commission policies in relation to next-generation access investment that put focus on regulated prices and relaxing of wholesale access obligations. Pointing at the vital socio-legal and economic arguments, it further challenges the assumptions of the current EU regulatory framework and calls for a more contractual utility-based model of regulation instead of the current system that overly relies on market-driven infrastructure-based competition.

  16. Evolving Artificial Neural Networks with Generative Encodings Inspired by Developmental Biology

    Science.gov (United States)

    2010-01-01

    role in our lives in generations to come. Legged consumer robots already exist, such as the biped ASIMO and the quadruped AIBO. Both the military and...gaits for legged robots . . . . . . . . . . . . . 28 4.2 Previous work evolving gaits for legged robots . . . . . . . . . . . . . . . . 28 4.3 Applying...The Simulated Robot in the Quadruped Controller Problem. . . . . . . . . 31 ix 4.2 ANN Configuration for HyperNEAT and FT-NEAT Treatments. The first

  17. Choice of insulation standard for pipe networks in 4th generation district heating systems

    DEFF Research Database (Denmark)

    Lund, Rasmus Søgaard; Mohammadi, Soma

    2016-01-01

    and smart gas grids. Improving DH pipes by improving the insulation standard results in decreasing the heat and temperature losses from the pipe networks. When reducing heat losses from DH pipes, there is a trade-off between the increasing cost of pipe insulation and the associated savings in the heat...... by implementing different pipe insulation standards. In the second step, the specific grid losses found in the first step are analysed in an integrated energy systems model where all main energy sectors and their interrelations are included. The outcome of the study can provide decision support when planning...... investments in DH systems today and in the future. The results from the case of Denmark shows that pipes with higher insulation standard (series 3) is generally preferable, but the highest insulation standard available today (series 4) might be preferable in the future if fuel prices or increase or investment...

  18. Artificial neural Network-Based modeling and monitoring of photovoltaic generator

    Directory of Open Access Journals (Sweden)

    H. MEKKI

    2015-03-01

    Full Text Available In this paper, an artificial neural network based-model (ANNBM is introduced for partial shading detection losses in photovoltaic (PV panel. A Multilayer Perceptron (MLP is used to estimate the electrical outputs (current and voltage of the photovoltaic module using the external meteorological data: solar irradiation G (W/m2 and the module temperature T (°C. Firstly, a database of the BP150SX photovoltaic module operating without any defect has been used to train the considered MLP. Subsequently, in the first case of this study, the developed model is used to estimate the output current and voltage of the PV module considering the partial shading effect. Results confirm the good ability of the ANNBM to detect the partial shading effect in the photovoltaic module with logical accuracy. The proposed strategy could also be used for the online monitoring and supervision of PV modules.

  19. Application of Neural Network to 24-hours-Ahead Generating Power Forecasting for PV System

    Science.gov (United States)

    Yona, Atsushi; Senjyu, Tomonobu; Funabshi, Toshihisa; Sekine, Hideomi

    In recent years, there have been focus on environmental pollution issue resulting from consumption of fuel, e.g., coal and oil. Thus, introduction of an alternative energy source such as solar energy is expected. However, insolation is not constant and output of photovoltaic (PV) system is influenced by meteorological conditions. In order to predict the power output for PV system as accurate as possible, it requires method of insolation estimation. In this paper, the authors take the insolation of each month into consideration, and confirm the validity of using neural network to predict insolation by computer simulations. The proposed method in this paper does not require complicated calculation and mathematical model with only meteorological data.

  20. A network model for generating differential symmetry axes of shapes via receptive fields.

    Science.gov (United States)

    Kurbat, M A

    1994-01-01

    Some symmetries (e.g. bilateral, rotational, translational) only describe quite specialized shapes, but differential symmetry axes (e.g. Blum, J. Theoret. Biol. 38, 205-287, 1973; Brady and Asada, Int. J. Robotics Res. 3, 36-61, 1984) describe more general shapes. Such axes are of interest in part because they form the 'backbone' of generalized cylinder and other shape representations used in shape recognition (e.g. Marr, Vision, W. H. Freeman and Co., NY, 1982; Biederman, Psychol. Rev. 94, 115-147, 1987). However, despite the popularity of these representations as psychological models, algorithms from machine vision for computing them have strong limitations as psychological models. This paper presents two versions of a network model, one of which is more plausible as a psychological model because it derives symmetry axes from the activations of idealized visual receptive fields.

  1. Wind Turbine Driving a PM Synchronous Generator Using Novel Recurrent Chebyshev Neural Network Control with the Ideal Learning Rate

    Directory of Open Access Journals (Sweden)

    Chih-Hong Lin

    2016-06-01

    Full Text Available A permanent magnet (PM synchronous generator system driven by wind turbine (WT, connected with smart grid via AC-DC converter and DC-AC converter, are controlled by the novel recurrent Chebyshev neural network (NN and amended particle swarm optimization (PSO to regulate output power and output voltage in two power converters in this study. Because a PM synchronous generator system driven by WT is an unknown non-linear and time-varying dynamic system, the on-line training novel recurrent Chebyshev NN control system is developed to regulate DC voltage of the AC-DC converter and AC voltage of the DC-AC converter connected with smart grid. Furthermore, the variable learning rate of the novel recurrent Chebyshev NN is regulated according to discrete-type Lyapunov function for improving the control performance and enhancing convergent speed. Finally, some experimental results are shown to verify the effectiveness of the proposed control method for a WT driving a PM synchronous generator system in smart grid.

  2. Comparison of two total energy systems for a diesel power generation plant. [deep space network

    Science.gov (United States)

    Chai, V. W.

    1979-01-01

    The capabilities and limitations, as well as the associated costs for two total energy systems for a diesel power generation plant are compared. Both systems utilize waste heat from engine cooling water and waste heat from exhaust gases. Pressurized water heat recovery system is simple in nature and requires no engine modifications, but operates at lower temperature ranges. On the other hand, a two-phase ebullient system operates the engine at constant temperature, provides higher temperature water or steam to the load, but is more expensive.

  3. Geographically determined Interactions of Distributed Generation, Consumption and the Transmission Network in the Case of Denmark

    DEFF Research Database (Denmark)

    Möller, Bernd

    2002-01-01

    . At some times electricity has to be exported to neighbouring countries at market prices pro-bably lower than the costs of generation. To match production and consumption in the future, and at the same time maintain a good economy, alternative regulation instruments have to be found. These could consist...... with the geographical distribution of electricity and district heat con-sumption. This paper presents a methodology for modelling the geographically determined interac-tions between local producers and consumption. The country has been divided into about 100 zones, for which hourly balances have been calculated...... electricity markets....

  4. Systems Medicine in Oncology: Signaling Network Modeling and New-Generation Decision-Support Systems.

    Science.gov (United States)

    Parodi, Silvio; Riccardi, Giuseppe; Castagnino, Nicoletta; Tortolina, Lorenzo; Maffei, Massimo; Zoppoli, Gabriele; Nencioni, Alessio; Ballestrero, Alberto; Patrone, Franco

    2016-01-01

    Two different perspectives are the main focus of this book chapter: (1) A perspective that looks to the future, with the goal of devising rational associations of targeted inhibitors against distinct altered signaling-network pathways. This goal implies a sufficiently in-depth molecular diagnosis of the personal cancer of a given patient. A sufficiently robust and extended dynamic modeling will suggest rational combinations of the abovementioned oncoprotein inhibitors. The work toward new selective drugs, in the field of medicinal chemistry, is very intensive. Rational associations of selective drug inhibitors will become progressively a more realistic goal within the next 3-5 years. Toward the possibility of an implementation in standard oncologic structures of technologically sufficiently advanced countries, new (legal) rules probably will have to be established through a consensus process, at the level of both diagnostic and therapeutic behaviors.(2) The cancer patient of today is not the patient of 5-10 years from now. How to support the choice of the most convenient (and already clinically allowed) treatment for an individual cancer patient, as of today? We will consider the present level of artificial intelligence (AI) sophistication and the continuous feeding, updating, and integration of cancer-related new data, in AI systems. We will also report briefly about one of the most important projects in this field: IBM Watson US Cancer Centers. Allowing for a temporal shift, in the long term the two perspectives should move in the same direction, with a necessary time lag between them.

  5. Generating compensation designs for tangential breast irradiation with artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Gulliford, S. [Joint Department of Physics, Institute of Cancer Research and Royal Marsden Hospital NHS Trust, Surrey (United Kingdom)]. E-mail: sarahg@icr.ac.uk; Corne, D. [Department of Computer Science, School of Computer Science, Cybernetics and Electronic Engineering, University of Reading, Berkshire (United Kingdom); Rowbottom, C.; Webb, S. [Joint Department of Physics, Institute of Cancer Research and Royal Marsden Hospital NHS Trust, Surrey (United Kingdom)

    2002-01-21

    In this paper we discuss a study comparing an algorithm implemented clinically to design intensity-modulated fields with two artificial neural networks (ANNs) trained to design the same fields. The purpose of the algorithm is to produce compensation for tangential breast radiotherapy in order to improve dose homogeneity. This was achieved by creating intensity-modulated fields to supplement standard wedged fields. Portal image data were used to create thickness maps of the medial and lateral fields, which in turn were used to design the wedged and intensity-modulated fields. The ANNs were developed to design the intensity-modulated fields from the portal image data and corresponding fluence map alone. One used localized groups of portal image pixels related to the fluence map (method 2), and the other used a one-to-one mapping between spatially corresponding pixels (method 3). A dosimetric comparison of the methods was performed by calculating the overall dose distribution. The volume of tissue outside the dose range 95-105% was used to assess dose homogeneity. The average volume outside 95-105%, averaged over 80 cases, was shown to be 2.3% for the algorithm, whilst average values of 9.9% and 13.5% were obtained for methods 2 and 3, respectively. The results of this study demonstrate the ability of an ANN to learn the general shape of compensation required and explore the use of image-based ANNs in the design of intensity-modulated fields. (author)

  6. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  7. Radio Telescope Focal Container for the Russian VLBI Network of New Generation

    Science.gov (United States)

    Ipatov, Alexander; Mardyshkin, Vyacheslav; Cherepanov, Andrey; Chernov, Vitaly; Diky, Dmitry; Khvostov, Evgeny; Yevstigneyev, Alexander

    2010-01-01

    This article considers the development of the structure of receivers for Russian radio telescopes. The development of these radio telescopes is undertaken within the project for creating a Russian small-antenna-based radio interferometer of new generation. It is shown that for small antennas (10. 12 meter) the principal unit, which provides the best SNR, is the so-called focal container placed at primary focus. It includes the primary feed, HEMT LNA, and cryogenic cooling system down to 20. K. A new multi-band feed based on traveling wave resonators is used. It has small dimensions, low weight, and allows working with circular polarizations. Thus it can be placed into focal container and cooled with the LNA. A sketch of the focal container, with traveling-wave-resonator feed, and calculations of the expected parameters of the multi-band receiver are presented.

  8. Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

    Science.gov (United States)

    Nayar, Priya; Singh, Bhim; Mishra, Sukumar

    2017-08-01

    An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

  9. A system-of-systems framework for the reliability analysis of distributed generation systems accounting for the impact of degraded communication networks

    International Nuclear Information System (INIS)

    Mo, Hua-Dong; Li, Yan-Fu; Zio, Enrico

    2016-01-01

    Highlights: • A system-of-systems framework is proposed for reliability analysis of DG system. • The impact of degraded communication networks is included and quantified. • Various uncertainties and contingencies in the DG system are considered. • A Monte Carlo simulation-optimal power flow computational framework is developed. • The results of the application study show the power of the proposed framework. - Abstract: Distributed generation (DG) systems install communication networks for managing real-time energy imbalance. Different from previous research, which typically assumes perfect communication networks, this work aims to quantitatively account for the impact of degraded communication networks on DG systems performance. The degraded behavior of communication networks is modeled by stochastic continuous time transmission delays and packet dropouts. On the DG systems side, we consider the inherent uncertainties of renewable energy sources, loads and energy prices. We develop a Monte Carlo simulation-optimal power flow (MCS-OPF) computational framework that is capable of generating consecutive time-dependent operating scenarios of the integrated system. Quantitative analysis is carried out to measure the impact of communication networks degradation onto the DG systems. For illustration, the framework is applied to a modified IEEE 13 nodes test feeder. The results demonstrate that the degraded communication networks can significantly deteriorate the performance of the integrated system. A grey differential model-based prediction method for reconstructing missing data is effective in mitigating the influence of the degraded communication networks.

  10. Intermittent renewable generation and network congestion: an empirical analysis of Italian Power Market

    International Nuclear Information System (INIS)

    Ardian, Faddy; Concettini, Silvia; Creti, Anna

    2015-01-01

    The literature demonstrates the likely reduction of wholesale electricity prices due to a larger penetration of renewable energy sources (RES). When markets are organized as two or more inter-connected sub-markets within a larger power market the final impact of increasing RES production may be less straightforward given the presence of network constraints. We tests this phenomenon by analyzing the impact of RES production on the probability of congestion and on the size of congestion cost in Italy. Using a database with hourly observations for a five year period we estimate two econometric models on five zonal pairings: a multinomial logit model for the occurrence and direction of congestion and a three stage least square model for the size of congestion costs. The analysis suggests that the effect of a larger local wind and solar supply is to decrease the probability of suffering congestion in entry and to increase the probability of causing a congestion in exit compared to no congestion case. Increasing hydroelectric production has a similar effect. These results hold for both importing and exporting regions, but importing regions are less likely to cause congestion in exit, therefore the installation of new RES capacity in these zones may have a positive effects in terms of flow balance between regions. Concerning the cost level, a larger local RES supply seems to push the congestion cost towards negative values as it decreases the marginal cost for balancing the system. This is true for all zones in the case of explicit congestion cost, but it is only verified in importing regions in the case of implicit congestion cost. This result suggests that the increase of RES production should be promoted in importing zones, but the overall growth should be controlled in order to avoid congestion in the opposite direction. (authors)

  11. An Efficient Reactive Power Control Method for Power Network Systems with Solar Photovoltaic Generators Using Sparse Optimization

    Directory of Open Access Journals (Sweden)

    Yu Li

    2017-05-01

    Full Text Available With the incremental introduction of solar photovoltaic (PV generators into existing power systems, and their fast-growing share in the gross electricity generation, system voltage stability has become a critical issue. One of the major concerns is voltage fluctuation, due to large and random penetration of solar PV generators. To suppress severe system voltage deviation, reactive power control of the photovoltaic system inverter has been widely proposed in recent works; however, excessive use of reactive power control would increase both initial and operating costs. In this paper, a method for efficient allocation and control of reactive power injection using the sparse optimization technique is proposed. Based on a constrained linearized model describing the influence of reactive power injection on voltage magnitude change, the objective of this study is formulated as an optimization problem, which aims to find the best reactive power injection that minimizes the whole system voltage variation. Two types of formulations are compared: the first one is the conventional least-square optimization, while the second one is adopted from a sparse optimization technique, called the constrained least absolute shrinkage and selection operator (LASSO method. The constrained LASSO method adds ℓ 1 -norm penalty to the total reactive power injection, which contributes to the suppression of the number of control nodes with non-zero reactive power injection. The authors analyzed the effectiveness of the constrained LASSO method using the IEEE 39-bus and 57-bus power network as benchmark examples, under various PV power generation and allocation patterns. The simulation results show that the constrained LASSO method automatically selects the minimum number of inverters required for voltage regulation at the current operating point.

  12. Automated generation of patient-tailored electronic care pathways by translating computer-interpretable guidelines into hierarchical task networks.

    Science.gov (United States)

    González-Ferrer, Arturo; ten Teije, Annette; Fdez-Olivares, Juan; Milian, Krystyna

    2013-02-01

    This paper describes a methodology which enables computer-aided support for the planning, visualization and execution of personalized patient treatments in a specific healthcare process, taking into account complex temporal constraints and the allocation of institutional resources. To this end, a translation from a time-annotated computer-interpretable guideline (CIG) model of a clinical protocol into a temporal hierarchical task network (HTN) planning domain is presented. The proposed method uses a knowledge-driven reasoning process to translate knowledge previously described in a CIG into a corresponding HTN Planning and Scheduling domain, taking advantage of HTNs known ability to (i) dynamically cope with temporal and resource constraints, and (ii) automatically generate customized plans. The proposed method, focusing on the representation of temporal knowledge and based on the identification of workflow and temporal patterns in a CIG, makes it possible to automatically generate time-annotated and resource-based care pathways tailored to the needs of any possible patient profile. The proposed translation is illustrated through a case study based on a 70 pages long clinical protocol to manage Hodgkin's disease, developed by the Spanish Society of Pediatric Oncology. We show that an HTN planning domain can be generated from the corresponding specification of the protocol in the Asbru language, providing a running example of this translation. Furthermore, the correctness of the translation is checked and also the management of ten different types of temporal patterns represented in the protocol. By interpreting the automatically generated domain with a state-of-art HTN planner, a time-annotated care pathway is automatically obtained, customized for the patient's and institutional needs. The generated care pathway can then be used by clinicians to plan and manage the patients long-term care. The described methodology makes it possible to automatically generate

  13. Natural gas power generation: interruptible gas distribution network regulation; Geracao termoeletrica a gas natural: regulacao do segmento interruptivel de distribuicao de gas canalizado

    Energy Technology Data Exchange (ETDEWEB)

    Paula, Claudio Paiva de; Kann, Zevi [Agencia Reguladora de Saneamento e Energia do Estado de Sao Paulo (ARSESP), SP (Brazil)

    2008-07-01

    The paper relates studies regarding the natural gas distribution network interruptible branch. This new service can be appropriate for thermal power generation on flexible dispatch mode, as 'take or pay' contracts surplus jobs. The paper indicates no regulatory restraints in an interruptible network implantation. The final conclusion is that interruptible contracts can be an improvement on the distribution business and certainly can accommodate a suitable demand and supply volumes in the long-term gas market balance. (author)

  14. Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

    Energy Technology Data Exchange (ETDEWEB)

    Perumalla, Kalyan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alam, Maksudul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-10-01

    A novel parallel algorithm is presented for generating random scale-free networks using the preferential-attachment model. The algorithm, named cuPPA, is custom-designed for single instruction multiple data (SIMD) style of parallel processing supported by modern processors such as graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidia GeForce 1080 GPU, cuPPA generates a scale free network of a billion edges in less than 2 seconds.

  15. Genetic alterations in mesiodens as revealed by targeted next-generation sequencing and gene co-occurrence network analysis.

    Science.gov (United States)

    Kim, Y Y; Hwang, J; Kim, H-S; Kwon, H J; Kim, S; Lee, J H; Lee, J H

    2017-10-01

    Mesiodens is the most common type of supernumerary tooth which includes a population prevalence of 0.15%-1.9%. Alongside evidence that the condition is heritable, mutations in single genes have been reported in few human supernumerary tooth cases. Gene sequencing methods in tradition way are time-consuming and labor-intensive, whereas next-generation sequencing and bioinformatics are cost-effective for large samples and target sizes. We describe the application of a targeted next-generation sequencing (NGS) and bioinformatics approach to samples from 17 mesiodens patients. Subjects were diagnosed on the basis of panoramic radiograph. A total of 101 candidate genes which were captured custom genes were sequenced on the Illumina HiSeq 2500. Multistep bioinformatics processing was performed including variant identification, base calling, and in silico analysis of putative disease-causing variants. Targeted capture identified 88 non-synonymous, rare, exonic variants involving 42 of the 101 candidate genes. Moreover, we investigated gene co-occurrence relationships between the genomic alterations and identified 88 significant relationships among 18 most recurrent driver alterations. Our search for co-occurring genetic alterations revealed that such alterations interact cooperatively to drive mesiodens. We discovered a gene co-occurrence network in mesiodens patients with functionally enriched gene groups in the sonic hedgehog (SHH), bone morphogenetic proteins (BMP), and wingless integrated (WNT) signaling pathways. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. All rights reserved.

  16. The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

    International Nuclear Information System (INIS)

    Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina

    2009-01-01

    Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.

  17. Two distinct olfactory bulb sublaminar networks involved in gamma and beta oscillation generation: a CSD study in the anesthetized rat.

    Directory of Open Access Journals (Sweden)

    Nicolas eFourcaud-Trocmé

    2014-07-01

    Full Text Available A prominent feature of olfactory bulb (OB dynamics is the expression of characteristic local field potential (LFP rhythms, including a slow respiration-related rhythm and two fast alternating oscillatory rhythms, beta (15-30 Hz and gamma (40-90 Hz. All of these rhythms are implicated in olfactory coding. Fast oscillatory rhythms are known to involve the mitral-granule cell loops. Although the underlying mechanisms of gamma oscillation have been studied, the origin of beta oscillation remains poorly understood. Whether these two different rhythms share the same underlying mechanism is unknown. This study uses a quantitative and detailed current-source density analysis combined with multi-unit activity recordings to shed light on this question in freely breathing anesthetized rats. In particular, we show that gamma oscillation generation involves mainly upper half of the external plexiform layer (EPL and superficial areas of granule cell layer. In contrast, the generation of beta oscillation involves the lower part of the EPL and deep granule cells. This differential involvement of sublaminar networks is neither dependent on odor quality nor on the precise frequency of the fast oscillation under study. Overall, this study demonstrates a functional sublaminar organization of the rat OB, which is supported by previous anatomical findings.

  18. Analysis of using interpulse intervals to generate 128-bit biometric random binary sequences for securing wireless body sensor networks.

    Science.gov (United States)

    Zhang, Guang-He; Poon, Carmen C Y; Zhang, Yuan-Ting

    2012-01-01

    Wireless body sensor network (WBSN), a key building block for m-Health, demands extremely stringent resource constraints and thus lightweight security methods are preferred. To minimize resource consumption, utilizing information already available to a WBSN, particularly common to different sensor nodes of a WBSN, for security purposes becomes an attractive solution. In this paper, we tested the randomness and distinctiveness of the 128-bit biometric binary sequences (BSs) generated from interpulse intervals (IPIs) of 20 healthy subjects as well as 30 patients suffered from myocardial infarction and 34 subjects with other cardiovascular diseases. The encoding time of a biometric BS on a WBSN node is on average 23 ms and memory occupation is 204 bytes for any given IPI sequence. The results from five U.S. National Institute of Standards and Technology statistical tests suggest that random biometric BSs can be generated from both healthy subjects and cardiovascular patients and can potentially be used as authentication identifiers for securing WBSNs. Ultimately, it is preferred that these biometric BSs can be used as encryption keys such that key distribution over the WBSN can be avoided.

  19. Observation and Modeling of Storm Generated Acoustic Waves in the Ionosphere Revealed in a Dense Network of GPS Receivers

    Science.gov (United States)

    Walterscheid, R. L.; Azeem, S. I.

    2017-12-01

    Acoustic waves generated in the lower atmosphere may become an important source of variably in the upper atmosphere. Although they are excited with small amplitudes they are minimally subject to viscous dissipation and may reach significant amplitudes at F-region altitudes. A number of studies in the 1970s showed clear signatures in ionosonde data in the infrasonic period range attributable to thunder storm activity. We have examined Total Electron Content data from a dense network of over 4000 ground-based GPS receivers over the continental United States during an outbreak of severe weather, including tornados, over Kansas in May 2015. A sequence of GPS TEC images showed clear Traveling Ionospheric Disturbances (TIDs) in the form of concentric rings moving outward from the center of the storm region. The characteristics of the disturbance (phase speed and frequency) were consistent with acoustic waves in the infrasonic range. We have modeled the disturbance by including a tropospheric heat source representing latent heat release from a large thunderstorm. The disturbance at ionospheric altitudes resembles the observed disturbance in terms of phase speed, frequency and horizontal wavelength. We conclude that the observed TIDs in TEC were caused by an acoustic wave generated by deep convection.

  20. Correlation-Based Network Generation, Visualization, and Analysis as a Powerful Tool in Biological Studies: A Case Study in Cancer Cell Metabolism

    Directory of Open Access Journals (Sweden)

    Albert Batushansky

    2016-01-01

    Full Text Available In the last decade vast data sets are being generated in biological and medical studies. The challenge lies in their summary, complexity reduction, and interpretation. Correlation-based networks and graph-theory based properties of this type of networks can be successfully used during this process. However, the procedure has its pitfalls and requires specific knowledge that often lays beyond classical biology and includes many computational tools and software. Here we introduce one of a series of methods for correlation-based network generation and analysis using freely available software. The pipeline allows the user to control each step of the network generation and provides flexibility in selection of correlation methods and thresholds. The pipeline was implemented on published metabolomics data of a population of human breast carcinoma cell lines MDA-MB-231 under two conditions: normal and hypoxia. The analysis revealed significant differences between the metabolic networks in response to the tested conditions. The network under hypoxia had 1.7 times more significant correlations between metabolites, compared to normal conditions. Unique metabolic interactions were identified which could lead to the identification of improved markers or aid in elucidating the mechanism of regulation between distantly related metabolites induced by the cancer growth.

  1. Next Generation Waste Tracking: Linking Legacy Systems with Modern Networking Technologies

    International Nuclear Information System (INIS)

    Walker, Randy M.; Resseguie, David R.; Shankar, Mallikarjun; Gorman, Bryan L.; Smith, Cyrus M.; Hill, David E.

    2010-01-01

    of existing legacy hazardous, radioactive and related informational databases and systems using emerging Web 2.0 technologies. These capabilities were used to interoperate ORNL s waste generating, packaging, transportation and disposal with other DOE ORO waste management contractors. Importantly, the DOE EM objectives were accomplished in a cost effective manner without altering existing information systems. A path forward is to demonstrate and share these technologies with DOE EM, contractors and stakeholders. This approach will not alter existing DOE assets, i.e. Automated Traffic Management Systems (ATMS), Transportation Tracking and Communications System (TRANSCOM), the Argonne National Laboratory (ANL) demonstrated package tracking system, etc.

  2. Understanding processes that generate flash floods in the arid Judean Desert to the Dead Sea - a measurement network

    Science.gov (United States)

    Hennig, Hanna; Rödiger, Tino; Laronne, Jonathan B.; Geyer, Stefan; Merz, Ralf

    2016-04-01

    Flash floods in (semi-) arid regions are fascinating in their suddenness and can be harmful for humans, infrastructure, industry and tourism. Generated within minutes, an early warning system is essential. A hydrological model is required to quantify flash floods. Current models to predict flash floods are often based on simplified concepts and/or on concepts which were developed for humid regions. To more closely relate such models to local conditions, processes within catchments where flash floods occur require consideration. In this study we present a monitoring approach to decipher different flash flood generating processes in the ephemeral Wadi Arugot on the western side of the Dead Sea. To understand rainfall input a dense rain gauge network was installed. Locations of rain gauges were chosen based on land use, slope and soil cover. The spatiotemporal variation of rain intensity will also be available from radar backscatter. Level pressure sensors located at the outlet of major tributaries have been deployed to analyze in which part of the catchment water is generated. To identify the importance of soil moisture preconditions, two cosmic ray sensors have been deployed. At the outlet of the Arugot water is sampled and level is monitored. To more accurately determine water discharge, water velocity is measured using portable radar velocimetry. A first analysis of flash flood processes will be presented following the FLEX-Topo concept .(Savenije, 2010), where each landscape type is represented using an individual hydrological model according to the processes within the three hydrological response units: plateau, desert and outlet. References: Savenije, H. H. G.: HESS Opinions "Topography driven conceptual modelling (FLEX-Topo)", Hydrol. Earth Syst. Sci., 14, 2681-2692, doi:10.5194/hess-14-2681-2010, 2010.

  3. Excitatory Modulation of the preBötzinger Complex Inspiratory Rhythm Generating Network by Endogenous Hydrogen Sulfide

    Directory of Open Access Journals (Sweden)

    Glauber S. F. da Silva

    2017-06-01

    Full Text Available Hydrogen Sulfide (H2S is one of three gasotransmitters that modulate excitability in the CNS. Global application of H2S donors or inhibitors of H2S synthesis to the respiratory network has suggested that inspiratory rhythm is modulated by exogenous and endogenous H2S. However, effects have been variable, which may reflect that the RTN/pFRG (retrotrapezoid nucleus, parafacial respiratory group and the preBötzinger Complex (preBötC, critical for inspiratory rhythm generation are differentially modulated by exogenous H2S. Importantly, site-specific modulation of respiratory nuclei by H2S means that targeted, rather than global, manipulation of respiratory nuclei is required to understand the role of H2S signaling in respiratory control. Thus, our aim was to test whether endogenous H2S, which is produced by cystathionine-β-synthase (CBS in the CNS, acts specifically within the preBötC to modulate inspiratory activity under basal (in vitro/in vivo and hypoxic conditions (in vivo. Inhibition of endogenous H2S production by bath application of the CBS inhibitor, aminooxyacetic acid (AOAA, 0.1–1.0 mM to rhythmic brainstem spinal cord (BSSC and medullary slice preparations from newborn rats, or local application of AOAA into the preBötC (slices only caused a dose-dependent decrease in burst frequency. Unilateral injection of AOAA into the preBötC of anesthetized, paralyzed adult rats decreased basal inspiratory burst frequency, amplitude and ventilatory output. AOAA in vivo did not affect the initial hypoxia-induced (10% O2, 5 min increase in ventilatory output, but enhanced the secondary hypoxic respiratory depression. These data suggest that the preBötC inspiratory network receives tonic excitatory modulation from the CBS-H2S system, and that endogenous H2S attenuates the secondary hypoxic respiratory depression.

  4. Changes in Policy and Market and Network Regulation to Increase Power Generation by Renewables and DG in the EU

    International Nuclear Information System (INIS)

    Van Oostvoorn, F.; Van der Welle, A.

    2009-01-01

    Recently the importance of 'Large scale DER integration' has increased as means to meet the ambitious 2020 EU policy objectives and targets for RES, emissions reductions and energy efficiency. Increasing the role of RES and DG (Renewable Energy Sources and Distributed Generation or DER) in supply is also highly beneficial for reducing EU dependency on gas and oil imports. In this EU context, it is important to review the current barriers, support policies and network regulation for integration of more DG, RES and small scale CHP (Combined Heat and Power) in the power systems. Several studies conducted for the EU and led by the ECN (Energy research Centre of the Netherlands) reveal that currently, in some, mainly new, Member States, the contribution of RES and DG is still very low. However, in coming decades the share of variable RES-E sources should become much larger in many EU countries. Note that 20% RES in a country in 2020 implies a share of electricity supply by RES of about 30% or more. Currently, countries like Denmark and Spain, already experience such a large contribution of (mostly intermittent type) renewables and this is already negatively impacting power system costs. Now the question arises whether or not we can increase the contribution of RES to the power supply beyond 20-30% without raising system inefficiency and what changes in system conditions and market and network regulation are necessary to efficiently absorb large volumes of so called intermittent RES supply resources. Based on findings from several large EU projects promoting the role of RES and DG in the power supply, the authors discuss and present the different barriers and solutions that should facilitate meeting the ambitious EU policy targets for RES in 2020

  5. Letter to the editor: Generation of self organized critical connectivity network map (SOCCNM of randomly situated water bodies during flooding process

    Directory of Open Access Journals (Sweden)

    B. S. Daya Sagar

    2001-01-01

    Full Text Available This letter presents a brief framework based on nonlinear morphological transformations to generate a self organized critical connectivity network map (SOCCNM in 2-dimensional space. This simple and elegant framework is implemented on a section that contains a few simulated water bodies to generate SOCCNM. This is based on a postulate that the randomly situated surface water bodies of various sizes and shapes self organize during flooding process.

  6. Letter to the editor: Generation of self organized critical connectivity network map (SOCCNM) of randomly situated water bodies during flooding process

    OpenAIRE

    B. S. Daya Sagar

    2001-01-01

    This letter presents a brief framework based on nonlinear morphological transformations to generate a self organized critical connectivity network map (SOCCNM) in 2-dimensional space. This simple and elegant framework is implemented on a section that contains a few simulated water bodies to generate SOCCNM. This is based on a postulate that the randomly situated surface water bodies of various sizes and shapes self organize during flooding process.

  7. Neural network radiative transfer solvers for the generation of high resolution solar irradiance spectra parameterized by cloud and aerosol parameters

    Science.gov (United States)

    Taylor, M.; Kosmopoulos, P. G.; Kazadzis, S.; Keramitsoglou, I.; Kiranoudis, C. T.

    2016-01-01

    This paper reports on the development of a neural network (NN) model for instantaneous and accurate estimation of solar radiation spectra and budgets geared toward satellite cloud data using a ≈2.4 M record, high-spectral resolution look up table (LUT) generated with the radiative transfer model libRadtran. Two NN solvers, one for clear sky conditions dominated by aerosol and one for cloudy skies, were trained on a normally-distributed and multiparametric subset of the LUT that spans a very broad class of atmospheric and meteorological conditions as inputs with corresponding high resolution solar irradiance target spectra as outputs. The NN solvers were tested by feeding them with a large (10 K record) ;off-grid; random subset of the LUT spanning the training data space, and then comparing simulated outputs with target values provided by the LUT. The NN solvers demonstrated a capability to interpolate accurately over the entire multiparametric space. Once trained, the NN solvers allow for high-speed estimation of solar radiation spectra with high spectral resolution (1 nm) and for a quantification of the effect of aerosol and cloud optical parameters on the solar radiation budget without the need for a massive database. The cloudy sky NN solver was applied to high spatial resolution (54 K pixel) cloud data extracted from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat Second Generation 3 (MSG3) satellite and demonstrated that coherent maps of spectrally-integrated global horizontal irradiance at this resolution can be produced on the order of 1 min.

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

    Science.gov (United States)

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

    2015-05-01

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

  9. Genetic data from avian influenza and avian paramyxoviruses generated by the European network of excellence (EPIZONE) between 2006 and 2011 - Review and recommendations for surveillance

    NARCIS (Netherlands)

    Dundon, W.G.; Heidari, A.; Fusaro, A.; Monne, I.; Beato, M.S.; Cattoli, G.; Koch, G.; Starick, E.; Brown, I.H.; Aldous, E.W.; Briand, F.X.; Gall-Reculé, Le G.; Jestin, V.; Jorgensen, P.H.; Berg, M.; Zohari, S.; Metreveli, G.; Munir, M.; Stahl, K.; Albina, E.; Hammoumi, S.; Gil, P.; Servan de Almeida, R.; Smietanka, K.; Domanska-Blicharz, K.; Minta, Z.; Borm, van S.; Berg, van den T.; Martin, A.M.; Barbieri, I.; Capua, I.

    2012-01-01

    Since 2006, the members of the molecular epidemiological working group of the European “EPIZONE” network of excellence have been generating sequence data on avianinfluenza and avianparamyxoviruses from both European and African sources in an attempt to more fully understand the circulation and

  10. Genetic data from avian influenza and avian paramyxoviruses generated by the European network of excellence (EPIZONE) between 2006 and 2011—Review and recommendations for surveillance

    DEFF Research Database (Denmark)

    Dundon, William G.; Heidari, Alireza; Fusaro, Alice

    2012-01-01

    Since 2006, the members of the molecular epidemiological working group of the European “EPIZONE” network of excellence have been generating sequence data on avian influenza and avian paramyxoviruses from both European and African sources in an attempt to more fully understand the circulation...

  11. Novel wavelength division multiplex-radio over fiber-passive optical network architecture for multiple access points based on multitone generation and triple sextupling frequency

    Science.gov (United States)

    Cheng, Guangming; Guo, Banghong; Liu, Songhao; Huang, Xuguang

    2014-01-01

    An innovative wavelength division multiplex-radio over fiber-passive optical network architecture for multiple access points (AP) based on multitone generation and triple sextupling frequency is proposed and demonstrated. A dual-drive Mach-Zehnder modulator (DD-MZM) is utilized to realize the multitone generation. Even sidebands are suppressed to make the adjacent frequency separation twice the frequency of the local oscillator by adjusting the modulation voltage of the DD-MZM. Due to adopting three fiber Bragg gratings to reflect the unmodulated sidebands for uplink communications source free at optical network unit (ONU), is achieved. The system can support at least three APs at one ONU simultaneously with a 30 km single-mode fiber (SMF) transmission and 5 Gb/s data rate both for uplink and downlink communications. The theoretical analysis and simulation results show the architecture has an excellent performance and will be a promising candidate in future hybrid access networks.

  12. Methods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists

    Directory of Open Access Journals (Sweden)

    Brenton J Prettejohn

    2011-03-01

    Full Text Available Many simulations of networks in computational neuroscience assume completely homogenous random networks of the Erd"{o}s-R'{e}nyi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the `scale-free' and `small-world' properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks.

  13. Voltage optimal regulation of distribution power network with a source of dispersed generation owned by either one or several owners

    Directory of Open Access Journals (Sweden)

    Олександр Станиславович Яндульський

    2015-11-01

    Full Text Available The criteria of optimal voltage regulation in the electrical distribution network (EDN with a source of dispersed generation (SDG were formulated, if they belong to either one or different owners, taking into account the peculiarities of voltage regulation by means of the SDG and the OLTC system of the transformer. It was found out that under the conditions of economic unprofitability of voltage regulation, in accordance with the above criteria, the owners should take up coordinated work – the general objective function of voltage regulation to improve the effectiveness of regulation and achieve cost-effectiveness. The criteria of optimal voltage regulation if EDN and SDG belong to one owner were formulated. If their work becomes coordinated it is necessary to know exactly which transformer must be regulated; so a transformer with OLTC system should be chosen. Selection sequence is based on the calculation of the sensitivity of the voltage at the nodes within SDG with respect to OLTC position. The proposed OLTC system and SDG coordinated work makes it possible to increase the effectiveness of voltage regulation in the EDN with SDG under different conditions of ownership and increase the economic profitability of regulation

  14. Use of Hot Rolling for Generating Low Deviation Twins and a Disconnected Random Boundary Network in Inconel 600 Alloy

    Science.gov (United States)

    Sahu, Sandeep; Yadav, Prabhat Chand; Shekhar, Shashank

    2018-02-01

    In this investigation, Inconel 600 alloy was thermomechanically processed to different strains via hot rolling followed by a short-time annealing treatment to determine an appropriate thermomechanical process to achieve a high fraction of low-Σ CSL boundaries. Experimental results demonstrate that a certain level of deformation is necessary to obtain effective "grain boundary engineering"; i.e., the deformation must be sufficiently high to provide the required driving force for postdeformation static recrystallization, yet it should be low enough to retain a large fraction of original twin boundaries. Samples processed in such a fashion exhibited 77 pct length fraction of low-Σ CSL boundaries, a dominant fraction of which was from Σ3 ( 64 pct), the latter with very low deviation from its theoretical misorientation. The application of hot rolling also resulted in a very low fraction of Σ1 ( 1 pct) boundaries, as desired. The process also leads to so-called "triple junction engineering" with the generation of special triple junctions, which are very effective in disrupting the connectivity of the random grain boundary network.

  15. Policy and Regulatory Roadmaps for the Integration of Distributed Generation and the Development of Sustainable Electricity Networks. Final Report of the SUSTELNET project

    Energy Technology Data Exchange (ETDEWEB)

    Scheepers, M.J.J. [ECN Policy Studies, Petten (Netherlands)

    2004-08-01

    The SUSTELNET project has been created to identify criteria for a regulatory framework for future electricity markets and network structures that create a level playing field between centralised and decentralised generation and facilitate the integration of renewable energy sources (RES). Furthermore, the objective of the project was to develop regulatory roadmaps for the transition to a sustainable electricity market and network structure. This report summarizes the results of the project. These results consist of: criteria, guidelines and rationales for a future electricity policy and regulatory framework, an outline for the development of regulatory roadmaps and nine national regulatory roadmaps (for Denmark, Germany, Italy, the Netherlands, United Kingdom, Czech Republic, Poland, Hungary and Slovakia), recommendations for a European regulatory policy on distributed generation and a benchmark study of current Member States policies towards distributed generation.

  16. A neural network model for the automatic detection and forecast of convective cells based on meteosat second generation data

    Science.gov (United States)

    Puca, S.; de Leonibus, L.; Zauli, F.; Rosci, P.; Musmanno, L.

    The Mesoscale Convective Systems (MCSs) are often correlated with heavy rainfall, thunderstorms and hail showers, frequently causing significant damages. The most intensive weather activities occur during the maturing stage of the development, which can be found in the case of a multi-cell storm in the centre of the convective complex systems. These convective systems may occur in several different unstable air mass; in a cold air mass behind a polar cold front, in the frontal zone of a polar front and in warm air ahead of a polar warm front. To understand the meteorological situation and apply the best conceptual model, the knowledge of the convective cluster is often not enough. In many cases the forecasters need to know the distribution of the convective cells in the cloudy cluster. A model, running in operational mode at the Italian Air Force Meteorological Service (UGM/CNMCA), for the automatic detection and forecast of the convective cells, is here proposed. The application relays on the Meteosat Second Generation infrared (IR) windows (10.8 μ m, 7.3 μ m) and the two water vapour (WV) channels (6.2 μ m and 7.3 μ m), giving as output the detection of the convective cells and their evolution for the next 15 and 30 minutes. The format of the output of the product is the last IR (10.8 μ m) image where the detected cells, their development and their tracking are represented. This multispectral method, based on a variable threshold method during the detection phase and a neural network algorithm during the forecast phase, allowed us to define a model able to detect the convective cells present in a convective cluster, plot their distribution and forecast the evolution of them for the next 15 and 30 minutes with a good efficiency. For analysing the performance of the model with the Meteosat Second Generation data, different error functions have been evaluated for various meteorological cloud contexts (i.e. high layer and cirrus clouds). Some methods for

  17. Relationship between trusting behaviors and psychometrics associated with social network and depression among young generation: a pilot study.

    Science.gov (United States)

    Watabe, Motoki; Kato, Takahiro A; Teo, Alan R; Horikawa, Hideki; Tateno, Masaru; Hayakawa, Kohei; Shimokawa, Norihiro; Kanba, Shigenobu

    2015-01-01

    Maladaptive social interaction and its related psychopathology have been highlighted in psychiatry especially among younger generations. In Japan, novel expressive forms of psychiatric phenomena such as "modern-type depression" and "hikikomori" (a syndrome of severe social withdrawal lasting for at least six months) have been reported especially among young people. Economic games such as the trust game have been utilized to evaluate real-world interpersonal relationships as a novel candidate for psychiatric evaluations. To investigate the relationship between trusting behaviors and various psychometric scales, we conducted a trust game experiment with eighty-one Japanese university students as a pilot study. Participants made a risky financial decision about whether to trust each of 40 photographed partners. Participants then answered a set of questionnaires with seven scales including the Lubben Social Network Scale (LSNS)-6 and the Patient Health Questionnaire (PHQ)-9. Consistent with previous research, male participants trusted partners more than female participants. Regression analysis revealed that LSNS-family (perceived support from family) for male participants, and item 8 of PHQ-9 (subjective agitation and/or retardation) for female participants were associated with participants' trusting behaviors. Consistent with claims by social scientists, our data suggest that, for males, support from family was negatively associated with cooperative behavior toward non-family members. Females with higher subjective agitation (and/or retardation) gave less money toward males and high attractive females, but not toward low attractive females in interpersonal relationships. We believe that our data indicate the possible impact of economic games in psychiatric research and clinical practice, and validation in clinical samples including modern-type depression and hikikomori should be investigated.

  18. Relationship between trusting behaviors and psychometrics associated with social network and depression among young generation: a pilot study.

    Directory of Open Access Journals (Sweden)

    Motoki Watabe

    Full Text Available Maladaptive social interaction and its related psychopathology have been highlighted in psychiatry especially among younger generations. In Japan, novel expressive forms of psychiatric phenomena such as "modern-type depression" and "hikikomori" (a syndrome of severe social withdrawal lasting for at least six months have been reported especially among young people. Economic games such as the trust game have been utilized to evaluate real-world interpersonal relationships as a novel candidate for psychiatric evaluations. To investigate the relationship between trusting behaviors and various psychometric scales, we conducted a trust game experiment with eighty-one Japanese university students as a pilot study. Participants made a risky financial decision about whether to trust each of 40 photographed partners. Participants then answered a set of questionnaires with seven scales including the Lubben Social Network Scale (LSNS-6 and the Patient Health Questionnaire (PHQ-9. Consistent with previous research, male participants trusted partners more than female participants. Regression analysis revealed that LSNS-family (perceived support from family for male participants, and item 8 of PHQ-9 (subjective agitation and/or retardation for female participants were associated with participants' trusting behaviors. Consistent with claims by social scientists, our data suggest that, for males, support from family was negatively associated with cooperative behavior toward non-family members. Females with higher subjective agitation (and/or retardation gave less money toward males and high attractive females, but not toward low attractive females in interpersonal relationships. We believe that our data indicate the possible impact of economic games in psychiatric research and clinical practice, and validation in clinical samples including modern-type depression and hikikomori should be investigated.

  19. INTEGRAL INDEX OF OPERATION QUALITY FOR EVALUATION OF IMPACT OF DISTRIBUTIVE GENERATION SOURCES ON ELECTRIC NETWORK MODES

    Directory of Open Access Journals (Sweden)

    Petro D. Lezhniuk

    2017-06-01

    Full Text Available Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

  20. Community-Based Social Networks: Generation of Power Law Degree Distribution and IP Solutions to the KPP

    Science.gov (United States)

    Wu, Wentao

    2012-01-01

    The objective of this thesis is two-fold: (1) to investigate the degree distribution property of community-based social networks (CSNs) and (2) to provide solutions to a pertinent problem, the Key Player Problem. In the first part of this thesis, we consider a growing community-based network in which the ability of nodes competing for links to new…

  1. Study on the energy-efficient scheme based on the interconnection of optical-network-units for next generation optical access network

    Science.gov (United States)

    Lv, Yunxin; Jiang, Ning; Qiu, Kun; Xue, Chenpeng

    2014-12-01

    An energy-efficient scheme based on the interconnection of optical network unit (ONU) is introduced, which can significantly reduce the energy consumption of the low-traffic operation. The energy consumption model for the ONU-interconnected optical access network (OAN) based on the electronic switch (ES) technology is established, and the energy efficiency of the proposed scheme is analyzed and compared with that of the OAN using optical switch (OS). The simulation results demonstrate that the ONU-interconnected scheme can efficiently reduce the energy consumption of OAN, and it shows a good energy consumption performance under daily traffic model.

  2. A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

    Science.gov (United States)

    Moreno-Tapia, Sandra Veronica; Vera-Salas, Luis Alberto; Osornio-Rios, Roque Alfredo; Dominguez-Gonzalez, Aurelio; Stiharu, Ion; de Jesus Romero-Troncoso, Rene

    2010-01-01

    Computer numerically controlled (CNC) machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA)-based sensor node. PMID:22163602

  3. A Field Programmable Gate Array-Based Reconfigurable Smart-Sensor Network for Wireless Monitoring of New Generation Computer Numerically Controlled Machines

    Directory of Open Access Journals (Sweden)

    Ion Stiharu

    2010-08-01

    Full Text Available Computer numerically controlled (CNC machines have evolved to adapt to increasing technological and industrial requirements. To cover these needs, new generation machines have to perform monitoring strategies by incorporating multiple sensors. Since in most of applications the online Processing of the variables is essential, the use of smart sensors is necessary. The contribution of this work is the development of a wireless network platform of reconfigurable smart sensors for CNC machine applications complying with the measurement requirements of new generation CNC machines. Four different smart sensors are put under test in the network and their corresponding signal processing techniques are implemented in a Field Programmable Gate Array (FPGA-based sensor node.

  4. The Next Generation of Scientists: Examining the Experiences of Graduate Students in Network-Level Social-Ecological Science

    Directory of Open Access Journals (Sweden)

    Michele Romolini

    2013-09-01

    Full Text Available By integrating the research and resources of hundreds of scientists from dozens of institutions, network-level science is fast becoming one scientific model of choice to address complex problems. In the pursuit to confront pressing environmental issues such as climate change, many scientists, practitioners, policy makers, and institutions are promoting network-level research that integrates the social and ecological sciences. To understand how this scientific trend is unfolding among rising scientists, we examined how graduate students experienced one such emergent social-ecological research initiative, Integrated Science for Society and Environment, within the large-scale, geographically distributed Long Term Ecological Research (LTER Network. Through workshops, surveys, and interviews, we found that graduate students faced challenges in how they conceptualized and practiced social-ecological research within the LTER Network. We have presented these conceptual challenges at three scales: the individual/project, the LTER site, and the LTER Network. The level of student engagement with and knowledge of the LTER Network was varied, and students faced different institutional, cultural, and logistic barriers to practicing social-ecological research. These types of challenges are unlikely to be unique to LTER graduate students; thus, our findings are relevant to other scientific networks implementing new social-ecological research initiatives.

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

    OpenAIRE

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

    2015-01-01

    Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of “gene” itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way w...

  6. Very late stent thrombosis with second generation drug eluting stents compared to bare metal stents: Network meta-analysis of randomized primary percutaneous coronary intervention trials.

    Science.gov (United States)

    Philip, Femi; Stewart, Susan; Southard, Jeffrey A

    2016-07-01

    The relative safety of drug-eluting stents (DES) and bare-metal stents (BMS) in primary percutaneous coronary intervention (PPCI) in ST elevation myocardial infarction (STEMI) continues to be debated. The long-term clinical outcomes between second generation DES and BMS for primary percutaneous coronary intervention (PCI) using network meta-analysis were compared. Randomized controlled trials comparing stent types (first generation DES, second generation DES, or BMS) were considered for inclusion. A search strategy used Medline, Embase, Cochrane databases, and proceedings of international meetings. Information about study design, inclusion criteria, and sample characteristics were extracted. Network meta-analysis was used to pool direct (comparison of second generation DES to BMS) and indirect evidence (first generation DES with BMS and second generation DES) from the randomized trials. Twelve trials comparing all stents types including 9,673 patients randomly assigned to treatment groups were analyzed. Second generation DES was associated with significantly lower incidence of definite or probable ST (OR 0.59, 95% CI 0.39-0.89), MI (OR 0.59, 95% CI 0.39-0.89), and TVR at 3 years (OR 0.50: 95% CI 0.31-0.81) compared with BMS. In addition, there was a significantly lower incidence of MACE with second generation DES versus BMS (OR 0.54, 95% CI 0.34-0.74) at 3 years. These were driven by a higher rate of TVR, MI and stent thrombosis in the BMS group at 3 years. There was a non-significant reduction in the overall and cardiac mortality [OR 0.83, 95% CI (0.60-1.14), OR 0.88, 95% CI (0.6-1.28)] with the use of second generation DES versus BMS at 3 years. Network meta-analysis of randomized trials of primary PCI demonstrated lower incidence of MACE, MI, TVR, and stent thrombosis with second generation DES compared with BMS. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  7. Multi-Objective Coordinated Planning of Distributed Generation and AC/DC Hybrid Distribution Networks Based on a Multi-Scenario Technique Considering Timing Characteristics

    Directory of Open Access Journals (Sweden)

    Yongchun Yang

    2017-12-01

    Full Text Available With increased direct current (DC load density and the penetration of a large number of distributed generation (DG units in alternating current (AC distribution networks (DNs; a planning approach that considers transforming some of the AC lines into DC lines and building the DC network is proposed. Considering the DG output uncertainty and the load fluctuation, a planning model for an AC/DC hybrid distribution network (DN with the DG based on the construction of multi-scenario technology with timing characteristics is built. In the DG configuration planning model, the lines to be transformed into DC form the access location and the decision regarding the DC or AC form of the newly built lines are considered optimizing variables. The DG investment, the network and converters of the DG and load, the active power loss and the voltage stability are considered in the objective functions. An improved adaptive niche genetic algorithm based on the fuzzy degree of membership and variance weighting is used to solve the nested model. Finally, considering the improved electrical and electronic engineers 33 (IEEE33 node system as an example, the correctness and effectiveness of the proposed planning method are verified. Compared to the plan without transforming some of the AC lines into DC lines and building a DC network, more DG can be admitted, and the economic cost of the AC/DC hybrid DN is notably decreased when planning to transform some of the AC lines into DC lines and build a DC network. The active power network loss and the voltage stability index are similarly further optimized.

  8. Dual Stack Deployment in a Carrier Grade Network to Fulfill the Demands of Next Generation of Internet

    Directory of Open Access Journals (Sweden)

    Tarique Jamil Saifullah Khanzada

    2013-07-01

    Full Text Available The Internet is migrating from IPv4 (Internet Protocol version 4 to IPv6 (Internet Protocol version 6. The high cost of migration services from IPv4-IPv6 and system complexity are main factors for slow adaption of IPv6 This paper presents the implementation of migration techniques from IPv4-IPv6. Furthermore, existing IPv4 addresses have already been depleted in IANA (Internet Assigned Numbers Authority and will be soon exhausted in RIR (Regional Internet Registry while more clients are joining the Internet. Slower rate of the progress of IPv6 confirms complete shifting from IPv4-IPv6 at once is still long away, although fewer parts of IPv6 have been employed in current market goods. Integration of IPv4 and IPv6 is carried in order to take care of online users. In this paper, it is suggested that hierarchical direction finding structural design in IPv4 and IPv6 will improve the efficiency of IPv4 network. This research work provides the way to design the network scenario for the carrier grade set of connections. The carrier grade network scenario routers are named to be Karachi, Sukkur, Islamabad, Multan and Peshawar for the managerial simulation purposes. The carrier grade network deployment is implemented along with dual stack to migrate to IPv6. This study holds the way to deploy IPv4-IPv6 carrier grade network by providing real time scenario which is yet not considered in the literature to the best of our knowledge

  9. Dual stack deployment in a carrier grade network to fulfill the demands of next generation of internet

    International Nuclear Information System (INIS)

    Khanzada, T.J.S.

    2013-01-01

    The Internet is migrating from IPv4 (Internet Protocol version 4) to IPv6 (Internet Protocol version 6). The high cost of migration services from IPv4-IPv6 and system complexity are main factors for slow adaption of IPv6 This paper presents the implementation of migration techniques from IPv4-IPv6. Furthermore, existing IPv4 addresses have already been depleted in IANA (Internet Assigned Numbers Authority) and will be soon exhausted in RIR (Regional Internet Registry) while more clients are joining the Internet. Slower rate of the progress of IPv6 confirms complete shifting from IPv4-IPv6 at once is still long away, although fewer parts of IPv6 have been employed in current market goods. Integration of IPv4 and IPv6 is carried in order to take care of online users. In this paper, it is suggested that hierarchical direction finding structural design in IPv4 and IPv6 will improve the efficiency of IPv4 network. This research work provides the way to design the network scenario for the carrier grade set of connections. The carrier grade network scenario routers are named to be Karachi, Sukkur, Islamabad, Multan and Peshawar for the managerial simulation purposes. The carrier grade network deployment is implemented along with dual stack to migrate to IPv6. This study holds the way to deploy IPv4-IPv6 carrier grade network by providing real time scenario which is yet not considered in the literature to the best of our knowledge. (author)

  10. A next-generation social media-based relapse prevention intervention for youth depression: Qualitative data on user experience outcomes for social networking, safety, and clinical benefit

    Directory of Open Access Journals (Sweden)

    Olga Santesteban-Echarri

    2017-09-01

    Full Text Available Major depressive disorder (MDD has a high prevalence and relapse rate among young people. For many individuals depression exhibits a severe course, and it is therefore critical to invest in innovative online interventions for depression that are cost-effective, acceptable and feasible. At present, there is a scarcity of research reporting on qualitative data regarding the subjective user experience of young people using social networking-based interventions for depression. This study provides in-depth qualitative insights generated from 38 semi-structured interviews, and a follow-up focus group, with young people (15–25 years after the implementation of a moderated online social therapy intervention for depression relapse prevention (“Rebound”. Exploratory analysis identified patterns of content from interview data related to three main themes: 1 preferred content compared to perceived helpfulness of the online platform, 2 interest in social networking, and 3 protective environment. Two clear groups emerged; those who perceived the social networking component of the intervention as the most helpful component; and those who preferred to engage in therapy content, receiving individualized content suggested by moderators. The Rebound intervention was shown to be acceptable for young people with major depression. Integration of social networking features appears to enhance intervention engagement for some young people recovering from depression.

  11. GLM Proxy Data Generation: Methods for Stroke/Pulse Level Inter-Comparison of Ground-Based Lightning Reference Networks

    Science.gov (United States)

    Cummins, Kenneth L.; Carey, Lawrence D.; Schultz, Christopher J.; Bateman, Monte G.; Cecil, Daniel J.; Rudlosky, Scott D.; Petersen, Walter Arthur; Blakeslee, Richard J.; Goodman, Steven J.

    2011-01-01

    In order to produce useful proxy data for the GOES-R Geostationary Lightning Mapper (GLM) in regions not covered by VLF lightning mapping systems, we intend to employ data produced by ground-based (regional or global) VLF/LF lightning detection networks. Before using these data in GLM Risk Reduction tasks, it is necessary to have a quantitative understanding of the performance of these networks, in terms of CG flash/stroke DE, cloud flash/pulse DE, location accuracy, and CLD/CG classification error. This information is being obtained through inter-comparison with LMAs and well-quantified VLF/LF lightning networks. One of our approaches is to compare "bulk" counting statistics on the spatial scale of convective cells, in order to both quantify relative performance and observe variations in cell-based temporal trends provided by each network. In addition, we are using microsecond-level stroke/pulse time correlation to facilitate detailed inter-comparisons at a more-fundamental level. The current development status of our ground-based inter-comparison and evaluation tools will be presented, and performance metrics will be discussed through a comparison of Vaisala s Global Lightning Dataset (GLD360) with the NLDN at locations within and outside the U.S.

  12. Distribution of networks generating and coordinating locomotor activity in the neonatal rat spinal cord in vitro: a lesion study

    DEFF Research Database (Denmark)

    Kjaerulff, O; Kiehn, O

    1996-01-01

    , these pathways were distributed along the lumbar enlargement. Both lateral and ventral funiculi were sufficient to coordinate activity in the rostral and caudal regions. We conclude that the networks organizing locomotor-related activity in the spinal cord of the newborn rat are distributed....

  13. The collaborative African genomics network training program: A trainee perspective on training the next generation of African scientists

    Science.gov (United States)

    The Collaborative African Genomics Network (CAfGEN) aims to establish sustainable genomics research programs in Botswana and Uganda through long-term training of PhD students from these countries at Baylor College of Medicine. Here, we present an overview of the CAfGEN PhD training program alongside...

  14. On Stability of Sustainable Power Systems : Network Fault Response of Transmission Systems with Very High Penetration of Distributed Generation

    NARCIS (Netherlands)

    Boemer, J.

    2016-01-01

    Power systems are undergoing a historic structural and technological transformation. The increase of distributed generation (DG), recently mostly wind power park modules (WPPMs) and photovoltaic power park modules (PVPPMs), is already changing the way power systems are structured and operated.

  15. Cooperation of the ER-shaping proteins atlastin, lunapark, and reticulons to generate a tubular membrane network

    OpenAIRE

    Wang, Songyu; Tukachinsky, Hanna; Romano, Fabian B; Rapoport, Tom A

    2016-01-01

    eLife digest The endoplasmic reticulum is a compartment within the cells of plants, animals and other eukaryotes. This compartment plays a number of roles within cells, for example, serving as the site where many proteins and fat molecules are built. Most often the endoplasmic reticulum exists as a network of thin tubules. However, this shape changes during the lifetime of a single cell, and the endoplasmic reticulum converts into flattened structures known as sheets when the cell divides. Th...

  16. Cooperation of the ER-shaping proteins atlastin, lunapark, and reticulons to generate a tubular membrane network.

    Science.gov (United States)

    Wang, Songyu; Tukachinsky, Hanna; Romano, Fabian B; Rapoport, Tom A

    2016-09-13

    In higher eukaryotes, the endoplasmic reticulum (ER) contains a network of membrane tubules, which transitions into sheets during mitosis. Network formation involves curvature-stabilizing proteins, including the reticulons (Rtns), as well as the membrane-fusing GTPase atlastin (ATL) and the lunapark protein (Lnp). Here, we have analyzed how these proteins cooperate. ATL is needed to not only form, but also maintain, the ER network. Maintenance requires a balance between ATL and Rtn, as too little ATL activity or too high Rtn4a concentrations cause ER fragmentation. Lnp only affects the abundance of three-way junctions and tubules. We suggest a model in which ATL-mediated fusion counteracts the instability of free tubule ends. ATL tethers and fuses tubules stabilized by the Rtns, and transiently sits in newly formed three-way junctions. Lnp subsequently moves into the junctional sheets and forms oligomers. Lnp is inactivated by mitotic phosphorylation, which contributes to the tubule-to-sheet conversion of the ER.

  17. The end of life treatment of second generation mobile phone networks: Strategies to reduce the environmental impact

    International Nuclear Information System (INIS)

    Scharnhorst, Wolfram; Althaus, Hans-Joerg; Classen, Mischa; Jolliet, Olivier; Hilty, Lorenz M.

    2005-01-01

    A life cycle assessment was carried out based on a detailed life cycle inventory for a typical GSM 900 mobile phone network and related End of Life (EOL) treatment infrastructure. The environmental relevance of the three life cycle phases: production, use and EOL treatment was analysed using IMPACT2002+. The environmentally preferable EOL treatment alternative was identified on the basis of six previously developed EOL treatment scenarios. The results indicate that the environmental impacts attributable to the use phase dominate the environmental impacts incurred over the entire life cycle of the network. The impacts of the production phase are primarily attributable to the energy intensive manufacturing of printed wiring boards (PWB). The EOL phase dominates the impacts on ecosystem quality. In particular the long-term emissions of heavy metals have critical effects. Detailed analysis of the EOL phase shows that recycling of network materials in general leads to a two fold reduction of environmental impacts: in the EOL phase itself as well as by means of the avoided primary production of materials recovered in the EOL phase. An increase in the material quality of the secondary precious and rare materials leads to a significant reduction in the impacts on human health

  18. Genetic data from avian influenza and avian paramyxoviruses generated by the European network of excellence (EPIZONE) between 2006 and 2011--review and recommendations for surveillance.

    Science.gov (United States)

    Dundon, William G; Heidari, Alireza; Fusaro, Alice; Monne, Isabella; Beato, Maria Serena; Cattoli, Giovanni; Koch, Guus; Starick, Elke; Brown, Ian H; Aldous, Elisabeth W; Briand, François-Xavier; Le Gall-Reculé, Ghislaine; Jestin, Véronique; Jørgensen, Poul H; Berg, Mikael; Zohari, Siamak; Metreveli, Giorgi; Munir, Muhammad; Ståhl, Karl; Albina, Emmanuel; Hammoumi, Saliha; Gil, Patricia; de Almeida, Renata Servan; Smietanka, Krzysztof; Domańska-Blicharz, Katarzyna; Minta, Zenon; Van Borm, Steven; van den Berg, Thierry; Martin, Ana Moreno; Barbieri, Ilaria; Capua, Ilaria

    2012-01-27

    Since 2006, the members of the molecular epidemiological working group of the European "EPIZONE" network of excellence have been generating sequence data on avian influenza and avian paramyxoviruses from both European and African sources in an attempt to more fully understand the circulation and impact of these viruses. This review presents a timely update on the epidemiological situation of these viruses based on sequence data generated during the lifetime of this project in addition to data produced by other groups during the same period. Based on this information and putting it all into a European context, recommendations for continued surveillance of these important viruses within Europe are presented. Copyright © 2011 Elsevier B.V. All rights reserved.

  19. Dataset generated for Dissection of mechanisms of Trypanothione Reductase and Tryparedoxin Peroxidase through dynamic network analysis and simulations in leishmaniasis

    Directory of Open Access Journals (Sweden)

    Anurag Kumar

    2017-12-01

    Full Text Available Leishmaniasis is the second largest parasitic killer disease caused by the protozoan parasite Leishmania, transmitted by the bite of sand flies. It's endemic in the eastern India with 165.4 million populations at risk with the current drug regimen. Three forms of leishmaniasis exist in which cutaneous is the most common form caused by Leishmania major. Trypanothione Reductase (TryR, a flavoprotein oxidoreductase, unique to thiol redox system, is considered as a potential target for chemotherapy for trypanosomatids infection. It is involved in the NADPH dependent reduction of Trypanothione disulphide to Trypanothione. Similarly, is Tryparedoxin Peroxidase (Txnpx, for detoxification of peroxides, an event pivotal for survival of Leishmania in two disparate biological environment. Fe-S plays a major role in regulating redox balance. To check for the closeness between human homologs of these proteins, we have carried the molecular clock analysis followed by molecular modeling of 3D structure of this protein, enabling us to design and test the novel drug like molecules. Molecular clock analysis suggests that human homologs of TryR i.e. Glutathione Reductase and Txnpx respectively are highly diverged in phylogenetic tree, thus, they serve as good candidates for chemotherapy of leishmaniasis. Furthermore, we have done the homology modeling of TryR using template of same protein from Leishmania infantum (PDB ID: 2JK6. This was done using Modeller 9.18 and the resultant models were validated. To inhibit this target, molecular docking was done with various screened inhibitors in which we found Taxifolin acts as common inhibitors for both TryR and Txnpx. We constructed the protein-protein interaction network for the proteins that are involved in the redox metabolism from various Interaction databases and the network was statistically analysed. Keywords: Trypanothione Reductase, Tryparedoxin Peroxidase, L.major, Homology modeling, Molecular clock analysis

  20. MO-DE-BRA-04: The CREATE Medical Physics Research Training Network: Training of New Generation Innovators

    International Nuclear Information System (INIS)

    Seuntjens, J; Collins, L; Devic, S; El Naqa, I; Nadeau, J; Reader, A; Beaulieu, L; Despres, P; Pike, B

    2015-01-01

    Purpose: Over the past century, physicists have played a major role in transforming scientific discovery into everyday clinical applications. However, with the increasingly stringent requirements to regulate medical physics as a health profession, the role of physicists as scientists and innovators has become at serious risk of erosion. These challenges trigger the need for a new, revolutionized training program at the graduate level that respects scientific rigor, attention for medical physics-relevant developments in basic sciences, innovation and entrepreneurship. Methods: A grant proposal was funded by the Collaborative REsearch and Training Experience program (CREATE) of the Natural Sciences and Engineering Research Council (NSERC) of Canada. This enabled the creation of the Medical Physics Research Training Network (MPRTN) around two CAMPEP-accredited medical physics programs. Members of the network consist of medical device companies, government (research and regulatory) and academia. The MPRTN/CREATE program proposes a curriculum with three main themes: (1) radiation physics, (2) imaging & image processing and (3) radiation response, outcomes and modeling. Results: The MPRTN was created mid 2013 (mprtn.com) and features (1) four new basic Ph.D. courses; (2) industry participation in research projects; (3) formal job-readiness training with involvement of guest faculty from academia, government and industry. MPRTN activities since 2013 include 22 conferences; 7 workshops and 4 exchange travels. Three patents were filed or issued, nine awards/best papers were won. Fifteen journal publications were accepted/published, 102 conference abstracts. There are now 13 industry partners. Conclusion: A medical physics research training network has been set up with the goal to harness graduate student’s job-readiness for industry, government and academia in addition to the conventional clinical role. Two years after inception, significant successes have been booked