WorldWideScience

Sample records for generation networks

  1. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    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. Generative Adversarial Networks: An Overview

    Science.gov (United States)

    Creswell, Antonia; White, Tom; Dumoulin, Vincent; Arulkumaran, Kai; Sengupta, Biswa; Bharath, Anil A.

    2018-01-01

    Generative adversarial networks (GANs) provide a way to learn deep representations without extensively annotated training data. They achieve this through deriving backpropagation signals through a competitive process involving a pair of networks. The representations that can be learned by GANs may be used in a variety of applications, including image synthesis, semantic image editing, style transfer, image super-resolution and classification. The aim of this review paper is to provide an overview of GANs for the signal processing community, drawing on familiar analogies and concepts where possible. In addition to identifying different methods for training and constructing GANs, we also point to remaining challenges in their theory and application.

  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. Next generation satellite communications networks

    Science.gov (United States)

    Garland, P. J.; Osborne, F. J.; Streibl, I.

    The paper introduces two potential uses for new space hardware to permit enhanced levels of signal handling and switching in satellite communication service for Canada. One application involves increased private-sector services in the Ku band; the second supports new personal/mobile services by employing higher levels of handling and switching in the Ka band. First-generation satellite regeneration and switching experiments involving the NASA/ACTS spacecraft are described, where the Ka band and switching satellite network problems are emphasized. Second-generation satellite development is outlined based on demand trends for more packet-based switching, low-cost earth stations, and closed user groups. A demonstration mission for new Ka- and Ku-band technologies is proposed, including the payload configuration. The half ANIK E payload is shown to meet the demonstration objectives, and projected to maintain a fully operational payload for at least 10 years.

  6. Network Restoration for Next-Generation Communication and Computing Networks

    Directory of Open Access Journals (Sweden)

    B. S. Awoyemi

    2018-01-01

    Full Text Available Network failures are undesirable but inevitable occurrences for most modern communication and computing networks. A good network design must be robust enough to handle sudden failures, maintain traffic flow, and restore failed parts of the network within a permissible time frame, at the lowest cost achievable and with as little extra complexity in the network as possible. Emerging next-generation (xG communication and computing networks such as fifth-generation networks, software-defined networks, and internet-of-things networks have promises of fast speeds, impressive data rates, and remarkable reliability. To achieve these promises, these complex and dynamic xG networks must be built with low failure possibilities, high network restoration capacity, and quick failure recovery capabilities. Hence, improved network restoration models have to be developed and incorporated in their design. In this paper, a comprehensive study on network restoration mechanisms that are being developed for addressing network failures in current and emerging xG networks is carried out. Open-ended problems are identified, while invaluable ideas for better adaptation of network restoration to evolving xG communication and computing paradigms are discussed.

  7. 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.

  8. 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....

  9. Generative adversarial networks for brain lesion detection

    Science.gov (United States)

    Alex, Varghese; Safwan, K. P. Mohammed; Chennamsetty, Sai Saketh; Krishnamurthi, Ganapathy

    2017-02-01

    Manual segmentation of brain lesions from Magnetic Resonance Images (MRI) is cumbersome and introduces errors due to inter-rater variability. This paper introduces a semi-supervised technique for detection of brain lesion from MRI using Generative Adversarial Networks (GANs). GANs comprises of a Generator network and a Discriminator network which are trained simultaneously with the objective of one bettering the other. The networks were trained using non lesion patches (n=13,000) from 4 different MR sequences. The network was trained on BraTS dataset and patches were extracted from regions excluding tumor region. The Generator network generates data by modeling the underlying probability distribution of the training data, (PData). The Discriminator learns the posterior probability P (Label Data) by classifying training data and generated data as "Real" or "Fake" respectively. The Generator upon learning the joint distribution, produces images/patches such that the performance of the Discriminator on them are random, i.e. P (Label Data = GeneratedData) = 0.5. During testing, the Discriminator assigns posterior probability values close to 0.5 for patches from non lesion regions, while patches centered on lesion arise from a different distribution (PLesion) and hence are assigned lower posterior probability value by the Discriminator. On the test set (n=14), the proposed technique achieves whole tumor dice score of 0.69, sensitivity of 91% and specificity of 59%. Additionally the generator network was capable of generating non lesion patches from various MR sequences.

  10. 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

  11. Network information provision to potential generators: Appendices

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This Code of Practice (CoP) has been prepared to outline the standard of information that Distribution Network Operators (DNOs) should be required to produce in relation to the provision of network maps, schematic diagrams and specific network data. Network information from DNOs may be required by generators (and other customers) in order to assess the potential opportunities available for the connection of new generation plant. Seven Year Statements are published annually by the Transmission Licensees operating in Great Britain, i.e. The National Grid Company, Scottish Power and Scottish Hydro Electric, and contain all the network information relating to each transmission system, e.g. Generation Capacities, System Parameters and Plant Fault Levels. A similar arrangement for DNOs has been outlined in the Electricity Distribution Licence published by Ofgem. Under Condition 25 of the licence, 'The Long Term Development Statement', distribution licence holders are required to make available historic and planned network data. By providing sufficient network information, competition in generation will be improved. At the time of writing, any party interested in assessing distribution network information needs to make contact with the appropriate DNO, identifying the correct department and person. Written applications are then sent to that person, describing the type of network information that is required. Information required from embedded generators by DNOs is specified in detail in both of The Distribution Codes of England and Wales, and Scotland. However, there are no guidelines or details of network information to be provided by DNOs. This Code of Practise is designed to balance this situation and help DNOs, prospective generators and other applicants for information to achieve satisfaction by clarifying expectations. (Author)

  12. 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....... of criticality and security, there are certain physical or logical segregation requirements between the avionic systems. Such segregations can be implemented on the proposed avionic networks with different hierarchies. In order to fulfill the segregation requirements, a tailored heuristic approach for solving...

  13. Modeling documents with Generative Adversarial Networks

    OpenAIRE

    Glover, John

    2016-01-01

    This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

  14. 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...

  15. 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...

  16. Network information provision to potential generators

    Energy Technology Data Exchange (ETDEWEB)

    Nicholson, G.

    2001-07-01

    At the time of finalising this report, an Ofgem consultation is underway on the form of Distribution Licence Condition 25, which will state the requirements for Distribution Network Operators to provide and publish data. This report is also relevant to the DTI Ofgem Embedded Generation Working Group (EGWG), which has recently completed its report and recommendations. It is hoped that this document will provide an overview of the status, importance, role and benefits of network information, which can be utilised by Generators, Network Operators and other industry players in framing their responses to this and future consultations. (Authors)

  17. 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)

  18. Modeling urbanization patterns with generative adversarial networks

    OpenAIRE

    Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

    2018-01-01

    In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

  19. Traffic Management for Next Generation Transport Networks

    DEFF Research Database (Denmark)

    Yu, Hao

    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...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...

  20. Fiber to the home: next generation network

    Science.gov (United States)

    Yang, Chengxin; Guo, Baoping

    2006-07-01

    Next generation networks capable of carrying converged telephone, television (TV), very high-speed internet, and very high-speed bi-directional data services (like video-on-demand (VOD), Game etc.) strategy for Fiber To The Home (FTTH) is presented. The potential market is analyzed. The barriers and some proper strategy are also discussed. Several technical problems like various powering methods, optical fiber cables, and different network architecture are discussed too.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Neural network application to diesel generator diagnostics

    International Nuclear Information System (INIS)

    Logan, K.P.

    1990-01-01

    Diagnostic problems typically begin with the observation of some system behavior which is recognized as a deviation from the expected. The fundamental underlying process is one involving pattern matching cf observed symptoms to a set of compiled symptoms belonging to a fault-symptom mapping. Pattern recognition is often relied upon for initial fault detection and diagnosis. Parallel distributed processing (PDP) models employing neural network paradigms are known to be good pattern recognition devices. This paper describes the application of neural network processing techniques to the malfunction diagnosis of subsystems within a typical diesel generator configuration. Neural network models employing backpropagation learning were developed to correctly recognize fault conditions from the input diagnostic symptom patterns pertaining to various engine subsystems. The resulting network models proved to be excellent pattern recognizers for malfunction examples within the training set. The motivation for employing network models in lieu of a rule-based expert system, however, is related to the network's potential for generalizing malfunctions outside of the training set, as in the case of noisy or partial symptom patterns

  6. Wavelet network controller for nuclear steam generators

    International Nuclear Information System (INIS)

    Habibiyan, H; Sayadian, A; Ghafoori-Fard, H

    2005-01-01

    Poor control of steam generator water level is the main cause of unexpected shutdowns in nuclear power plants. Particularly at low powers, it is a difficult task due to shrink and swell phenomena and flow measurement errors. In addition, the steam generator is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, it seems that design of a suitable controller is a necessary step to enhance plant availability factor. The purpose of this paper is to design, analyze and evaluate a water level controller for U-tube steam generators using wavelet neural networks. Computer simulations show that the proposed controller improves transient response of steam generator water level and demonstrate its superiority to existing controllers

  7. Embedded generation and network management issues

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-07-01

    This report focuses on the characteristics of power generators that are important to accommodation in a distribution system. Part 1 examines the differences between transmission and distribution systems, and issues such as randomness, diversity, predictability, and controllability associated with accommodation in a distribution system. Part 2 concentrates on technical and operational issues relating to embedded generation, and the possible impact of the New Electricity Trading Arrangements. Commercial issues, contractual relationships for network charging and provision of services, and possible ways forward are examined in the last three parts of the report.

  8. Generative Adversarial Networks for Improving Face Classification

    OpenAIRE

    Natten, Jonas

    2017-01-01

    Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Facial recognition can be applied in a wide variety of cases, including entertainment purposes and biometric security. In this thesis we take a look at improving the results of an existing facial recognition approach by utilizing generative adversarial networks to improve the existing dataset. The training data was taken from the LFW dataset[4] and was preprocessed using OpenCV[2] for...

  9. 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

  10. Saliency detection by conditional generative adversarial network

    Science.gov (United States)

    Cai, Xiaoxu; Yu, Hui

    2018-04-01

    Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

  11. 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...

  12. Unified Model for Generation Complex Networks with Utility Preferential Attachment

    International Nuclear Information System (INIS)

    Wu Jianjun; Gao Ziyou; Sun Huijun

    2006-01-01

    In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.

  13. 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.

  14. Cascading Generative Adversarial Networks for Targeted

    KAUST Repository

    Hamdi, Abdullah

    2018-01-01

    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.

  15. 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.

  16. 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.

  17. Application of genetic neural network in steam generator fault diagnosing

    International Nuclear Information System (INIS)

    Lin Xiaogong; Jiang Xingwei; Liu Tao; Shi Xiaocheng

    2005-01-01

    In the paper, a new algorithm which neural network and genetic algorithm are mixed is adopted, aiming at the problems of slow convergence rate and easily falling into part minimums in network studying of traditional BP neural network, and used in the fault diagnosis of steam generator. The result shows that this algorithm can solve the convergence problem in the network trains effectively. (author)

  18. Network reconfiguration and neuronal plasticity in rhythm-generating networks.

    Science.gov (United States)

    Koch, Henner; Garcia, Alfredo J; Ramirez, Jan-Marino

    2011-12-01

    Neuronal networks are highly plastic and reconfigure in a state-dependent manner. The plasticity at the network level emerges through multiple intrinsic and synaptic membrane properties that imbue neurons and their interactions with numerous nonlinear properties. These properties are continuously regulated by neuromodulators and homeostatic mechanisms that are critical to maintain not only network stability and also adapt networks in a short- and long-term manner to changes in behavioral, developmental, metabolic, and environmental conditions. This review provides concrete examples from neuronal networks in invertebrates and vertebrates, and illustrates that the concepts and rules that govern neuronal networks and behaviors are universal.

  19. Wireless Integrated Network Sensors Next Generation

    National Research Council Canada - National Science Library

    Merrill, William

    2004-01-01

    ..., autonomous networking, and distributed operations for wireless networked sensor systems. Multiple types of sensor systems were developed and provided including capabilities for acoustic, seismic, passive infrared detection, and visual imaging...

  20. 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

  1. METHODOLOGY FOR GENERATION OF CORPORATE NETWORK HOSTNAME

    OpenAIRE

    Garrigós, Allan Mac Quinn; Sassi, Renato José

    2011-01-01

    The general concept of corporate network is made up of two or more interconnected computers sharing information, for the right functionality of the sharing. the nomenclature of these computers within the network is extremely important for proper organization of the names on Active Directory (AD -Domain Controller) and removing the duplicated names improperly created equal, removing the arrest of communications between machines with the same name on the network. The aim of this study was to de...

  2. 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

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

    NARCIS (Netherlands)

    Xyngi, I.; Ishchenko, A.; Popov, M.; Sluis, van der 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

  4. The New Generation Russian VLBI Network

    Science.gov (United States)

    Finkelstein, Andrey; Ipatov, Alexander; Smolentsev, Sergey; Mardyshkin, Vyacheslav; Fedotov, Leonid; Surkis, Igor; Ivanov, Dmitrij; Gayazov, Iskander

    2010-01-01

    This paper deals with a new project of the Russian VLBI Network dedicated for Universal Time determinations in quasi on-line mode. The basic principles of the network design and location of antennas are explained. Variants of constructing receiving devices, digital data acquisition system, and phase calibration system are specially considered. The frequency ranges and expected values of noise temperature are given.

  5. 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...

  6. Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

    OpenAIRE

    Jalalifar, Seyed Ali; Hasani, Hosein; Aghajan, Hamid

    2018-01-01

    We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track.

  7. 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.

  8. Next Generation Campus Network Deployment Project Based on Softswitch

    OpenAIRE

    HU Feng; LIU Ziyan

    2011-01-01

    After analyzing the current networks of Guizhou University,we brought forward a scheme of next generation campus networks based on softswitch technology by choosing SoftX3000 switching system of HuaWei and provided the specific solution of accessing campus networks in this paper. It is proved that this scheme is feasible by using OPNET, which not only accomplished the integration of the PSTN and IP networks but also achieved the combining of voice services and data services.

  9. 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.

  10. Next Generation Network Routing and Control Plane

    DEFF Research Database (Denmark)

    Fu, Rong

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

  11. 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...

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

    OpenAIRE

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

    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) 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 u...

  13. 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.

  14. Individual heterogeneity generating explosive system network dynamics.

    Science.gov (United States)

    Manrique, Pedro D; Johnson, Neil F

    2018-03-01

    Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

  15. Individual heterogeneity generating explosive system network dynamics

    Science.gov (United States)

    Manrique, Pedro D.; Johnson, Neil F.

    2018-03-01

    Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

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

    DEFF Research Database (Denmark)

    Thongthammachart, Saowanee; Olesen, Henning

    2003-01-01

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

  17. 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

  18. Synthetic aperture radar ship discrimination, generation and latent variable extraction using information maximizing generative adversarial networks

    CSIR Research Space (South Africa)

    Schwegmann, Colin P

    2017-07-01

    Full Text Available such as Synthetic Aperture Radar imagery. To aid in the creation of improved machine learning-based ship detection and discrimination methods this paper applies a type of neural network known as an Information Maximizing Generative Adversarial Network. Generative...

  19. 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…

  20. 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.

  1. 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 ...

  2. 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

  3. ALGORITHMS FOR TETRAHEDRAL NETWORK (TEN) GENERATION

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The Tetrahedral Network(TEN) is a powerful 3-D vector structure in GIS, which has a lot of advantages such as simple structure, fast topological relation processing and rapid visualization. The difficulty of TEN application is automatic creating data structure. Al though a raster algorithm has been introduced by some authors, the problems in accuracy, memory requirement, speed and integrity are still existent. In this paper, the raster algorithm is completed and a vector algorithm is presented after a 3-D data model and structure of TEN have been introducted. Finally, experiment, conclusion and future work are discussed.

  4. 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.

  5. Automated Item Generation with Recurrent Neural Networks.

    Science.gov (United States)

    von Davier, Matthias

    2018-03-12

    Utilizing technology for automated item generation is not a new idea. However, test items used in commercial testing programs or in research are still predominantly written by humans, in most cases by content experts or professional item writers. Human experts are a limited resource and testing agencies incur high costs in the process of continuous renewal of item banks to sustain testing programs. Using algorithms instead holds the promise of providing unlimited resources for this crucial part of assessment development. The approach presented here deviates in several ways from previous attempts to solve this problem. In the past, automatic item generation relied either on generating clones of narrowly defined item types such as those found in language free intelligence tests (e.g., Raven's progressive matrices) or on an extensive analysis of task components and derivation of schemata to produce items with pre-specified variability that are hoped to have predictable levels of difficulty. It is somewhat unlikely that researchers utilizing these previous approaches would look at the proposed approach with favor; however, recent applications of machine learning show success in solving tasks that seemed impossible for machines not too long ago. The proposed approach uses deep learning to implement probabilistic language models, not unlike what Google brain and Amazon Alexa use for language processing and generation.

  6. Generating pipeline networks for corrosion assessment

    Energy Technology Data Exchange (ETDEWEB)

    Ferguson, J. [Cimarron Engineering Ltd., Calgary, AB (Canada)

    2008-07-01

    Production characteristics and gas-fluid compositions of fluids must be known in order to assess pipelines for internal corrosion risk. In this study, a gathering system pipeline network was built in order to determine corrosion risk for gathering system pipelines. Connections were established between feeder and collector lines in order measure upstream production and the weighted average of the upstream composition of each pipeline in the system. A Norsok M-506 carbon dioxide (CO{sub 2}) corrosion rate model was used to calculate corrosion rates. A spreadsheet was then used to tabulate the obtained data. The analysis used straight lines drawn between the 'from' and 'to' legal sub-division (LSD) endpoints in order to represent pipelines on an Alberta township system (ATS) and identify connections between pipelines. Well connections were established based on matching surface hole location and 'from' LSDs. Well production, composition, pressure, and temperature data were sourced and recorded as well attributes. XSL hierarchical computations were used to determine the production and composition properties of the commingled inflows. It was concluded that the corrosion assessment process can identify locations within the pipeline network where potential deadlegs branched off from flowing pipelines. 4 refs., 2 tabs., 2 figs.

  7. Voltage regulation in distribution networks with distributed generation

    Science.gov (United States)

    Blažič, B.; Uljanić, B.; Papič, I.

    2012-11-01

    The paper deals with the topic of voltage regulation in distribution networks with relatively high distributed energy resources (DER) penetration. The problem of voltage rise is described and different options for voltage regulation are given. The influence of DER on voltage profile and the effectiveness of the investigated solutions are evaluated by means of simulation in DIgSILENT. The simulated network is an actual distribution network in Slovenia with a relatively high penetration of distributed generation. Recommendations for voltage control in networks with DER penetration are given at the end.

  8. Big Data Perspective and Challenges in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Kashif Sultan

    2018-06-01

    Full Text Available With the development towards the next generation cellular networks, i.e., 5G, the focus has shifted towards meeting the higher data rate requirements, potential of micro cells and millimeter wave spectrum. The goals for next generation networks are very high data rates, low latency and handling of big data. The achievement of these goals definitely require newer architecture designs, upgraded technologies with possible backward support, better security algorithms and intelligent decision making capability. In this survey, we identify the opportunities which can be provided by 5G networks and discuss the underlying challenges towards implementation and realization of the goals of 5G. This survey also provides a discussion on the recent developments made towards standardization, the architectures which may be potential candidates for deployment and the energy concerns in 5G networks. Finally, the paper presents a big data perspective and the potential of machine learning for optimization and decision making in 5G networks.

  9. 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

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

    DEFF Research Database (Denmark)

    Brambini-Pedersen, Jan Vang; Jensen, Kent W; 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......Much attention has been paid to analysing the determinants of the economic development in the different generations of Asian tiger economies. This stream of research has provided valuable insights on the particular generational challenges, the tigers face in implementing successful catching up...

  11. 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.

  12. MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks

    OpenAIRE

    Ding, Wenhao; He, Liang

    2018-01-01

    In this paper, we propose an enhanced triplet method that improves the encoding process of embeddings by jointly utilizing generative adversarial mechanism and multitasking optimization. We extend our triplet encoder with Generative Adversarial Networks (GANs) and softmax loss function. GAN is introduced for increasing the generality and diversity of samples, while softmax is for reinforcing features about speakers. For simplification, we term our method Multitasking Triplet Generative Advers...

  13. 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.

  14. 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

  15. Learning Orthographic Structure With Sequential Generative Neural Networks.

    Science.gov (United States)

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

    2016-04-01

    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 connectionist modeling. Here, we investigated a sequential version of the restricted Boltzmann machine (RBM), a stochastic recurrent neural network that extracts high-order structure from sensory data through unsupervised generative learning and can encode contextual information in the form of internal, distributed representations. We assessed whether this type of network can extract the orthographic structure of English monosyllables by learning a generative model of the letter sequences forming a word training corpus. We show that the network learned an accurate probabilistic model of English graphotactics, which can be used to make predictions about the letter following a given context as well as to autonomously generate high-quality pseudowords. The model was compared to an extended version of simple recurrent networks, augmented with a stochastic process that allows autonomous generation of sequences, and to non-connectionist probabilistic models (n-grams and hidden Markov models). We conclude that sequential RBMs and stochastic simple recurrent networks are promising candidates for modeling cognition in the temporal domain. Copyright © 2015 Cognitive Science Society, Inc.

  16. 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

    This paper contributes on presenting a step towards the realization of Carrier Ethernet control plane based on the next generation network (NGN). Specifically, transport MPLS (T-MPLS) is taken as the transport technology in Carrier Ethernet. It begins with providing an overview of the evolving...... architecture of the next generation network (NGN). As an essential candidate among the NGN transport technologies, the definition of Carrier Ethernet (CE) is also introduced here. The second part of this paper depicts the contribution on the T-MPLS based Carrier Ethernet network with control plane based on NGN...... at illustrating the improvement of the Carrier Ethernet network with the NGN control plane....

  17. Intrinsically-generated fluctuating activity in excitatory-inhibitory networks

    Science.gov (United States)

    Mastrogiuseppe, Francesca; Ostojic, Srdjan

    2017-01-01

    Recurrent networks of non-linear units display a variety of dynamical regimes depending on the structure of their synaptic connectivity. A particularly remarkable phenomenon is the appearance of strongly fluctuating, chaotic activity in networks of deterministic, but randomly connected rate units. How this type of intrinsically generated fluctuations appears in more realistic networks of spiking neurons has been a long standing question. To ease the comparison between rate and spiking networks, recent works investigated the dynamical regimes of randomly-connected rate networks with segregated excitatory and inhibitory populations, and firing rates constrained to be positive. These works derived general dynamical mean field (DMF) equations describing the fluctuating dynamics, but solved these equations only in the case of purely inhibitory networks. Using a simplified excitatory-inhibitory architecture in which DMF equations are more easily tractable, here we show that the presence of excitation qualitatively modifies the fluctuating activity compared to purely inhibitory networks. In presence of excitation, intrinsically generated fluctuations induce a strong increase in mean firing rates, a phenomenon that is much weaker in purely inhibitory networks. Excitation moreover induces two different fluctuating regimes: for moderate overall coupling, recurrent inhibition is sufficient to stabilize fluctuations; for strong coupling, firing rates are stabilized solely by the upper bound imposed on activity, even if inhibition is stronger than excitation. These results extend to more general network architectures, and to rate networks receiving noisy inputs mimicking spiking activity. Finally, we show that signatures of the second dynamical regime appear in networks of integrate-and-fire neurons. PMID:28437436

  18. 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.

  19. 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.

  20. 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.

  1. Satellite communications for the next generation telecommunication services and networks

    Science.gov (United States)

    Chitre, D. M.

    1991-01-01

    Satellite communications can play an important role in provisioning the next-generation telecommunication services and networks, provided the protocols specifying these services and networks are satellite-compatible and the satellite subnetworks, consisting of earth stations interconnected by the processor and the switch on board the satellite, interwork effectively with the terrestrial networks. The specific parameters and procedures of frame relay and broadband integrated services digital network (B-ISDN) protocols which are impacted by a satellite delay. Congestion and resource management functions for frame relay and B-ISDN are discussed in detail, describing the division of these functions between earth stations and on board the satellite. Specific onboard and ground functions are identified as potential candidates for their implementation via neural network technology.

  2. 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.

  3. 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.

  4. Interaction Networks: Generating High Level Hints Based on Network Community Clustering

    Science.gov (United States)

    Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

    2012-01-01

    We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

  5. 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.

  6. 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.

  7. Generative adversarial networks for anomaly detection in images

    OpenAIRE

    Batiste Ros, Guillem

    2018-01-01

    Anomaly detection is used to identify abnormal observations that don t follow a normal pattern. Inthis work, we use the power of Generative Adversarial Networks in sampling from image distributionsto perform anomaly detection with images and to identify local anomalous segments within thisimages. Also, we explore potential application of this method to support pathological analysis ofbiological tissues

  8. Facilitate generation connections on Orkney by automatic distribution network management

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2004-07-01

    This report summarises the results of a study assessing the capability and limitations of the Orkney Network under a variety of conditions of demand, generation connections, network configuration, and reactive compensation). A conceptual active management scheme (AMS) suitable for the conditions on Orkney is developed and evaluated. Details are given of a proposed framework for the design and evaluation of future active management schemes, logic control sequences for managed generation units, and a proposed evaluation method for the active management scheme. Implications of introducing the proposed AMS are examined, and the commercial aspects of an AMS and system security are considered. The existing Orkney network is described; and an overview of the SHEPDL (Scottish Hydro Electric Power Distribution Ltd.) SCADA system is presented with a discussion of AMS identification, selection, and development.

  9. 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.

  10. Distribution network planning method considering distributed generation for peak cutting

    International Nuclear Information System (INIS)

    Ouyang Wu; Cheng Haozhong; Zhang Xiubin; Yao Liangzhong

    2010-01-01

    Conventional distribution planning method based on peak load brings about large investment, high risk and low utilization efficiency. A distribution network planning method considering distributed generation (DG) for peak cutting is proposed in this paper. The new integrated distribution network planning method with DG implementation aims to minimize the sum of feeder investments, DG investments, energy loss cost and the additional cost of DG for peak cutting. Using the solution techniques combining genetic algorithm (GA) with the heuristic approach, the proposed model determines the optimal planning scheme including the feeder network and the siting and sizing of DG. The strategy for the site and size of DG, which is based on the radial structure characteristics of distribution network, reduces the complexity degree of solving the optimization model and eases the computational burden substantially. Furthermore, the operation schedule of DG at the different load level is also provided.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Loss optimization in distribution networks with distributed generation

    DEFF Research Database (Denmark)

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

    2017-01-01

    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...... 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...... penetration are created to test the proposed algorithm. It is tested in a benchmark medium voltage network to show the effectiveness and performance of the algorithm. Results obtained are found to be encouraging for radial distribution system. It shows that we can reduce the power loss by more than 30% using...

  20. 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.

  1. User-generated content curation with deep convolutional neural networks

    OpenAIRE

    Tous Liesa, Rubén; Wust, Otto; Gómez, Mauro; Poveda, Jonatan; Elena, Marc; Torres Viñals, Jordi; Makni, Mouna; Ayguadé Parra, Eduard

    2016-01-01

    In this paper, we report a work consisting in using deep convolutional neural networks (CNNs) for curating and filtering photos posted by social media users (Instagram and Twitter). The final goal is to facilitate searching and discovering user-generated content (UGC) with potential value for digital marketing tasks. The images are captured in real time and automatically annotated with multiple CNNs. Some of the CNNs perform generic object recognition tasks while others perform what we call v...

  2. Generation and prediction of time series by a neural network

    International Nuclear Information System (INIS)

    Eisenstein, E.; Kanter, I.; Kessler, D.A.; Kinzel, W.

    1995-01-01

    Generation and prediction of time series are analyzed for the case of a bit generator: a perceptron where in each time step the input units are shifted one bit to the right with the state of the leftmost input unit set equal to the output unit in the previous time step. The long-time dynamical behavior of the bit generator consists of cycles whose typical period scales polynomially with the size of the network and whose spatial structure is periodic with a typical finite wavelength. The generalization error on a cycle is zero for a finite training set, and global dynamical behaviors can also be learned in a finite time. Hence, a projection of a rule can be learned in a finite time

  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. Pinning Synchronization of Linear Complex Coupling Synchronous Generators Network of Hydroelectric Generating Set

    Directory of Open Access Journals (Sweden)

    Xuefei Wu

    2014-01-01

    Full Text Available A novel linear complex system for hydroturbine-generator sets in multimachine power systems is suggested in this paper and synchronization of the power-grid networks is studied. The advanced graph theory and stability theory are combined to solve the problem. Here we derive a sufficient condition under which the synchronous state of power-grid networks is stable in disturbance attenuation. Finally, numerical simulations are provided to illustrate the effectiveness of the results by the IEEE 39 bus system.

  5. 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.

  6. 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.

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

    DEFF Research Database (Denmark)

    Schou, Saowanee; Olesen, Henning

    2005-01-01

    This paper proposes a novel conceptual mechanism for detecting the location of a mobile user on next generation wireless networks. This mechanism can provide location information of a mobile user at different levels of accuracy, by applying the movement detection mechanism of Mobile IPv6 at both...... macro- and micromobility level. In this scheme, an intradomain mobility management protocol (IDMP) is applied to manage the location of the mobile terminal. The mobile terminal needs two care-of addresses, a global care-of address (GCoA) and a local care-of address (LCoA). The current location...... 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. 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. Artificial earthquake record generation using cascade neural network

    Directory of Open Access Journals (Sweden)

    Bani-Hani Khaldoon A.

    2017-01-01

    Full Text Available This paper presents the results of using artificial neural networks (ANN in an inverse mapping problem for earthquake accelerograms generation. This study comprises of two parts: 1-D site response analysis; performed for Dubai Emirate at UAE, where eight earthquakes records are selected and spectral matching are performed to match Dubai response spectrum using SeismoMatch software. Site classification of Dubai soil is being considered for two classes C and D based on shear wave velocity of soil profiles. Amplifications factors are estimated to quantify Dubai soil effect. Dubai’s design response spectra are developed for site classes C & D according to International Buildings Code (IBC -2012. In the second part, ANN is employed to solve inverse mapping problem to generate time history earthquake record. Thirty earthquakes records and their design response spectrum with 5% damping are used to train two cascade forward backward neural networks (ANN1, ANN2. ANN1 is trained to map the design response spectrum to time history and ANN2 is trained to map time history records to the design response spectrum. Generalized time history earthquake records are generated using ANN1 for Dubai’s site classes C and D, and ANN2 is used to evaluate the performance of ANN1.

  10. Neural network based daily precipitation generator (NNGEN-P)

    Energy Technology Data Exchange (ETDEWEB)

    Boulanger, Jean-Philippe [LODYC, UMR CNRS/IRD/UPMC, Paris (France); University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Martinez, Fernando; Segura, Enrique C. [University of Buenos Aires, Departamento de Computacion, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina); Penalba, Olga [University of Buenos Aires, Departamento de Ciencias de la Atmosfera y los Oceanos, Facultad de Ciencias Exactas y Naturales, Buenos Aires (Argentina)

    2007-02-15

    Daily weather generators are used in many applications and risk analyses. The present paper explores the potential of neural network architectures to design daily weather generator models. Focusing this first paper on precipitation, we design a collection of neural networks (multi-layer perceptrons in the present case), which are trained so as to approximate the empirical cumulative distribution (CDF) function for the occurrence of wet and dry spells and for the precipitation amounts. This approach contributes to correct some of the biases of the usual two-step weather generator models. As compared to a rainfall occurrence Markov model, NNGEN-P represents fairly well the mean and standard deviation of the number of wet days per month, and it significantly improves the simulation of the longest dry and wet periods. Then, we compared NNGEN-P to three parametric distribution functions usually applied to fit rainfall cumulative distribution functions (Gamma, Weibull and double-exponential). A data set of 19 Argentine stations was used. Also, data corresponding to stations in the United States, in Europe and in the Tropics were included to confirm the results. One of the advantages of NNGEN-P is that it is non-parametric. Unlike other parametric function, which adapt to certain types of climate regimes, NNGEN-P is fully adaptive to the observed cumulative distribution functions, which, on some occasions, may present complex shapes. On-going works will soon produce an extended version of NNGEN to temperature and radiation. (orig.)

  11. Advanced optical components for next-generation photonic networks

    Science.gov (United States)

    Yoo, S. J. B.

    2003-08-01

    Future networks will require very high throughput, carrying dominantly data-centric traffic. The role of Photonic Networks employing all-optical systems will become increasingly important in providing scalable bandwidth, agile reconfigurability, and low-power consumptions in the future. In particular, the self-similar nature of data traffic indicates that packet switching and burst switching will be beneficial in the Next Generation Photonic Networks. While the natural conclusion is to pursue Photonic Packet Switching and Photonic Burst Switching systems, there are significant challenges in realizing such a system due to practical limitations in optical component technologies. Lack of a viable all-optical memory technology will continue to drive us towards exploring rapid reconfigurability in the wavelength domain. We will introduce and discuss the advanced optical component technologies behind the Photonic Packet Routing system designed and demonstrated at UC Davis. The system is capable of packet switching and burst switching, as well as circuit switching with 600 psec switching speed and scalability to 42 petabit/sec aggregated switching capacity. By utilizing a combination of rapidly tunable wavelength conversion and a uniform-loss cyclic frequency (ULCF) arrayed waveguide grating router (AWGR), the system is capable of rapidly switching the packets in wavelength, time, and space domains. The label swapping module inside the Photonic Packet Routing system containing a Mach-Zehnder wavelength converter and a narrow-band fiber Bragg-grating achieves all-optical label swapping with optical 2R (potentially 3R) regeneration while maintaining optical transparency for the data payload. By utilizing the advanced optical component technologies, the Photonic Packet Routing system successfully demonstrated error-free, cascaded, multi-hop photonic packet switching and routing with optical-label swapping. This paper will review the advanced optical component technologies

  12. 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...

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

  18. StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

    OpenAIRE

    Zhang, Han; Xu, Tao; Li, Hongsheng; Zhang, Shaoting; Wang, Xiaogang; Huang, Xiaolei; Metaxas, Dimitris

    2017-01-01

    Although Generative Adversarial Networks (GANs) have shown remarkable success in various tasks, they still face challenges in generating high quality images. In this paper, we propose Stacked Generative Adversarial Networks (StackGAN) aiming at generating high-resolution photo-realistic images. First, we propose a two-stage generative adversarial network architecture, StackGAN-v1, for text-to-image synthesis. The Stage-I GAN sketches the primitive shape and colors of the object based on given...

  19. 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.

  20. 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

  1. 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

  2. Dynamic simulation of a steam generator by neural networks

    International Nuclear Information System (INIS)

    Masini, R.; Padovani, E.; Ricotti, M.E.; Zio, E.

    1999-01-01

    Numerical simulation by computers of the dynamic evolution of complex systems and components is a fundamental phase of any modern engineering design activity. This is of particular importance for risk-based design projects which require that the system behavior be analyzed under several and often extreme conditions. The traditional methods of simulation typically entail long, iterative, processes which lead to large simulation times, often exceeding the transients real time. Artificial neural networks (ANNs) may be exploited in this context, their advantages residing mainly in the speed of computation, in the capability of generalizing from few examples, in the robustness to noisy and partially incomplete data and in the capability of performing empirical input-output mapping without complete knowledge of the underlying physics. In this paper we present a novel approach to dynamic simulation by ANNs based on a superposition scheme in which a set of networks are individually trained, each one to respond to a different input forcing function. The dynamic simulation of a steam generator is considered as an example to show the potentialities of this tool and to point out the difficulties and crucial issues which typically arise when attempting to establish an efficient neural network simulator. The structure of the networks system is such to feedback, at each time step, a portion of the past evolution of the transient and this allows a good reproduction of also non-linear dynamic behaviors. A nice characteristic of the approach is that the modularization of the training reduces substantially its burden and gives this neural simulation tool a nice feature of transportability. (orig.)

  3. Modeling of steam generator in nuclear power plant using neural network ensemble

    International Nuclear Information System (INIS)

    Lee, S. K.; Lee, E. C.; Jang, J. W.

    2003-01-01

    Neural network is now being used in modeling the steam generator is known to be difficult due to the reverse dynamics. However, Neural network is prone to the problem of overfitting. This paper investigates the use of neural network combining methods to model steam generator water level and compares with single neural network. The results show that neural network ensemble is effective tool which can offer improved generalization, lower dependence of the training set and reduced training time

  4. 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.

  5. 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.

  6. Impact of distributed generation units with power electronic converters on distribution network protection

    NARCIS (Netherlands)

    Morren, J.; Haan, de S.W.H.

    2008-01-01

    An increasing number of distributed generation units (DG units) are connected to the distribution network. These generators affect the operation and coordination of the distribution network protection. The influence from DG units that are coupled to the network with a power electronic converter

  7. 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 Flexible, open source network emulation tools can provide network researchers with significant benefits regarding network behaviour and performance. The evaluation of these networks can benefit greatly from the integration of realistic, network...

  8. 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.

  9. 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%.

  10. 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 ...

  11. 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 ...

  12. 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.

  13. Pythoscape: A framework for generation of large protein similarity networks

    OpenAIRE

    Babbitt, Patricia; Barber, AE; Babbitt, PC

    2012-01-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among pr

  14. 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.

  15. Persona: Network Layer Anonymity and Accountability for Next Generation Internet

    Science.gov (United States)

    Mallios, Yannis; Modi, Sudeep; Agarwala, Aditya; Johns, Christina

    Individual privacy has become a major concern, due to the intrusive nature of the services and websites that collect increasing amounts of private information. One of the notions that can lead towards privacy protection is that of anonymity. Unfortunately, anonymity can also be maliciously exploited by attackers to hide their actions and identity. Thus some sort of accountability is also required. The current Internet has failed to provide both properties, as anonymity techniques are difficult to fully deploy and thus are easily attacked, while the Internet provides limited level of accountability. The Next Generation Internet (NGI) provides us with the opportunity to examine how these conflicting properties could be efficiently applied and thus protect users’ privacy while holding malicious users accountable. In this paper we present the design of a scheme, called Persona that can provide anonymity and accountability in the network layer of NGI. More specifically, our design requirements are to combine these two conflicting desires in a stateless manner within routers. Persona allows users to choose different levels of anonymity, while it allows the discovery of malicious nodes.

  16. 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.

  17. ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

    Directory of Open Access Journals (Sweden)

    Zhihuai Xiao

    2015-01-01

    Full Text Available Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO- initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the frequency components of the hydroturbine generating unit vibration signals are used as feature vectors for wavelet neural network training to realize mapping relationship from vibration features to fault types. A real vibration fault diagnosis case result of a hydroturbine generating unit shows that the proposed method has faster convergence speed and stronger generalization ability than the traditional wavelet neural network and ACO wavelet neural network. Thus it can provide an effective solution for online vibration fault diagnosis of a hydroturbine generating unit.

  18. Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2009-01-01

    A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

  19. 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.

  20. Next Generation Access Network Deployment in Croatia: Optical Access Networks and Current IoT/5G Status

    Science.gov (United States)

    Breskovic, Damir; Sikirica, Mladen; Begusic, Dinko

    2018-05-01

    This paper gives an overview and background of optical access network deployment in Croatia. Optical access network development in Croatia has been put into a global as well as in the European Union context. All the challenges and the driving factors for optical access networks deployment are considered. Optical access network architectures that have been deployed by most of the investors in Croatian telecommunication market are presented, as well as the architectures that are in early phase of deployment. Finally, an overview on current status of mobile networks of the fifth generation and Internet of Things is given.

  1. 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.

  2. Network investments and the integration of distributed generation: Regulatory recommendations for the Dutch electricity industry

    International Nuclear Information System (INIS)

    Niesten, Eva

    2010-01-01

    An increase in the distributed generation of electricity 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, average benchmarking and a 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 system operators 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 regulations, 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 generation.

  3. 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.

  4. 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

  5. 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

  6. 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

  7. 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…

  8. Generation of arbitrary two-point correlated directed networks with given modularity

    International Nuclear Information System (INIS)

    Zhou Jie; Xiao Gaoxi; Wong, Limsoon; Fu Xiuju; Ma, Stefan; Cheng, Tee Hiang

    2010-01-01

    In this Letter, we introduce measures of correlation in directed networks and develop an efficient algorithm for generating directed networks with arbitrary two-point correlation. Furthermore, a method is proposed for adjusting community structure in directed networks without changing the correlation. Effectiveness of both methods is verified by numerical results.

  9. 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...

  10. VIGAN: Missing View Imputation with Generative Adversarial Networks.

    Science.gov (United States)

    Shang, Chao; Palmer, Aaron; Sun, Jiangwen; Chen, Ko-Shin; Lu, Jin; Bi, Jinbo

    2017-01-01

    In an era when big data are becoming the norm, there is less concern with the quantity but more with the quality and completeness of the data. In many disciplines, data are collected from heterogeneous sources, resulting in multi-view or multi-modal datasets. The missing data problem has been challenging to address in multi-view data analysis. Especially, when certain samples miss an entire view of data, it creates the missing view problem. Classic multiple imputations or matrix completion methods are hardly effective here when no information can be based on in the specific view to impute data for such samples. The commonly-used simple method of removing samples with a missing view can dramatically reduce sample size, thus diminishing the statistical power of a subsequent analysis. In this paper, we propose a novel approach for view imputation via generative adversarial networks (GANs), which we name by VIGAN. This approach first treats each view as a separate domain and identifies domain-to-domain mappings via a GAN using randomly-sampled data from each view, and then employs a multi-modal denoising autoencoder (DAE) to reconstruct the missing view from the GAN outputs based on paired data across the views. Then, by optimizing the GAN and DAE jointly, our model enables the knowledge integration for domain mappings and view correspondences to effectively recover the missing view. Empirical results on benchmark datasets validate the VIGAN approach by comparing against the state of the art. The evaluation of VIGAN in a genetic study of substance use disorders further proves the effectiveness and usability of this approach in life science.

  11. The effect of increasing levels of embedded generation on the distribution network. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Collinson, A; Earp, G K; Howson, D; Owen, R D; Wright, A J

    1999-10-01

    This report was commissioned as part of the EA Technology Strategic Technology Programme under guidance of the Module 5 (Embedded Generation) Steering Group. This report aims to provide information related to the distribution and supply of electricity in the context of increasing levels of embedded generation. There is a brief description of the operating environment within which electricity companies in the UK must operate. Technical issues related to the connection of generation to the existing distribution infrastructure are highlighted and the design philosophy adopted by network designers in accommodating applications for the connection of embedded generation to the network is discussed. The effects embedded generation has on the network and the issues raised are presented as many of them present barriers to the connection of embedded generators. The final chapters cover the forecast of required connection to 2010 and solutions to restrictions preventing the connection of more embedded generation to the network. (author)

  12. 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.

  13. Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation

    OpenAIRE

    Yang, Shan; Tong, Xiangqian

    2016-01-01

    Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverte...

  14. Pythoscape: a framework for generation of large protein similarity networks.

    Science.gov (United States)

    Barber, Alan E; Babbitt, Patricia C

    2012-11-01

    Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.

  15. ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

    OpenAIRE

    Xiao, Zhihuai; He, Xinying; Fu, Xiangqian; Malik, O. P.

    2015-01-01

    Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO-) initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the fr...

  16. The Influence of Social Network on Consumer Purchase Intention of Young Generation in Manado

    OpenAIRE

    Tumewu, Ferdinand; Korompis, Prycilia Novita

    2014-01-01

    Social network now is very prevalent in the society. Today, many small enterprises sell and promote their product through social network and also many people are likely to make an online purchase especially for young generation. Social network is play a vital role in increasing someone intention to buy a product. This research is designed because there are some factor in social network that influence someone purchase intention. The original purpose of this research is to know the influence of...

  17. 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.

  18. 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

  19. 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...

  20. 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.

  1. Efficient Key Generation and Distribution on Wireless Sensor Networks

    OpenAIRE

    Ariño Pérez, Víctor

    2013-01-01

    Projecte realitzat en el marc d’un programa de mobilitat amb la KTH Electrical Engineering [ANGLÈS] Wireless Sensor Networks have become popular during the last years. The introduction of IPv6 which broadened the address space available, IEEE802.15.4 and adaptation layers such as 6loWPAN have allowed the intercommunication of small devices. These networks are useful in many scenarios such as civil monitoring, mining, battlefield operations, as well as consumer products. Hence, practical se...

  2. GLEON: An Example of Next Generation Network Biogeoscience

    Science.gov (United States)

    Weathers, K. C.; Hanson, P. C.

    2014-12-01

    When we think of sensor networks, we often focus on hardware development and deployments and the resulting data and synthesis. Yet, for networks that cross institutional boundaries, such as distributed federations of observatories, people are the critical network resource. They establish the linkages and enable access to and interpretation of the data. In the Global Lake Ecological Observatory Network (GLEON), we found that careful integration of three networks --people, hardware, and data--was essential to providing an effective research environment. Accomplishing this integration is not trivial and requires a shared vision among members, explicit attention to the emerging tenets of the science of team science, and training of scientists at all career stages. In GLEON these efforts have resulted in scientific inferences covering new scales, crossing broad ecosystem gradients, and capturing important environmental events. Network-level capital has been increased by the deployment of instrumented buoys, the creation of new data sets and publicly available models, and new ways to synthesize and analyze high frequency data. The formation of international teams of scientists is essential to these goals. Our approach unites a diverse membership in GLEON-style team science, with emphasis on training and engagement of graduate students while creating knowledge. Examples of the bottom-up scientific output from GLEON include creating and confronting models using high frequency data from sensor networks; interpreting output from biological sensors (e.g., algal pigment sensors) as predictors for water quality indices such as water clarity; and understanding the relationship between occasional, highly noxious algal blooms and fluorometric measurements of pigments from sensor networks. Numerical simulation models are not adequate for predicting highly skewed distributions of phytoplankton in eutrophic lakes, suggesting that our fundamental understanding of phytoplankton

  3. A review on the impact of embedded generation to network fault level

    Science.gov (United States)

    Yahaya, M. S.; Basar, M. F.; Ibrahim, Z.; Nasir, M. N. N.; Lada, M. Y.; Bukhari, W. M.

    2015-05-01

    The line of Embedded Generation (EG) in power systems especially for renewable energy has increased markedly in recent years. The interconnection of EG has a technical impact which needs to considered. One of the technical challenges faced by the Distribution Network Operator (DNO) is the network fault level. In this paper, the different methods of interconnection with and without EG on the network is analyze by looking at the impact of network fault level. This comparative study made to determine the most effective method to reduce fault level or fault current. This paper will gives basic understanding on the fault level effect when synchronous generator connected to network by different method of interconnection. A three phase fault is introduced at one network bus bar. By employ it to simple network configuration of network configurations which is normal interconnection and splitting network connection with and without EG, the fault level has been simulated and analyzed. Developing the network model by using PSS-Viper™ software package, the fault level for both networks will be showed and the difference is defines. From the review, network splitting was found the best interconnection method and greatest potential for reducing the fault level in the network.

  4. Network Edge Intelligence for the Emerging Next-Generation Internet

    Directory of Open Access Journals (Sweden)

    Salekul Islam

    2010-11-01

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

  5. 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.

  6. 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

  7. 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

  8. Automatic theory generation from analyst text files using coherence networks

    Science.gov (United States)

    Shaffer, Steven C.

    2014-05-01

    This paper describes a three-phase process of extracting knowledge from analyst textual reports. Phase 1 involves performing natural language processing on the source text to extract subject-predicate-object triples. In phase 2, these triples are then fed into a coherence network analysis process, using a genetic algorithm optimization. Finally, the highest-value sub networks are processed into a semantic network graph for display. Initial work on a well- known data set (a Wikipedia article on Abraham Lincoln) has shown excellent results without any specific tuning. Next, we ran the process on the SYNthetic Counter-INsurgency (SYNCOIN) data set, developed at Penn State, yielding interesting and potentially useful results.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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.

  15. Transient stability of distributed generation in MV-ring networks

    NARCIS (Netherlands)

    Coster, E.J.; Myrzik, J.M.A.; Kling, W.L.

    2008-01-01

    Due to the increase of distributed generation (DG) in the future it can become important to keep DG connected to the grid in order to maintain balance between consumed and generated electrical power. Keeping DG-units connected to the grid during a disturbance, the dynamic behavior of the DG-units

  16. 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...

  17. 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.

  18. Next generation network performance management: a business perspective

    CSIR Research Space (South Africa)

    Harding, C

    2010-08-01

    Full Text Available multitude of transport and access technologies on almost any user device. The most important and integral component of the NGCN NGN Architectural Framework is the physical and logical management of the network elements and services to provide maximum utility...

  19. 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...

  20. 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 ...

  1. IMECCHI-DATANETWORK: empowering knowledge generation through international data network

    Directory of Open Access Journals (Sweden)

    Marie Annick Le Pogam

    2017-04-01

    Within the IMECCHI-DATANETWORK initiative, databases from various countries will be locally converted in a CDM which will facilitate study replication in a distributed fashion while granting interoperability across coding systems. Through such international data networks, data are empowered for creating results which are generalizable to multiple countries. Cross-border data sharing and international comparisons are also facilitated.

  2. 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 ...

  3. Life cycle assessment of second generation (2G) and third generation (3G) mobile phone networks.

    Science.gov (United States)

    Scharnhorst, Wolfram; Hilty, Lorenz M; Jolliet, Olivier

    2006-07-01

    The environmental performance of presently operated GSM and UMTS networks was analysed concentrating on the environmental effects of the End-of-Life (EOL) phase using the Life Cycle Assessment (LCA) method. The study was performed based on comprehensive life cycle inventory and life cycle modelling. The environmental effects were quantified using the IMPACT2002+ method. Based on technological forecasts, the environmental effects of forthcoming mobile telephone networks were approximated. The results indicate that a parallel operation of GSM and UMTS networks is environmentally detrimental and the transition phase should be kept as short as possible. The use phase (i.e. the operation) of the radio network components account for a large fraction of the total environmental impact. In particular, there is a need to lower the energy consumption of those network components. Seen in relation to each other, UMTS networks provide an environmentally more efficient mobile communication technology than GSM networks. In assessing the EOL phase, recycling the electronic scrap of mobile phone networks was shown to have clear environmental benefits. Under the present conditions, material recycling could help lower the environmental impact of the production phase by up to 50%.

  4. 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.

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

    International Nuclear Information System (INIS)

    Zamora-Lopez, Gorka; Kurths, Juergen; Zhou Changsong; Zlatic, Vinko

    2008-01-01

    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

  6. 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

  7. 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....

  8. Optimal placement of distributed generation in distribution networks

    African Journals Online (AJOL)

    user

    The objective of power system operation is to meet the demand at all the locations ... The traditional electric power generation systems utilize the conventional energy resources, such as fossil ..... Power Distribution Planning Reference Book.

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

    KAUST Repository

    Zhou, Bingpu; Xu, Wei; Wang, Cong; Chau, Yeungyeung; Zeng, Xiping; Zhang, Xixiang; Shen, Rong; Wen, Weijia

    2014-01-01

    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

  10. 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

  11. 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.

  12. 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

  13. 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…

  14. 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.

  15. 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...

  16. 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…

  17. 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

  18. Distributed generation connected to the local network - a guide

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    This guide provides advice to the developers and operators of small distributed generation plant (including microgenerators) in the UK about the practical issues associated with connecting their plant and trading their output. Particular attention is given to sales revenues and how to access these revenue streams, including the mechanisms for purchasing Renewable Obligation Certificates (ROCs). The guide clarifies key terms, explains the wholesale trading system and provides an overview of sales opportunities (including ROCs and Levy Exemption Certificates (LECs)). Requirements on small distributed generation (including licensing, claiming class exemptions and metering) are described and the commercial aspects of connection (including the recent reduction in the barriers to connection) examined. Microgeneration (ie generators below 10 kW) issues are covered in their own chapter. The six appendices contain: background information about the industry; a list of purchasers of electricity from small distributed generators; descriptions of the generation, transmission and supply industries; information about industry standards and their governance; the role of government departments and institutions; and a glossary and other links.

  19. 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.

  20. Embedded generation: issues arising in network charging and supply

    International Nuclear Information System (INIS)

    1999-01-01

    This study has been commissioned by ETSU, as part of the DTI's New and Renewable Energy Commercialisation programme, with the intention of informing the debate about the appropriate basis for transmission and distribution charges for, and supply of electricity by, Embedded Generators (EGs). (Author)

  1. 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

  2. Embedded generation: issues arising in network charging and supply

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1999-07-01

    This study has been commissioned by ETSU, as part of the DTI's New and Renewable Energy Commercialisation programme, with the intention of informing the debate about the appropriate basis for transmission and distribution charges for, and supply of electricity by, Embedded Generators (EGs). (Author)

  3. 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…

  4. Column generation algorithms for virtual network embedding in flexi-grid optical networks.

    Science.gov (United States)

    Lin, Rongping; Luo, Shan; Zhou, Jingwei; Wang, Sheng; Chen, Bin; Zhang, Xiaoning; Cai, Anliang; Zhong, Wen-De; Zukerman, Moshe

    2018-04-16

    Network virtualization provides means for efficient management of network resources by embedding multiple virtual networks (VNs) to share efficiently the same substrate network. Such virtual network embedding (VNE) gives rise to a challenging problem of how to optimize resource allocation to VNs and to guarantee their performance requirements. In this paper, we provide VNE algorithms for efficient management of flexi-grid optical networks. We provide an exact algorithm aiming to minimize the total embedding cost in terms of spectrum cost and computation cost for a single VN request. Then, to achieve scalability, we also develop a heuristic algorithm for the same problem. We apply these two algorithms for a dynamic traffic scenario where many VN requests arrive one-by-one. We first demonstrate by simulations for the case of a six-node network that the heuristic algorithm obtains very close blocking probabilities to exact algorithm (about 0.2% higher). Then, for a network of realistic size (namely, USnet) we demonstrate that the blocking probability of our new heuristic algorithm is about one magnitude lower than a simpler heuristic algorithm, which was a component of an earlier published algorithm.

  5. 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

  6. Real Time Synchronization of Live Broadcast Streams with User Generated Content and Social Network Streams

    NARCIS (Netherlands)

    Stokking, H.M.; Kaptein, A.M.; Veenhuizen, A.T.; Spitters4, M.M.; Niamut, O.A.

    2013-01-01

    This paper describes the work in the FP7 STEER project on augmenting a live broadcast with live user generated content. This user generated content consists of both video content, captured with mobile devices, and social network content, such as Facebook or Twitter messages. To enable multi-source

  7. Securing Networks from Modern Threats using Next Generation Firewalls

    OpenAIRE

    Delgiusto, Valter

    2016-01-01

    Classic firewalls have long been unable to cope with modern threats that ordinary Internet users are exposed to. This thesis discusses their successors - the next-generation firewalls. The first part of the thesis describes modern threats and attacks. We described in detail the DoS and APT attacks, which are among the most frequent and which may cause most damage to the system under attack. Then we explained the theoretical basics of firewalls and described the functionalities of next gen...

  8. Network integration of distributed generation: international research and development

    Energy Technology Data Exchange (ETDEWEB)

    Watson, J.

    2003-07-01

    This report provides information on privately and publicly funded research and development programmes in distributed generation (DG) in the USA, the European Union and Japan. Protection systems for the installation of DG, power electronics for the connection of DG to electricity distribution systems, reliability modelling, power quality issues, connection standards, and simulation and computer modelling are examined. The relevance of the programmes to the UK is considered.

  9. Generation of Complex Karstic Conduit Networks with a Hydro-chemical Model

    Science.gov (United States)

    De Rooij, R.; Graham, W. D.

    2016-12-01

    The discrete-continuum approach is very well suited to simulate flow and solute transport within karst aquifers. Using this approach, discrete one-dimensional conduits are embedded within a three-dimensional continuum representative of the porous limestone matrix. Typically, however, little is known about the geometry of the karstic conduit network. As such the discrete-continuum approach is rarely used for practical applications. It may be argued, however, that the uncertainty associated with the geometry of the network could be handled by modeling an ensemble of possible karst conduit networks within a stochastic framework. We propose to generate stochastically realistic karst conduit networks by simulating the widening of conduits as caused by the dissolution of limestone over geological relevant timescales. We illustrate that advanced numerical techniques permit to solve the non-linear and coupled hydro-chemical processes efficiently, such that relatively large and complex networks can be generated in acceptable time frames. Instead of specifying flow boundary conditions on conduit cells to recharge the network as is typically done in classical speleogenesis models, we specify an effective rainfall rate over the land surface and let model physics determine the amount of water entering the network. This is advantageous since the amount of water entering the network is extremely difficult to reconstruct, whereas the effective rainfall rate may be quantified using paleoclimatic data. Furthermore, we show that poorly known flow conditions may be constrained by requiring a realistic flow field. Using our speleogenesis model we have investigated factors that influence the geometry of simulated conduit networks. We illustrate that our model generates typical branchwork, network and anastomotic conduit systems. Flow, solute transport and water ages in karst aquifers are simulated using a few illustrative networks.

  10. Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation

    Directory of Open Access Journals (Sweden)

    Shan Yang

    2016-01-01

    Full Text Available Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverter based distributed generation is proposed. The proposed method let the inverter based distributed generation be equivalent to Iθ bus, which makes it suitable to calculate the power flow of distribution network with a current limited inverter based distributed generation. And the low voltage ride through capability of inverter based distributed generation can be considered as well in this paper. Finally, some tests of power flow and short circuit current calculation are performed on a 33-bus distribution network. The calculated results from the proposed method in this paper are contrasted with those by the traditional method and the simulation method, whose results have verified the effectiveness of the integrated method suggested in this paper.

  11. Probabilistic generation of random networks taking into account information on motifs occurrence.

    Science.gov (United States)

    Bois, Frederic Y; Gayraud, Ghislaine

    2015-01-01

    Because of the huge number of graphs possible even with a small number of nodes, inference on network structure is known to be a challenging problem. Generating large random directed graphs with prescribed probabilities of occurrences of some meaningful patterns (motifs) is also difficult. We show how to generate such random graphs according to a formal probabilistic representation, using fast Markov chain Monte Carlo methods to sample them. As an illustration, we generate realistic graphs with several hundred nodes mimicking a gene transcription interaction network in Escherichia coli.

  12. 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

    as it has been used to generate game maps in previous productions [3, 4]. The diversity test showed the generated maps had a significantly greater diversity than the Perlin noise maps. Afterwards the heightmaps was converted to 3D maps in Unity3D. The 3D maps’ perceived realism and videogame usability...

  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

    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......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...... 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. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

    Science.gov (United States)

    Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

    2017-11-01

    In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

  15. 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.

  16. Network Characteristics and the Value of Collaborative User-Generated Content

    OpenAIRE

    Sam Ransbotham; Gerald C. Kane; Nicholas H. Lurie

    2012-01-01

    User-generated content is increasingly created through the collaborative efforts of multiple individuals. In this paper, we argue that the value of collaborative user-generated content is a function both of the direct efforts of its contributors and of its embeddedness in the content-contributor network that creates it. An analysis of Wikipedia's WikiProject Medicine reveals a curvilinear relationship between the number of distinct contributors to user-generated content and viewership. A two-...

  17. Software Defined Networking for Next Generation Converged Metro-Access Networks

    Science.gov (United States)

    Ruffini, M.; Slyne, F.; Bluemm, C.; Kitsuwan, N.; McGettrick, S.

    2015-12-01

    While the concept of Software Defined Networking (SDN) has seen a rapid deployment within the data center community, its adoption in telecommunications network has progressed slowly, although the concept has been swiftly adopted by all major telecoms vendors. This paper presents a control plane architecture for SDN-driven converged metro-access networks, developed through the DISCUS European FP7 project. The SDN-based controller architecture was developed in a testbed implementation targeting two main scenarios: fast feeder fiber protection over dual-homed Passive Optical Networks (PONs) and dynamic service provisioning over a multi-wavelength PON. Implementation details and results of the experiment carried out over the second scenario are reported in the paper, showing the potential of SDN in providing assured on-demand services to end-users.

  18. Toward the automated generation of genome-scale metabolic networks in the SEED.

    Science.gov (United States)

    DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron

    2007-04-26

    Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the

  19. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  20. Creating, generating and comparing random network models with NetworkRandomizer.

    Science.gov (United States)

    Tosadori, Gabriele; Bestvina, Ivan; Spoto, Fausto; Laudanna, Carlo; Scardoni, Giovanni

    2016-01-01

    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.

  1. 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

  2. New-generation security network with synergistic IP sensors

    Science.gov (United States)

    Peshko, Igor

    2007-09-01

    Global Dynamic Monitoring and Security Network (GDMSN) for real-time monitoring of (1) environmental and atmospheric conditions: chemical, biological, radiological and nuclear hazards, climate/man-induced catastrophe areas and terrorism threats; (2) water, soil, food chain quantifiers, and public health care; (3) large government/public/ industrial/ military areas is proposed. Each GDMSN branch contains stationary or mobile terminals (ground, sea, air, or space manned/unmanned vehicles) equipped with portable sensors. The sensory data are transferred via telephone, Internet, TV, security camera and other wire/wireless or optical communication lines. Each sensor is a self-registering, self-reporting, plug-and-play, portable unit that uses unified electrical and/or optical connectors and operates with IP communication protocol. The variant of the system based just on optical technologies cannot be disabled by artificial high-power radio- or gamma-pulses or sunbursts. Each sensor, being supplied with a battery and monitoring means, can be used as a separate portable unit. Military personnel, police officers, firefighters, miners, rescue teams, and nuclear power plant personnel may individually use these sensors. Terminals may be supplied with sensors essential for that specific location. A miniature "universal" optical gas sensor for specific applications in life support and monitoring systems was designed and tested. The sensor is based on the physics of absorption and/or luminescence spectroscopy. It can operate at high pressures and elevated temperatures, such as in professional and military diving equipment, submarines, underground shelters, mines, command stations, aircraft, space shuttles, etc. To enable this capability, the multiple light emitters, detectors and data processing electronics are located within a specially protected chamber.

  3. How Irish Political Parties are Using Social Networking Sites to Reach Generation Z: an Insight into a New Online Social Network in a Small Democracy

    OpenAIRE

    Lynch, Kevin; Hogan, John

    2016-01-01

    This study, using in-depth interviews and focus groups, examines perceptions of social networking sites as a means of communicating with Generation Z, from the perspectives of the major Irish political parties using these online resources and the perspective of their young target audience. There are two research questions: (1) How do political parties perceive social networking sites’ role in communicating with Generation Z? and (2) How do members of Generation Z perceive social networking si...

  4. 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...

  5. 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.

  6. 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.

  7. 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.

  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

    , 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...... 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...

  9. 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.

  10. 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

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

    Science.gov (United States)

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

    2015-01-01

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

  12. 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

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

    Science.gov (United States)

    2015-11-23

    P11035 (2014). [19] P. L. Krapivsky and S. Redner, Phys. Rev. E. 71, 036118 (2005). [20] M. O. Jackson and B. W. Rogers, Amer. Econ . Rev. 97, 890...P06004 (2010). [24] M. E. J. Newman, Networks: An Introduction (Oxford Univ. Press, Oxford, 2010). [25] P. J. Flory, Principles of Polymer Chemistry

  14. GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

    Science.gov (United States)

    Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

    2011-08-15

    Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

  15. 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.

  16. 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...... consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schrödinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks....

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

    International Nuclear Information System (INIS)

    Amaya, F; Cardenas, A; Tafur, I

    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 consider in the model the effect of distributed Raman amplification, used to extent the capacity and the reach of the optical link. In the model, we use the nonlinear Schroedinger equation with the purpose to obtain capacity limitations and design constrains of the next generation optical access networks.

  18. 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

  19. 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)

  20. Technical guide to the connection of generation to the distribution network

    Energy Technology Data Exchange (ETDEWEB)

    Jarrett, K.; Hedgecock, J.; Gregory, R.; Warham, T.

    2003-07-01

    This guide provides a 'route map' of the processes of getting a generation scheme connected to the network and is intended to help developers of any form of distributed generation connected to the UK's local electricity networks, eg: renewable energy schemes; waste-to-energy schemes; on-site generation and combined heat and power (CHP) schemes; and peak lopping schemes using back-up generators. Where necessary, the guide distinguishes between arrangements that apply in Scotland and those that apply in England and Wales. The guide aims to: provide background information about the electricity industry; highlight common technical issues that arise during connection negotiation and their implications for distribution network operators (DNOs) and developers; examine the main factors affecting connection costs and timescales for achieving connections; and identify the different types of contracts relating to connection. The report considers the connection process, the connection application process and timescales, costs and charges, competition in connection, the structure of the UK electricity industry, the statutory framework, the effects of distributed generation of the distribution system, earthing and protection design, safety issues and DNO network information. It includes a glossary, checklists, useful contact details and information about standards and other useful documents.

  1. 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.

  2. Game-theoretic modeling of curtailment rules and network investments with distributed generation

    International Nuclear Information System (INIS)

    Andoni, Merlinda; Robu, Valentin; Früh, Wolf-Gerrit; Flynn, David

    2017-01-01

    Highlights: •Comparative study on curtailment rules and their effects on RES profitability. •Proposal of novel fair curtailment rule which minimises generators’ disruption. •Modeling of private network upgrade as leader-follower (Stackelberg) game. •New model incorporating stochastic generation and variable demand. •New methodology for setting transmission charges in private network upgrade. -- Abstract: Renewable energy has achieved high penetration rates in many areas, leading to curtailment, especially if existing network infrastructure is insufficient and energy generated cannot be exported. In this context, Distribution Network Operators (DNOs) face a significant knowledge gap about how to implement curtailment rules that achieve desired operational objectives, but at the same time minimise disruption and economic losses for renewable generators. In this work, we study the properties of several curtailment rules widely used in UK renewable energy projects, and their effect on the viability of renewable generation investment. Moreover, we propose a new curtailment rule which guarantees fair allocation of curtailment amongst all generators with minimal disruption. Another key knowledge gap faced by DNOs is how to incentivise private network upgrades, especially in settings where several generators can use the same line against the payment of a transmission fee. In this work, we provide a solution to this problem by using tools from algorithmic game theory. Specifically, this setting can be modelled as a Stackelberg game between the private transmission line investor and local renewable generators, who are required to pay a transmission fee to access the line. We provide a method for computing the equilibrium of this game, using a model that captures the stochastic nature of renewable energy generation and demand. Finally, we use the practical setting of a grid reinforcement project from the UK and a large dataset of wind speed measurements and demand

  3. Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation

    Directory of Open Access Journals (Sweden)

    Christian Nowke

    2018-06-01

    Full Text Available Simulation models in many scientific fields can have non-unique solutions or unique solutions which can be difficult to find. Moreover, in evolving systems, unique final state solutions can be reached by multiple different trajectories. Neuroscience is no exception. Often, neural network models are subject to parameter fitting to obtain desirable output comparable to experimental data. Parameter fitting without sufficient constraints and a systematic exploration of the possible solution space can lead to conclusions valid only around local minima or around non-minima. To address this issue, we have developed an interactive tool for visualizing and steering parameters in neural network simulation models. In this work, we focus particularly on connectivity generation, since finding suitable connectivity configurations for neural network models constitutes a complex parameter search scenario. The development of the tool has been guided by several use cases—the tool allows researchers to steer the parameters of the connectivity generation during the simulation, thus quickly growing networks composed of multiple populations with a targeted mean activity. The flexibility of the software allows scientists to explore other connectivity and neuron variables apart from the ones presented as use cases. With this tool, we enable an interactive exploration of parameter spaces and a better understanding of neural network models and grapple with the crucial problem of non-unique network solutions and trajectories. In addition, we observe a reduction in turn around times for the assessment of these models, due to interactive visualization while the simulation is computed.

  4. 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.

  5. 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

  6. Distributed generation in the Dutch LV network - self-supporting residential area

    NARCIS (Netherlands)

    Mes, M.; Vanalme, G.M.A.; Myrzik, J.M.A.; Bongaerts, M.; Verbong, G.P.J.; Kling, W.L.

    2008-01-01

    A self-supporting residential area is seen as an alternative operational approach of power supply in low voltage (LV) networks. The intention of the new approach is to exploit the advantages of distributed generation (DG) and avoid the difficulties, that come with DG when implemented in the

  7. GalaxyGAN: Generative Adversarial Networks for recovery of galaxy features

    Science.gov (United States)

    Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Krishnan Santhanam, Gokula

    2017-02-01

    GalaxyGAN uses Generative Adversarial Networks to reliably recover features in images of galaxies. The package uses machine learning to train on higher quality data and learns to recover detailed features such as galaxy morphology by effectively building priors. This method opens up the possibility of recovering more information from existing and future imaging data.

  8. 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

  9. 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…

  10. 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...

  11. 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.

  12. Generation of intervention strategy for a genetic regulatory network represented by a family of Markov Chains.

    Science.gov (United States)

    Berlow, Noah; Pal, Ranadip

    2011-01-01

    Genetic Regulatory Networks (GRNs) are frequently modeled as Markov Chains providing the transition probabilities of moving from one state of the network to another. The inverse problem of inference of the Markov Chain from noisy and limited experimental data is an ill posed problem and often generates multiple model possibilities instead of a unique one. In this article, we address the issue of intervention in a genetic regulatory network represented by a family of Markov Chains. The purpose of intervention is to alter the steady state probability distribution of the GRN as the steady states are considered to be representative of the phenotypes. We consider robust stationary control policies with best expected behavior. The extreme computational complexity involved in search of robust stationary control policies is mitigated by using a sequential approach to control policy generation and utilizing computationally efficient techniques for updating the stationary probability distribution of a Markov chain following a rank one perturbation.

  13. NASCENT: an automatic protein interaction network generation tool for non-model organisms.

    Science.gov (United States)

    Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

    2009-04-24

    Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

  14. 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...... 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...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...

  15. 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.

  16. 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...

  17. Automatic Generation of Connectivity for Large-Scale Neuronal Network Models through Structural Plasticity.

    Science.gov (United States)

    Diaz-Pier, Sandra; Naveau, Mikaël; Butz-Ostendorf, Markus; Morrison, Abigail

    2016-01-01

    With the emergence of new high performance computation technology in the last decade, the simulation of large scale neural networks which are able to reproduce the behavior and structure of the brain has finally become an achievable target of neuroscience. Due to the number of synaptic connections between neurons and the complexity of biological networks, most contemporary models have manually defined or static connectivity. However, it is expected that modeling the dynamic generation and deletion of the links among neurons, locally and between different regions of the brain, is crucial to unravel important mechanisms associated with learning, memory and healing. Moreover, for many neural circuits that could potentially be modeled, activity data is more readily and reliably available than connectivity data. Thus, a framework that enables networks to wire themselves on the basis of specified activity targets can be of great value in specifying network models where connectivity data is incomplete or has large error margins. To address these issues, in the present work we present an implementation of a model of structural plasticity in the neural network simulator NEST. In this model, synapses consist of two parts, a pre- and a post-synaptic element. Synapses are created and deleted during the execution of the simulation following local homeostatic rules until a mean level of electrical activity is reached in the network. We assess the scalability of the implementation in order to evaluate its potential usage in the self generation of connectivity of large scale networks. We show and discuss the results of simulations on simple two population networks and more complex models of the cortical microcircuit involving 8 populations and 4 layers using the new framework.

  18. Generation of hourly irradiation synthetic series using the neural network multilayer perceptron

    Energy Technology Data Exchange (ETDEWEB)

    Hontoria, L.; Aguilera, J. [Universidad de Jaen, Linares-Jaen (Spain). Dpto. de Electronica; Zufiria, P. [Ciudad Universitaria, Madrid (Spain). Grupo de Redes Neuronales

    2002-05-01

    In this work, a methodology based on the neural network model called multilayer perceptron (MLP) to solve a typical problem in solar energy is presented. This methodology consists of the generation of synthetic series of hourly solar irradiation. The model presented is based on the capacity of the MLP for finding relations between variables for which interrelation is unknown explicitly. The information available can be included progressively at the series generator at different stages. A comparative study with other solar irradiation synthetic generation methods has been done in order to demonstrate the validity of the one proposed. (author)

  19. Research of PV Power Generation MPPT based on GABP Neural Network

    Science.gov (United States)

    Su, Yu; Lin, Xianfu

    2018-05-01

    Photovoltaic power generation has become the main research direction of new energy power generation. But high investment and low efficiency of photovoltaic industry arouse concern in some extent. So maximum power point tracking of photovoltaic power generation has been a popular study point. Due to slow response, oscillation at maximum power point and low precision, the algorithm based on genetic algorithm combined with BP neural network are designed detailedly in this paper. And the modeling and simulation are completed by use of MATLAB/SIMULINK. The results show that the algorithm is effective and the maximum power point can be tracked accurately and quickly.

  20. 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...

  1. 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

    In the past decade, Denmark has dramatically increased the share of distributed power generation from wind power and decentralised co-generation of heat and power (DCHP). This trend will conti-nue, with the consequence that the power transmission network will face capacity problems in the future....... 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...... electricity markets....

  2. 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.

  3. 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)

  4. Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks.

    Science.gov (United States)

    Molina, Martin; Sanchez-Soriano, Javier; Corcho, Oscar

    2015-07-03

    Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia) to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods) and their impact in the generation of sensor descriptions.

  5. Using Open Geographic Data to Generate Natural Language Descriptions for Hydrological Sensor Networks

    Directory of Open Access Journals (Sweden)

    Martin Molina

    2015-07-01

    Full Text Available Providing descriptions of isolated sensors and sensor networks in natural language, understandable by the general public, is useful to help users find relevant sensors and analyze sensor data. In this paper, we discuss the feasibility of using geographic knowledge from public databases available on the Web (such as OpenStreetMap, Geonames, or DBpedia to automatically construct such descriptions. We present a general method that uses such information to generate sensor descriptions in natural language. The results of the evaluation of our method in a hydrologic national sensor network showed that this approach is feasible and capable of generating adequate sensor descriptions with a lower development effort compared to other approaches. In the paper we also analyze certain problems that we found in public databases (e.g., heterogeneity, non-standard use of labels, or rigid search methods and their impact in the generation of sensor descriptions.

  6. A neuronal network model with simplified tonotopicity for tinnitus generation and its relief by sound therapy.

    Science.gov (United States)

    Nagashino, Hirofumi; Kinouchi, Yohsuke; Danesh, Ali A; Pandya, Abhijit S

    2013-01-01

    Tinnitus is the perception of sound in the ears or in the head where no external source is present. Sound therapy is one of the most effective techniques for tinnitus treatment that have been proposed. In order to investigate mechanisms of tinnitus generation and the clinical effects of sound therapy, we have proposed conceptual and computational models with plasticity using a neural oscillator or a neuronal network model. In the present paper, we propose a neuronal network model with simplified tonotopicity of the auditory system as more detailed structure. In this model an integrate-and-fire neuron model is employed and homeostatic plasticity is incorporated. The computer simulation results show that the present model can show the generation of oscillation and its cessation by external input. It suggests that the present framework is promising as a modeling for the tinnitus generation and the effects of sound therapy.

  7. 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.

  8. Data-Driven Handover Optimization in Next Generation Mobile Communication Networks

    Directory of Open Access Journals (Sweden)

    Po-Chiang Lin

    2016-01-01

    Full Text Available Network densification is regarded as one of the important ingredients to increase capacity for next generation mobile communication networks. However, it also leads to mobility problems since users are more likely to hand over to another cell in dense or even ultradense mobile communication networks. Therefore, supporting seamless and robust connectivity through such networks becomes a very important issue. In this paper, we investigate handover (HO optimization in next generation mobile communication networks. We propose a data-driven handover optimization (DHO approach, which aims to mitigate mobility problems including too-late HO, too-early HO, HO to wrong cell, ping-pong HO, and unnecessary HO. The key performance indicator (KPI is defined as the weighted average of the ratios of these mobility problems. The DHO approach collects data from the mobile communication measurement results and provides a model to estimate the relationship between the KPI and features from the collected dataset. Based on the model, the handover parameters, including the handover margin and time-to-trigger, are optimized to minimize the KPI. Simulation results show that the proposed DHO approach could effectively mitigate mobility problems.

  9. 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.

  10. 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.

  11. 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.

  12. Voltage regulation in MV networks with dispersed generations by a neural-based multiobjective methodology

    Energy Technology Data Exchange (ETDEWEB)

    Galdi, Vincenzo [Dipartimento di Ingegneria dell' Informazione e Ingegneria Elettrica, Universita degli studi di Salerno, Via Ponte Don Melillo 1, 84084 Fisciano (Italy); Vaccaro, Alfredo; Villacci, Domenico [Dipartimento di Ingegneria, Universita degli Studi del Sannio, Piazza Roma 21, 82100 Benevento (Italy)

    2008-05-15

    This paper puts forward the role of learning techniques in addressing the problem of an efficient and optimal centralized voltage control in distribution networks equipped with dispersed generation systems (DGSs). The proposed methodology employs a radial basis function network (RBFN) to identify the multidimensional nonlinear mapping between a vector of observable variables describing the network operating point and the optimal set points of the voltage regulating devices. The RBFN is trained by numerical data generated by solving the voltage regulation problem for a set of network operating points by a rigorous multiobjective solution methodology. The RBFN performance is continuously monitored by a supervisor process that notifies when there is the need of a more accurate solution of the voltage regulation problem if nonoptimal network operating conditions (ex post monitoring) or excessive distances between the actual network state and the neuron's centres (ex ante monitoring) are detected. A more rigorous problem solution, if required, can be obtained by solving the voltage regulation problem by a conventional multiobjective optimization technique. This new solution, in conjunction with the corresponding input vector, is then adopted as a new train data sample to adapt the RBFN. This online training process allows RBFN to (i) adaptively learn the more representative domain space regions of the input/output mapping without needing a prior knowledge of a complete and representative training set, and (ii) manage effectively any time varying phenomena affecting this mapping. The results obtained by simulating the regulation policy in the case of a medium-voltage network are very promising. (author)

  13. 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.

  14. 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)

  15. 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

  16. Translation-aware semantic segmentation via conditional least-square generative adversarial networks

    Science.gov (United States)

    Zhang, Mi; Hu, Xiangyun; Zhao, Like; Pang, Shiyan; Gong, Jinqi; Luo, Min

    2017-10-01

    Semantic segmentation has recently made rapid progress in the field of remote sensing and computer vision. However, many leading approaches cannot simultaneously translate label maps to possible source images with a limited number of training images. The core issue is insufficient adversarial information to interpret the inverse process and proper objective loss function to overcome the vanishing gradient problem. We propose the use of conditional least squares generative adversarial networks (CLS-GAN) to delineate visual objects and solve these problems. We trained the CLS-GAN network for semantic segmentation to discriminate dense prediction information either from training images or generative networks. We show that the optimal objective function of CLS-GAN is a special class of f-divergence and yields a generator that lies on the decision boundary of discriminator that reduces possible vanished gradient. We also demonstrate the effectiveness of the proposed architecture at translating images from label maps in the learning process. Experiments on a limited number of high resolution images, including close-range and remote sensing datasets, indicate that the proposed method leads to the improved semantic segmentation accuracy and can simultaneously generate high quality images from label maps.

  17. Unbundling in Current Broadband and Next-Generation Ultra-Broadband Access Networks

    Science.gov (United States)

    Gaudino, Roberto; Giuliano, Romeo; Mazzenga, Franco; Valcarenghi, Luca; Vatalaro, Francesco

    2014-05-01

    This article overviews the methods that are currently under investigation for implementing multi-operator open-access/shared-access techniques in next-generation access ultra-broadband architectures, starting from the traditional "unbundling-of-the-local-loop" techniques implemented in legacy twisted-pair digital subscriber line access networks. A straightforward replication of these copper-based unbundling-of-the-local-loop techniques is usually not feasible on next-generation access networks, including fiber-to-the-home point-to-multipoint passive optical networks. To investigate this issue, the article first gives a concise description of traditional copper-based unbundling-of-the-local-loop solutions, then focalizes on both next-generation access hybrid fiber-copper digital subscriber line fiber-to-the-cabinet scenarios and on fiber to the home by accounting for the mix of regulatory and technological reasons driving the next-generation access migration path, focusing mostly on the European situation.

  18. 3D conditional generative adversarial networks for high-quality PET image estimation at low dose.

    Science.gov (United States)

    Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping

    2018-07-01

    Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state

  19. Personal identifiers in medical research networks: evaluation of the personal identifier generator in the Competence Network Paediatric Oncology and Haematology

    Directory of Open Access Journals (Sweden)

    Pommerening, Klaus

    2006-06-01

    Full Text Available The Society for Paediatric Oncology and Haematology (GPOH and the corresponding Competence Network Paediatric Oncology and Haematology conduct various clinical trials. The comprehensive analysis requires reliable identification of the recruited patients. Therefore, a personal identifier (PID generator is used to assign unambiguous, pseudonymous, non-reversible PIDs to participants in those trials. We tested the matching algorithm of the PID generator using a configuration specific to the GPOH. False data was used to verify the correct processing of PID requests (functionality tests, while test data was used to evaluate the matching outcome. We also assigned PIDs to more than 44,000 data records from the German Childhood Cancer Registry (GCCR and assessed the status of the associated patient list which contains the PIDs, partly encrypted data items and information on the PID generation process for each data record. All the functionality tests showed the expected results. Neither 14,915 test data records nor the GCCR data records yielded any homonyms. Six synonyms were found in the test data, due to erroneous birth dates, and 22 synonyms were found when the GCCR data was run against the actual patient list of 2579 records. In the resulting patient list of 45,693 entries, duplicate record submissions were found for about 7% of all listed patients, while more frequent submissions occurred in less than 1% of cases. The synonym error rate depends mainly on the quality of the input data and on the frequency of multiple submissions. Depending on the requirements on maximally tolerable synonym and homonym error rates, additional measures for securing input data quality might be necessary. The results demonstrate that the PID generator is an appropriate tool for reliably identifying trial participants in medical research networks.

  20. 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

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

    Science.gov (United States)

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    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. Communication network structure parameters and new knowledge generation capabilities in companies engaged in industry control system engineering projects

    Directory of Open Access Journals (Sweden)

    Titov Sergei

    2016-01-01

    Full Text Available Engineering companies engaged in business of industry control systems need to manage the processes of generation of innovations within and across their projects. Generation and diffusion of innovations materialize through the communication networks of project teams. Therefore, it is possible to hypothesize that the characteristics of communication networks play role in generation of new knowledge. With the data from 14 industry control system projects of a Russian engineering company the communication network structure characteristics were calculated and the analysis of correlation between these characteristics and knowledge generation capabilities was performed. As a result correlation between centralization of communication and the number of new technical solutions developed in projects was discovered.

  3. 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...

  4. Reflection on Migration Scenarios 2G and 3G Mobile Networks to Fourth Generation in Colombia

    Directory of Open Access Journals (Sweden)

    Sergio A. Sepúlveda-Leiva

    2013-11-01

    Full Text Available In the development of the following article is an analysis of some of the migration scenarios third generation mobile technologies for fourth generation mobile technologies, in order to select which is the most suitable migration scenario for mobile operators Colombia, taking into account the characteristics of the market and the needs that are more optimally suited for the needs of mobile operators in the country, the whole development of the article is based on operators with own infrastructure is not analyzed migration characteristics of mobile virtual network operators.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Occluded object reconstruction for first responders with augmented reality glasses using conditional generative adversarial networks

    OpenAIRE

    Yun, Kyongsik; Lu, Thomas; Chow, Edward

    2018-01-01

    Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts....

  11. 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..

  12. 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.

  13. Establishing a national knowledge translation and generation network in kidney disease: the CAnadian KidNey KNowledge TraNslation and GEneration NeTwork.

    Science.gov (United States)

    Manns, Braden; Barrett, Brendan; Evans, Michael; Garg, Amit; Hemmelgarn, Brenda; Kappel, Joanne; Klarenbach, Scott; Madore, Francois; Parfrey, Patrick; Samuel, Susan; Soroka, Steven; Suri, Rita; Tonelli, Marcello; Wald, Ron; Walsh, Michael; Zappitelli, Michael

    2014-01-01

    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.

  14. 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.

  15. 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.

  16. 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.

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

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2017-01-01

    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.

  18. 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

  19. 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.

  20. 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...

  1. An 8-GW long-pulse generator based on Tesla transformer and pulse forming network.

    Science.gov (United States)

    Su, Jiancang; Zhang, Xibo; Li, Rui; Zhao, Liang; Sun, Xu; Wang, Limin; Zeng, Bo; Cheng, Jie; Wang, Ying; Peng, Jianchang; Song, Xiaoxin

    2014-06-01

    A long-pulse generator TPG700L based on a Tesla transformer and a series pulse forming network (PFN) is constructed to generate intense electron beams for the purpose of high power microwave (HPM) generation. The TPG700L mainly consists of a 12-stage PFN, a built-in Tesla transformer in a pulse forming line, a three-electrode gas switch, a transmission line with a trigger, and a load. The Tesla transformer and the compact PFN are the key technologies for the development of the TPG700L. This generator can output electrical pulses with a width as long as 200 ns at a level of 8 GW and a repetition rate of 50 Hz. When used to drive a relative backward wave oscillator for HPM generation, the electrical pulse width is about 100 ns on a voltage level of 520 kV. Factors affecting the pulse waveform of the TPG700L are also discussed. At present, the TPG700L performs well for long-pulse HPM generation in our laboratory.

  2. An 8-GW long-pulse generator based on Tesla transformer and pulse forming network

    Energy Technology Data Exchange (ETDEWEB)

    Su, Jiancang; Zhang, Xibo; Li, Rui; Zhao, Liang, E-mail: zhaoliang0526@163.com; Sun, Xu; Wang, Limin; Zeng, Bo; Cheng, Jie; Wang, Ying; Peng, Jianchang; Song, Xiaoxin [Science and Technology on High Power Microwave Laboratory, Northwest Institute of Nuclear Technology, Xi' an, Shaanxi 710024 (China)

    2014-06-15

    A long-pulse generator TPG700L based on a Tesla transformer and a series pulse forming network (PFN) is constructed to generate intense electron beams for the purpose of high power microwave (HPM) generation. The TPG700L mainly consists of a 12-stage PFN, a built-in Tesla transformer in a pulse forming line, a three-electrode gas switch, a transmission line with a trigger, and a load. The Tesla transformer and the compact PFN are the key technologies for the development of the TPG700L. This generator can output electrical pulses with a width as long as 200 ns at a level of 8 GW and a repetition rate of 50 Hz. When used to drive a relative backward wave oscillator for HPM generation, the electrical pulse width is about 100 ns on a voltage level of 520 kV. Factors affecting the pulse waveform of the TPG700L are also discussed. At present, the TPG700L performs well for long-pulse HPM generation in our laboratory.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Automated generation of node-splitting models for assessment of inconsistency in network meta-analysis.

    Science.gov (United States)

    van Valkenhoef, Gert; Dias, Sofia; Ades, A E; Welton, Nicky J

    2016-03-01

    Network meta-analysis enables the simultaneous synthesis of a network of clinical trials comparing any number of treatments. Potential inconsistencies between estimates of relative treatment effects are an important concern, and several methods to detect inconsistency have been proposed. This paper is concerned with the node-splitting approach, which is particularly attractive because of its straightforward interpretation, contrasting estimates from both direct and indirect evidence. However, node-splitting analyses are labour-intensive because each comparison of interest requires a separate model. It would be advantageous if node-splitting models could be estimated automatically for all comparisons of interest. We present an unambiguous decision rule to choose which comparisons to split, and prove that it selects only comparisons in potentially inconsistent loops in the network, and that all potentially inconsistent loops in the network are investigated. Moreover, the decision rule circumvents problems with the parameterisation of multi-arm trials, ensuring that model generation is trivial in all cases. Thus, our methods eliminate most of the manual work involved in using the node-splitting approach, enabling the analyst to focus on interpreting the results. © 2015 The Authors Research Synthesis Methods Published by John Wiley & Sons Ltd.

  10. 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

  11. 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.

  12. Multi-agent based controller for islanding operation of active distribution networks with distributed generation

    DEFF Research Database (Denmark)

    Cha, Seung-Tae; Wu, Qiuwei; Østergaard, Jacob

    2011-01-01

    -bus system was used to investigate the dynamic and steady state performance of the active distribution system during islanding operation. Case studies have been carried out using the Real-Time Digital Simulator (RTDS) based simulation platform. Case study results show that the proposed multi......The increasing amount of distributed generation (DG) in today’s highly complex restructured power networks gives more options for distribution system operators (DSOs) under contingency conditions. A low voltage distribution network with a large amount of DG can be operated as an islanded system...... if the distribution system is disconnected from the main grid due to the contingency. In order to successfully operate distribution systems under islanding mode, the possibility of small power islands within the distribution system needs to be considered. The control and management of these small power islands...

  13. 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.

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2007-01-01

    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. PMID:17584920

  17. 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.

  18. 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.

  19. Automatic Seamline Network Generation for Urban Orthophoto Mosaicking with the Use of a Digital Surface Model

    Directory of Open Access Journals (Sweden)

    Qi Chen

    2014-12-01

    Full Text Available Intelligent seamline selection for image mosaicking is an area of active research in the fields of massive data processing, computer vision, photogrammetry and remote sensing. In mosaicking applications for digital orthophoto maps (DOMs, the visual transition in mosaics is mainly caused by differences in positioning accuracy, image tone and relief displacement of high ground objects between overlapping DOMs. Among these three factors, relief displacement, which prevents the seamless mosaicking of images, is relatively more difficult to address. To minimize visual discontinuities, many optimization algorithms have been studied for the automatic selection of seamlines to avoid high ground objects. Thus, a new automatic seamline selection algorithm using a digital surface model (DSM is proposed. The main idea of this algorithm is to guide a seamline toward a low area on the basis of the elevation information in a DSM. Given that the elevation of a DSM is not completely synchronous with a DOM, a new model, called the orthoimage elevation synchronous model (OESM, is derived and introduced. OESM can accurately reflect the elevation information for each DOM unit. Through the morphological processing of the OESM data in the overlapping area, an initial path network is obtained for seamline selection. Subsequently, a cost function is defined on the basis of several measurements, and Dijkstra’s algorithm is adopted to determine the least-cost path from the initial network. Finally, the proposed algorithm is employed for automatic seamline network construction; the effective mosaic polygon of each image is determined, and a seamless mosaic is generated. The experiments with three different datasets indicate that the proposed method meets the requirements for seamline network construction. In comparative trials, the generated seamlines pass through fewer ground objects with low time consumption.

  20. 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.

  1. Shortening actin filaments cause force generation in actomyosin network to change from contractile to extensile

    Science.gov (United States)

    Kumar, Nitin; Gardel, Margaret

    Motor proteins in conjunction with filamentous proteins convert biochemical energy into mechanical energy which serves a number of cellular processes including cell motility, force generation and intracellular cargo transport. In-vitro experiments suggest that the forces generated by kinesin motors on microtubule bundles are extensile in nature whereas myosin motors on actin filaments are contractile. It is not clear how qualitatively similar systems can show completely different behaviors in terms of the nature of force generation. In order to answer this question, we carry out in vitro experiments where we form quasi 2D filamentous actomyosin networks and vary the length of actin filaments by adding capping protein. We show that when filaments are much shorter than their typical persistence length (approximately 10 microns), the forces generated are extensile and we see active nematic defect propagation, as seen in the microtubule-kinesin system. Based on this observation, we claim that the rigidity of rods plays an important role in dictating the nature of force generation in such systems. In order to understand this transition, we selectively label individual filaments and find that longer filaments show considerable bending and buckling, making them difficult to slide and extend along their length.

  2. 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)

  3. 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.

  4. Generation of n x m-scroll attractors in a two-port RCL network with hysteresis circuits

    International Nuclear Information System (INIS)

    Yu Simin; Tang, Wallace K.S.

    2009-01-01

    In this paper, the generation of n x m-scroll attractors based on a two-port network is presented. The two-port network is built according to the RCL circuit suggested in the conventional Chua's circuit. By appending hysteresis voltage controlled devices on this two-port network, n-scroll and n x m-scroll attractors can be duly obtained both in simulations and experiments.

  5. 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.

  6. 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.

  7. Generating macroscopic chaos in a network of globally coupled phase oscillators

    Science.gov (United States)

    So, Paul; Barreto, Ernest

    2011-01-01

    We consider an infinite network of globally coupled phase oscillators in which the natural frequencies of the oscillators are drawn from a symmetric bimodal distribution. We demonstrate that macroscopic chaos can occur in this system when the coupling strength varies periodically in time. We identify period-doubling cascades to chaos, attractor crises, and horseshoe dynamics for the macroscopic mean field. Based on recent work that clarified the bifurcation structure of the static bimodal Kuramoto system, we qualitatively describe the mechanism for the generation of such complicated behavior in the time varying case. PMID:21974662

  8. 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...

  9. Voltage management of distribution networks with high penetration of distributed photovoltaic generation sources

    Science.gov (United States)

    Alyami, Saeed

    Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage

  10. 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

  11. 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.

  12. Generative Adversarial Networks for Noise Reduction in Low-Dose CT.

    Science.gov (United States)

    Wolterink, Jelmer M; Leiner, Tim; Viergever, Max A; Isgum, Ivana

    2017-12-01

    Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.

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

    Science.gov (United States)

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

    2009-12-01

    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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Energy-Efficient User Association Strategy for Hyperdense Heterogeneous Networking in the Fifth Generation Systems

    Directory of Open Access Journals (Sweden)

    Lei Li

    2015-01-01

    Full Text Available Redesigning user association strategies to improve energy efficiency (EE has been viewed as one of the promising shifting paradigms for the fifth generation (5G cellular networks. In this paper, we investigate how to optimize users’ association to enhance EE for hyper dense heterogeneous networking in the 5G cellular networks, where the low-power node (LPN much outnumbers the high-power node (HPN. To characterize that densely deployed LPNs would undertake a majority of high-rate services, while HPNs mainly support coverage; the EE metric is defined as average weighted EE of access nodes with the unit of bit per joule. Then, the EE optimization objective function is formulated and proved to be nonconvex. Two mathematical transformation techniques are presented to solve the nonconvex problem. In the first case, the original problem is reformulated as an equivalent problem involving the maximization of a biconcave function. In the second case, it is equivalent to a concave minimization problem. We focus on the solution of the biconcave framework, and, by exploiting the biconcave structure, a novel iterative algorithm based on dual theory is proposed, where a partially optimal solution can be achieved. Simulation results have verified the effectiveness of the proposed algorithm.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. Training-Image Based Geostatistical Inversion Using a Spatial Generative Adversarial Neural Network

    Science.gov (United States)

    Laloy, Eric; Hérault, Romain; Jacques, Diederik; Linde, Niklas

    2018-01-01

    Probabilistic inversion within a multiple-point statistics framework is often computationally prohibitive for high-dimensional problems. To partly address this, we introduce and evaluate a new training-image based inversion approach for complex geologic media. Our approach relies on a deep neural network of the generative adversarial network (GAN) type. After training using a training image (TI), our proposed spatial GAN (SGAN) can quickly generate 2-D and 3-D unconditional realizations. A key characteristic of our SGAN is that it defines a (very) low-dimensional parameterization, thereby allowing for efficient probabilistic inversion using state-of-the-art Markov chain Monte Carlo (MCMC) methods. In addition, available direct conditioning data can be incorporated within the inversion. Several 2-D and 3-D categorical TIs are first used to analyze the performance of our SGAN for unconditional geostatistical simulation. Training our deep network can take several hours. After training, realizations containing a few millions of pixels/voxels can be produced in a matter of seconds. This makes it especially useful for simulating many thousands of realizations (e.g., for MCMC inversion) as the relative cost of the training per realization diminishes with the considered number of realizations. Synthetic inversion case studies involving 2-D steady state flow and 3-D transient hydraulic tomography with and without direct conditioning data are used to illustrate the effectiveness of our proposed SGAN-based inversion. For the 2-D case, the inversion rapidly explores the posterior model distribution. For the 3-D case, the inversion recovers model realizations that fit the data close to the target level and visually resemble the true model well.

  13. 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)

    1998-12-31

    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

  14. 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…

  15. 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.

  16. 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.

  17. Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Yi Yu

    2018-02-01

    Full Text Available The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.

  18. 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.

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

    International Nuclear Information System (INIS)

    Ten Donkelaar, M.; Van Oostvoorn, F.

    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

  20. 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.

  1. Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

    KAUST Repository

    Alqerm, Ismail

    2018-01-01

    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

  2. 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

  3. 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.

  4. 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...... converter, the model of the main transformer and a simple model of the grid. The simulation results obtained by means of the detailed wind turbine model are compared with the results obtained from a simplified simulator with an analytical model and FEM model of DFIG. The comparison of the results shows...... 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...

  5. The contribution to distribution network fault levels from the connection of distributed generation

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2005-07-01

    This report summarises the findings of a study investigating the potential impact of distributed generation (DG) on the UK distribution network fault levels up to the year 2010, and examining ways of managing the fault levels so that they do not become a barrier to increased penetration of DG. The project focuses on the circumstances and scenarios that give rise to the fault levels. The background to the study is traced, and a technical review is presented covering the relationship between DG and fault levels, and the likely impact in the period to 2010. Options for managing increased fault levels, and fault level management and costs are outlined, and a case study is given. The measurement and calculation of fault level values are described along with constraints to DG penetration due to fault level limitations, characteristics of DG machines, and long term perspectives to 2020-2030.

  6. Fine-Tuning Neural Patient Question Retrieval Model with Generative Adversarial Networks.

    Science.gov (United States)

    Tang, Guoyu; Ni, Yuan; Wang, Keqiang; Yong, Qin

    2018-01-01

    The online patient question and answering (Q&A) system attracts an increasing amount of users in China. Patient will post their questions and wait for doctors' response. To avoid the lag time involved with the waiting and to reduce the workload on the doctors, a better method is to automatically retrieve the semantically equivalent question from the archive. We present a Generative Adversarial Networks (GAN) based approach to automatically retrieve patient question. We apply supervised deep learning based approaches to determine the similarity between patient questions. Then a GAN framework is used to fine-tune the pre-trained deep learning models. The experiment results show that fine-tuning by GAN can improve the performance.

  7. 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.

  8. 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.

  9. 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.

  10. Third generation algae biofuels in Italy by 2030: A scenario analysis using Bayesian networks

    International Nuclear Information System (INIS)

    Gambelli, Danilo; Alberti, Francesca; Solfanelli, Francesco; Vairo, Daniela; Zanoli, Raffaele

    2017-01-01

    We have analysed the potential for biofuels from microalgae in the Italian biofuels context. This scenario analysis considers alternative pathways for the adoption of biofuels from microalgae by the year 2030. The scenarios were developed using a probabilistic approach based on Bayesian networks, through a structured process for elicitation of expert knowledge. We have identified the most and least favourable scenarios in terms of the expected likelihood for the development of the market of biofuels from microalgae, through which we have focussed on the contribution of economic and policy aspects in the development of the sector. A detailed analysis of the contribution of each variable in the context of the scenarios is also provided. These data represent a starting point for the evaluation of different policy options for the future biofuel market in Italy. The best scenario shows a 75% probability that biofuels from microalgae will exceed 20% of the biofuel market by 2030. This is conditional on the improvement and development of the technological changes and environmental policies, and of the markets for bioenergy and novel foods derived from microalgae. - Highlights: • Scenarios for Third generation biofuels are modelled by Bayesian networks. • Best and worst scenarios for year 2030 are presented. • The role of environmental policy is analysed. • Energy and food-feed markets influence the share of biofuels from micro-algae.

  11. 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.

  12. Performance assessment of electric power generations using an adaptive neural network algorithm

    International Nuclear Information System (INIS)

    Azadeh, A.; Ghaderi, S.F.; Anvari, M.; Saberi, M.

    2007-01-01

    Efficiency frontier analysis has been an important approach of evaluating firms' performance in private and public sectors. There have been many efficiency frontier analysis methods reported in the literature. However, the assumptions made for each of these methods are restrictive. Each of these methodologies has its strength as well as major limitations. This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions about the function structure of the stochastic frontier. In this algorithm, for calculating the efficiency scores, a similar approach to econometric methods has been used. Moreover, the effect of the return to scale of decision-making units (DMUs) on its efficiency is included and the unit used for the correction is selected by notice of its scale (under constant return to scale assumption). An example using real data is presented for illustrative purposes. In the application to the power generation sector of Iran, we find that the neural network provide more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored. Moreover, principle component analysis (PCA) is used to verify the findings of the proposed algorithm

  13. 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.

  14. 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.

  15. Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

    2014-01-01

    Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

  16. Opinion Mining for User Generated Design by Social Networking Service and Japanese Manga

    Directory of Open Access Journals (Sweden)

    Anak Agung Gede Dharma

    2013-09-01

    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 XE "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.

  17. A generation-attraction model for renewable energy flows in Italy: A complex network approach

    Science.gov (United States)

    Valori, Luca; Giannuzzi, Giovanni Luca; Facchini, Angelo; Squartini, Tiziano; Garlaschelli, Diego; Basosi, Riccardo

    2016-10-01

    In recent years, in Italy, the trend of the electricity demand and the need to connect a large number of renewable energy power generators to the power-grid, developed a novel type of energy transmission/distribution infrastructure. The Italian Transmission System Operator (TSO) and the Distribution System Operator (DSO), worked on a new infrastructural model, based on electronic meters and information technology. In pursuing this objective it is crucial importance to understand how even more larger shares of renewable energy can be fully integrated, providing a constant and reliable energy background over space and time. This is particularly true for intermittent sources as photovoltaic installations due to the fine-grained distribution of them across the Country. In this work we use an over-simplified model to characterize the Italian power grid as a graph whose nodes are Italian municipalities and the edges cross the administrative boundaries between a selected municipality and its first neighbours, following a Delaunay triangulation. Our aim is to describe the power flow as a diffusion process over a network, and using open data on the solar irradiation at the ground level, we estimate the production of photovoltaic energy in each node. An attraction index was also defined using demographic data, in accordance with average per capita energy consumption data. The available energy on each node was calculated by finding the stationary state of a generation-attraction model.

  18. 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.

  19. 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.

  20. 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.

  1. Fluid distribution network and steam generators and method for nuclear power plant training simulator

    International Nuclear Information System (INIS)

    Alliston, W.H.; Johnson, S.J.; Mutafelija, B.A.

    1975-01-01

    A description is given of a training simulator for the real-time dynamic operation of a nuclear power plant which utilizes apparatus that includes control consoles having manual and automatic devices corresponding to simulated plant components and indicating devices for monitoring physical values in the simulated plant. A digital computer configuration is connected to the control consoles to calculate the dynamic real-time simulated operation of the plant in accordance with the simulated plant components to provide output data including data for operating the control console indicating devices. In the method and system for simulating a fluid distribution network of the power plant, such as that which includes, for example, a main steam system which distributes steam from steam generators to high pressure turbine steam reheaters, steam dump valves, and feedwater heaters, the simultaneous solution of linearized non-linear algebraic equations is used to calculate all the flows throughout the simulated system. A plurality of parallel connected steam generators that supply steam to the system are simulated individually, and include the simulation of shrink-swell characteristics

  2. 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

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

    Science.gov (United States)

    Li, Cheng-Wei; Chen, Bor-Sen

    2016-01-01

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

  4. 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.

  5. 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

    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...... 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...

  6. 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.

  7. Protection from ground faults in the stator winding of generators at power plants in the Siberian networks

    International Nuclear Information System (INIS)

    Vainshtein, R. A.; Lapin, V. I.; Naumov, A. M.; Doronin, A. V.; Yudin, S. M.

    2010-01-01

    The experience of many years of experience in developing and utilization of ground fault protection in the stator winding of generators in the Siberian networks is generalized. The main method of protection is to apply a direct current or an alternating current with a frequency of 25 Hz to the primary circuits of the stator. A direct current is applied to turbo generators operating in a unit with a transformer without a resistive coupling to the external grid or to other generators. Applying a 25 Hz control current is appropriate for power generation systems with compensation of a capacitive short circuit current to ground. This method forms the basis for protection of generators operating on busbars, hydroelectric generators with a neutral grounded through an arc-suppression reactor, including in consolidated units with generators operating in parallel on a single low-voltage transformer winding.

  8. 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…

  9. 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.

  10. White light emission and second harmonic generation from secondary group participation (SGP) in a coordination network.

    Science.gov (United States)

    He, Jun; Zeller, Matthias; Hunter, Allen D; Xu, Zhengtao

    2012-01-25

    We describe a white emitting coordination network solid that can be conveniently applied as a thin film onto a commercial UV-LED lamp for practical white lighting applications. The solid state material was discovered in an exercise of exploring molecular building blocks equipped with secondary groups for fine-tuning the structures and properties of coordination nets. Specifically, CH(3)SCH(2)CH(2)S- and (S)-CH(3)(OH)CHCH(2)S- (2-hydroxylpropyl) were each attached as secondary groups to the 2,5- positions of 1,4-benzenedicarboxylic acid (bdc), and the resultant molecules (L1 and L2, respectively) were crystallized with Pb(II) into the topologically similar 3D nets of PbL1 and PbL2, both consisting of interlinked Pb-carboxyl chains. While the CH(3)S- groups in PbL1 are not bonded to the Pb(II) centers, the hydroxy groups in PbL2 participate in coordinating to Pb(II) and thus modify the bonding features around the Pb(II), but only to a slight and subtle degree (e.g., Pb-O distances 2.941-3.116 Å). Interestingly, the subtle change in structure significantly impacts the properties, i.e., while the photoluminescence of PbL1 is yellowish green, PbL2 features bright white emission. Also, the homochiral side group in PbL2 imparts significant second harmonic generation, in spite of its seemingly weak association with the main framework (the NLO-phore). In a broad perspective, this work showcases the idea of secondary group participation (SGP) in the construction of coordination networks, an idea that parallels that of hemilabile ligands in organometallics and points to an effective strategy in developing advanced functions in solid state framework materials. © 2011 American Chemical Society

  11. 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

  12. 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...

  13. 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...

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

    KAUST Repository

    Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

    2017-01-01

    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

  15. Heterogeneous flow in multi-layer joint networks and its influence on incipient karst generation

    Science.gov (United States)

    Wang, X.; Jourde, H.

    2017-12-01

    Various dissolution types (e.g. pipe, stripe and sheet karstic features) have been observed in fractured layered limestones. Yet, due to a large range of structural and hydraulic parameters play a role in the karstification process, the dissolution mechanism, occurring either along fractures or bedding planes, is difficult to quantify. In this study, we use numerical models to investigate the influence of these parameters on the generation of different types of incipient karst. Specifically, we focus on two parameters: the fracture intensity contrast between adjacent layers and the aperture ratio between bedding planes and joints (abed/ajoint). The DFN models were generated using a pseudo-genetic code that considers the stress shadow zone. Flow simulations were performed using a combined finite-volume finite-element simulator under practical boundary conditions. The flow channeling within the fracture networks was characterized by applying a multi-fractal technique. The rock block equivalent permeability (keff) was also calculated to quantify the change in bulk hydraulic properties when changing the selected structural and hydraulic parameters. The flow simulation results show that the abed/ajoint ratio has a first-order control on the heterogeneous distribution of flow in the multi-layer system and on the magnitude of equivalent permeability. When abed/ajoint 0.1, the bedding plane has more control and flow becomes more pervasive and uniform, and the keff is accordingly high. A simple model, accounting for the calculation of the heterogeneous distributions of Damköhler number associated with different aperture ratios, is proposed to predict what type of incipient karst tends to develop under the studied flow conditions.

  16. 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

  17. Synthesis of variable harmonic impedance in inverter-interfaced distributed generation unit for harmonic damping throughout a distribution network

    DEFF Research Database (Denmark)

    Wang, Xiongfei; Blaabjerg, Frede; Chen, Zhe

    2012-01-01

    This paper proposes a harmonic impedance synthesis technique for voltage-controlled distributed generation inverter in order to damp harmonic voltage distortion on a distribution network. The approach employs a multiloop control scheme, where a selective load harmonic current feedforward loop bas...

  18. Dynamic optical routing and simultaneous generation of millimeter-wave signals for in-building access network

    NARCIS (Netherlands)

    Zou, S.; Okonkwo, C.M.; Cao, Z.; Tran, N.C.; Tangdiongga, E.; Koonen, A.M.J.

    2012-01-01

    Two-stage optical routing using SOA and integrated micro-ring resonator, and remote generation of millimeter-wave signals by optical frequency multiplication is demonstrated for inbuilding network. Both 150Mb/s 64-QAM and 802.11a WLAN signal at 38GHz are transmitted.

  19. 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,

  20. Complex networks generated by the Penna bit-string model: Emergence of small-world and assortative mixing

    Science.gov (United States)

    Li, Chunguang; Maini, Philip K.

    2005-10-01

    The Penna bit-string model successfully encompasses many phenomena of population evolution, including inheritance, mutation, evolution, and aging. If we consider social interactions among individuals in the Penna model, the population will form a complex network. In this paper, we first modify the Verhulst factor to control only the birth rate, and introduce activity-based preferential reproduction of offspring in the Penna model. The social interactions among individuals are generated by both inheritance and activity-based preferential increase. Then we study the properties of the complex network generated by the modified Penna model. We find that the resulting complex network has a small-world effect and the assortative mixing property.

  1. 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.

  2. 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.

  3. 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.

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

    KAUST Repository

    Dhaini, Ahmad R.; Ho, Pin-Han; Shen, Gangxiang; Shihada, Basem

    2014-01-01

    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.

  5. 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.

  6. 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.

    2018-06-01

    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 r-band images with artificial AGN point sources added that are then removed using the GAN and with parametric methods using GALFIT. When the AGN point source is more than twice as bright as the host galaxy, we find that our method, PSFGAN, can recover point source and host galaxy magnitudes with smaller systematic error and a lower average scatter (49 per cent). 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 per cent if it is trained on multiple PSFs. 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 is more robust and easy to use than parametric methods as it requires no input parameters.

  7. 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.

  8. 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.

  9. 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.

  10. Generative adversarial networks recover features in astrophysical images of galaxies beyond the deconvolution limit

    Science.gov (United States)

    Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Santhanam, Gokula Krishnan

    2017-05-01

    Observations of astrophysical objects such as galaxies are limited by various sources of random and systematic noise from the sky background, the optical system of the telescope and the detector used to record the data. Conventional deconvolution techniques are limited in their ability to recover features in imaging data by the Shannon-Nyquist sampling theorem. Here, we train a generative adversarial network (GAN) on a sample of 4550 images of nearby galaxies at 0.01 < z < 0.02 from the Sloan Digital Sky Survey and conduct 10× cross-validation to evaluate the results. We present a method using a GAN trained on galaxy images that can recover features from artificially degraded images with worse seeing and higher noise than the original with a performance that far exceeds simple deconvolution. The ability to better recover detailed features such as galaxy morphology from low signal to noise and low angular resolution imaging data significantly increases our ability to study existing data sets of astrophysical objects as well as future observations with observatories such as the Large Synoptic Sky Telescope (LSST) and the Hubble and James Webb space telescopes.

  11. 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.

  12. 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.

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

    Science.gov (United States)

    Kogut, Tomasz; Niemeyer, Joachim; Bujakiewicz, Aleksandra

    2016-06-01

    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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. MR-based synthetic CT generation using a deep convolutional neural network method.

    Science.gov (United States)

    Han, Xiao

    2017-04-01

    Interests have been rapidly growing in the field of radiotherapy to replace CT with magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and the desire to reduce unnecessary radiation dose. MR-only radiotherapy also simplifies clinical workflow and avoids uncertainties in aligning MR with CT. Methods, however, are needed to derive CT-equivalent representations, often known as synthetic CT (sCT), from patient MR images for dose calculation and DRR-based patient positioning. Synthetic CT estimation is also important for PET attenuation correction in hybrid PET-MR systems. We propose in this work a novel deep convolutional neural network (DCNN) method for sCT generation and evaluate its performance on a set of brain tumor patient images. The proposed method builds upon recent developments of deep learning and convolutional neural networks in the computer vision literature. The proposed DCNN model has 27 convolutional layers interleaved with pooling and unpooling layers and 35 million free parameters, which can be trained to learn a direct end-to-end mapping from MR images to their corresponding CTs. Training such a large model on our limited data is made possible through the principle of transfer learning and by initializing model weights from a pretrained model. Eighteen brain tumor patients with both CT and T1-weighted MR images are used as experimental data and a sixfold cross-validation study is performed. Each sCT generated is compared against the real CT image of the same patient on a voxel-by-voxel basis. Comparison is also made with respect to an atlas-based approach that involves deformable atlas registration and patch-based atlas fusion. The proposed DCNN method produced a mean absolute error (MAE) below 85 HU for 13 of the 18 test subjects. The overall average MAE was 84.8 ± 17.3 HU for all subjects, which was found to be significantly better than the average MAE of 94.5 ± 17.8 HU for the atlas-based method. The DCNN

  19. 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...

  20. 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.

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

    International Nuclear Information System (INIS)

    Choi, Jae Bong; Hur, Nam Su; Moon, Seong In; Seo, Hyeong Won; Park, Bo Kyu; Park, Sung Ho; Kim, Hyung Geun

    2004-02-01

    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

  2. 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.

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

    Institute of Scientific and Technical Information of China (English)

    ZHAO Haitao; ZHANG Shaojie; Emiliano Garcia-Palacios

    2016-01-01

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

  4. 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.

  5. Dual Cross-Linked Biofunctional and Self-Healing Networks to Generate User-Defined Modular Gradient Hydrogel Constructs.

    Science.gov (United States)

    Wei, Zhao; Lewis, Daniel M; Xu, Yu; Gerecht, Sharon

    2017-08-01

    Gradient hydrogels have been developed to mimic the spatiotemporal differences of multiple gradient cues in tissues. Current approaches used to generate such hydrogels are restricted to a single gradient shape and distribution. Here, a hydrogel is designed that includes two chemical cross-linking networks, biofunctional, and self-healing networks, enabling the customizable formation of modular gradient hydrogel construct with various gradient distributions and flexible shapes. The biofunctional networks are formed via Michael addition between the acrylates of oxidized acrylated hyaluronic acid (OAHA) and the dithiol of matrix metalloproteinase (MMP)-sensitive cross-linker and RGD peptides. The self-healing networks are formed via dynamic Schiff base reaction between N-carboxyethyl chitosan (CEC) and OAHA, which drives the modular gradient units to self-heal into an integral modular gradient hydrogel. The CEC-OAHA-MMP hydrogel exhibits excellent flowability at 37 °C under shear stress, enabling its injection to generate gradient distributions and shapes. Furthermore, encapsulated sarcoma cells respond to the gradient cues of RGD peptides and MMP-sensitive cross-linkers in the hydrogel. With these superior properties, the dual cross-linked CEC-OAHA-MMP hydrogel holds significant potential for generating customizable gradient hydrogel constructs, to study and guide cellular responses to their microenvironment such as in tumor mimicking, tissue engineering, and stem cell differentiation and morphogenesis. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. 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.

  7. 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.

  8. Studi Migrasi Public Switched Telephone Network (Pstn) Menuju Jaringan Telekomunikasi Berbasis Paket Next Generation Network (Ngn) Dengan Teknologi Softswitch

    OpenAIRE

    Suseno, Andrias Danang; Najib, Warsun; Samiyono, -

    2009-01-01

    Public Switched Telephone Network (PSTN) adalah sistem telekomunikasi berbasis circuit-switched. Pada awalnya PSTN hanya menyediakan layanan voice. PSTN sekarang telah berkembang ke arah pelayanan komunikasi data yang didorong oleh berkembangnya dunia internet dengan Internet Protokol (IP)-nya. Telah muncul teknologi Voice over IP (VoIP) yang mampu melewatkan trafik voice pada jaringan data dengan mengubah voice menjadi paket. VoIP telah mendorong trend/kecenderungan terjadinya konvergensi an...

  9. 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.

  10. 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

  11. 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.

  12. 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…

  13. 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.)

  14. Access regulation in the next generation access network environment: A comparative study of Hong Kong and Singapore from the transaction cost economics perspectives

    OpenAIRE

    Ho, Au Man

    2012-01-01

    Hong Kong and Singapore have adopted two different models in the regulation of the next generation access (NGA) networks. In Hong Kong, the government has decided that access regulation will not be applied to fibre-based access networks and its strategy will be to rely on facilities-based competition to promote investment in the NGA networks. Singapore, on the other hand, has promoted access/services-based competition over a next generation broadband infrastructure subsidised by public fundin...

  15. Calculation of the energy provided by a PV generator. Comparative study: Conventional methods vs. artificial neural networks

    International Nuclear Information System (INIS)

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

    2011-01-01

    The use of photovoltaics for electricity generation purposes has recorded one of the largest increases in the field of renewable energies. The energy production of a grid-connected PV system depends on various factors. In a wide sense, it is considered that the annual energy provided by a generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. However, a range of factors is influencing the expected outcome by reducing the generation of energy. The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network developed by the R and D Group for Solar and Automatic Energy at the University of Jaen. The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study, mainly due to the fact that this method takes also into account some second order effects, such as low irradiance, angular and spectral effects. -- Research highlights: → It is considered that the annual energy provided by a PV generator is directly proportional to the annual radiation incident on the plane of the generator and to the installed nominal power. → A range of factors are influencing the expected outcome by reducing the generation of energy (mismatch losses, dirt and dust, Ohmic losses,.). → The aim of this study is to compare the results of four different methods for estimating the annual energy produced by a PV generator: three of them are classical methods and the fourth one is based on an artificial neural network. → The results obtained shown that the method based on an artificial neural network provides better results than the alternative classical methods in study. While classical methods have only taken into account temperature losses, the method based in

  16. 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.

  17. A Scalable QoS-Aware VoD Resource Sharing Scheme for Next Generation Networks

    Science.gov (United States)

    Huang, Chenn-Jung; Luo, Yun-Cheng; Chen, Chun-Hua; Hu, Kai-Wen

    In network-aware concept, applications are aware of network conditions and are adaptable to the varying environment to achieve acceptable and predictable performance. In this work, a solution for video on demand service that integrates wireless and wired networks by using the network aware concepts is proposed to reduce the blocking probability and dropping probability of mobile requests. Fuzzy logic inference system is employed to select appropriate cache relay nodes to cache published video streams and distribute them to different peers through service oriented architecture (SOA). SIP-based control protocol and IMS standard are adopted to ensure the possibility of heterogeneous communication and provide a framework for delivering real-time multimedia services over an IP-based network to ensure interoperability, roaming, and end-to-end session management. The experimental results demonstrate that effectiveness and practicability of the proposed work.

  18. 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

  19. 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.

  20. 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...... and distributed generators’ reactive powers in order to minimize comprehensive cost. Corresponding constraints, including voltage profile, maximum allowable daily switching operation numbers (MADSON), reactive power limits, and so on, are considered. The strategy of grouping branches is used to simplify...... (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...

  1. 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.

  2. 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.

  3. 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.

  4. 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

    The isolated spinal cord of the newborn rat contains networks that are able to create a patterned motor output resembling normal locomotor movements. In this study, we sought to localize the regions of primary importance for rhythm and pattern generation using specific mechanical lesions. We used...... 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......, 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....

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

    Directory of Open Access Journals (Sweden)

    K. Di

    2017-07-01

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

  6. 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

  7. 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.

  8. 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.

  9. 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

    2016-01-01

    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. PMID:26861336

  10. Spin wave absorber generated by artificial surface anisotropy for spin wave device network

    Directory of Open Access Journals (Sweden)

    Naoki Kanazawa

    2016-09-01

    Full Text Available Spin waves (SWs have the potential to reduce the electric energy loss in signal processing networks. The SWs called magnetostatic forward volume waves (MSFVWs are advantageous for networking due to their isotropic dispersion in the plane of a device. To control the MSFVW flow in a processing network based on yttrium iron garnet, we developed a SW absorber using artificial structures. The mechanical surface polishing method presented in this work can well control extrinsic damping without changing the SW dispersion of the host material. Furthermore, enhancement of the ferromagnetic resonance linewidth over 3 Oe was demonstrated.

  11. 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

  12. New approach in electricity network regulation: an issue on effective integration of distributed generation in electricity supply systems

    International Nuclear Information System (INIS)

    Scheepers, Martin J.J.; Wals, Adrian F.

    2003-11-01

    Technological developments and EU targets for penetration of renewable energy sources (RES) and greenhouse gas (GHG) reduction are decentralising the electricity infrastructure and services. Although, the liberalisation and internationalisation of the European electricity market has resulted in efforts to harmonise transmission pricing and regulation, hardly any initiative exists to consider the opening up and regulation of distribution networks to ensure effective participation of RES and distributed generation (DG) in the internal market. The SUSTELNET project has been created in order to close this policy gap. Its main objective is to develop regulatory roadmaps for the transition to an electricity market and network structure that creates a level playing field between centralised and decentralised generation and that facilitates the integration of RES, within the framework of the liberalisation of the EU electricity market. By analysing the technical, socio-economic and institutional dynamics of the European electricity system and markets, the project identifies the underlying patterns that provide the boundary conditions and levers for policy development to reach long term RES and GHG targets (2020-2030 time frame). This paper presents results of this analytical phase of the SUSTELNET project. Furthermore, preliminary results of the current work in progress are presented. Principles and criteria for a regulatory framework for sustainable electricity systems are discussed, as well as the development of medium to long-term transition strategies/roadmaps for network regulation and market transformation to facilitate the integration of RES and decentralised electricity generating systems.

  13. 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

  14. 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.

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

    KAUST Repository

    Ghazzai, Hakim; Yaacoub, Elias; Kadri, Abdullah; Yanikomeroglu, Halim; Alouini, Mohamed-Slim

    2016-01-01

    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

  16. 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...

  17. 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.

  18. Interplay of intrinsic and synaptic conductances in the generation of high-frequency oscillations in interneuronal networks with irregular spiking.

    Directory of Open Access Journals (Sweden)

    Fabiano Baroni

    2014-05-01

    Full Text Available High-frequency oscillations (above 30 Hz have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF or Generalized Integrate-and-Fire (GIF neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i the firing rate response to the noisy background input, ii the membrane potential distribution, and iii the shape of Inhibitory Post-Synaptic Potentials (IPSPs. For hyperpolarizing inhibition, the GIF IPSP profile (factor iii exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i and ii, respectively, which tend to decrease synchrony. If inhibition is shunting instead

  19. Interplay of intrinsic and synaptic conductances in the generation of high-frequency oscillations in interneuronal networks with irregular spiking.

    Science.gov (United States)

    Baroni, Fabiano; Burkitt, Anthony N; Grayden, David B

    2014-05-01

    High-frequency oscillations (above 30 Hz) have been observed in sensory and higher-order brain areas, and are believed to constitute a general hallmark of functional neuronal activation. Fast inhibition in interneuronal networks has been suggested as a general mechanism for the generation of high-frequency oscillations. Certain classes of interneurons exhibit subthreshold oscillations, but the effect of this intrinsic neuronal property on the population rhythm is not completely understood. We study the influence of intrinsic damped subthreshold oscillations in the emergence of collective high-frequency oscillations, and elucidate the dynamical mechanisms that underlie this phenomenon. We simulate neuronal networks composed of either Integrate-and-Fire (IF) or Generalized Integrate-and-Fire (GIF) neurons. The IF model displays purely passive subthreshold dynamics, while the GIF model exhibits subthreshold damped oscillations. Individual neurons receive inhibitory synaptic currents mediated by spiking activity in their neighbors as well as noisy synaptic bombardment, and fire irregularly at a lower rate than population frequency. We identify three factors that affect the influence of single-neuron properties on synchronization mediated by inhibition: i) the firing rate response to the noisy background input, ii) the membrane potential distribution, and iii) the shape of Inhibitory Post-Synaptic Potentials (IPSPs). For hyperpolarizing inhibition, the GIF IPSP profile (factor iii)) exhibits post-inhibitory rebound, which induces a coherent spike-mediated depolarization across cells that greatly facilitates synchronous oscillations. This effect dominates the network dynamics, hence GIF networks display stronger oscillations than IF networks. However, the restorative current in the GIF neuron lowers firing rates and narrows the membrane potential distribution (factors i) and ii), respectively), which tend to decrease synchrony. If inhibition is shunting instead of

  20. Next generation passive optical networks based on orthogonal frequency division multiplexing techniques

    OpenAIRE

    Escayola Elias, Francesc Xavier

    2015-01-01

    In recent decades, the industry of communications has acquired huge significance, and nowadays constitutes an essential tool for the society information. Thus, the exponential growth in demand of broadband services and the increasing amount of information to be transmitted have spurred the evolution of the access network infrastructure to effectively meet the user needs in an effective way in terms of costs of both installation and maintenance. Passive optical networks (PON) are current...

  1. 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...

  2. A system design for distributed energy generation in low temperature district heating (LTDH) networks

    OpenAIRE

    Jones, Sean; Gillott, Mark C.; Boukhanouf, Rabah; Walker, Gavin S.; Tunzi, Michele; Tetlow, David; Rodrigues, Lucélia Taranto; Sumner, M.

    2017-01-01

    Project SCENIC (Smart Controlled Energy Networks Integrated in Communities) involves connecting properties at the University of Nottingham’s Creative Energy Homes test site in a community scale, integrated heat and power network. Controls will be developed to allow for the most effective heat load allocation and power distribution scenarios. Furthermore, the system will develop the prosumer concept, where consumers are both buyers and sellers of energy in both heat and power systems. \\ud \\ud ...

  3. An Exploratory Application of Neural Networks to the Sortie Generation Forecasting Problem

    Science.gov (United States)

    1991-09-01

    research of Dr. David A. Diener, Major, USAF. As the initial research increment to be improved upon by future researchers, this study (1) provides a... David A. Diener, Major, USAF, who virtually transformed my dream of exploring neural network techniques into concrete reality. His talents in...New York: John Wiley & Sons, 1978. Barron R. L., Gilstrap, L. 0., and Shrier , S. "Polynomial al and Neural Networks: Analogies and Engineering

  4. Energy Saving in Water Distribution Network through Pump as Turbine Generators: Economic and Environmental Analysis

    Directory of Open Access Journals (Sweden)

    Mauro De Marchis

    2016-10-01

    Full Text Available Complex systems of water distribution networks (WDS are used to supply water to users. WDSs are systems where a lot of distributed energy is available. Historically, this energy is artificially dissipated by pressure reduction valves (PRVs, thanks to which water utilities manage the pressure level in selected nodes of the network. The present study explores the use of economic hydraulic machines, pumps as turbines (PATs to produce energy in a small network located in a town close to Palermo (Italy. The main idea is to avoid dissipation in favor of renewable energy production. The proposed study is applied to a WDN typical of the Mediterranean countries, where the users, to collect water during the period of water scarcity conditions, install private tanks. The presence of private tanks deeply modifies the network from its designed condition. In the proposed analysis, the economic benefit of PATs application in water distribution networks has been investigated, accounting for the presence of users’ private tanks. The analysis, carried out by mean of a mathematical model able to dynamically simulate the water distribution network with PATs, shows the advantage of their installation in terms of renewable energy recovery, even though the energy production of PATs is strictly conditioned by their installation position.

  5. 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

  6. Stator current harmonics evolution by neural network method based on CFE/SS algorithm for ACEC generator of Rey Power Plant

    International Nuclear Information System (INIS)

    Soleymani, S.; Ranjbar, A.M.; Mirabedini, H.

    2001-01-01

    One method for on-line fault diagnosis in synchronous generator is stator current harmonics analysis. Then artificial neural network is considered in this paper in order to evaluate stator current harmonics in different loads. Training set of artificial neural network is made ready by generator modeling, finite element method and state space model. Many points from generator capability curve are used in order to complete this set. Artificial neural network which is used in this paper is a percept ron network with a single hidden layer, Eight hidden neurons and back propagation algorithm. Results are indicated that the trained artificial neural network can identify stator current harmonics for arbitrary load from the capability curve. The error is less than 10% in comparison with values obtained directly from the CFE-SS algorithm. The rating parameters of modeled generator are 43950 (kV A), 11(KV), 3000 (rpm), 50 (H Z), (P F=0.8)

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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...... 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....... 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...

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

    DEFF Research Database (Denmark)

    Park, Kiwoo

    enable various renewable energy sources, such as Photovoltaic (PV) and wind, to produce dc power directly. In addition, battery-based energy storage systems inherently operate with dc power. Hence, dc network (dc-grid) systems which connect these dc sources and storages directly using dc networks...... are gaining much attention again. The dc network system has a great potential to outdo the traditional ac systems in many technical challenges and could be highly profitable especially for offshore wind farm applications, where the size and weight of the components are crucial to the entire system costs......Wind power technology, as the most competitive renewable energy technology, is quickly developing. The wind turbine size is growing and the grid penetration of wind power is increasing rapidly. Recently, the developments on wind power technology pay more attentions on efficiency and reliability...

  15. 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 ...

  16. 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.

  17. 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

  18. Next Generation Enterprise Network: Navy Implementing Revised Approach, but Improvement Needed in Mitigating Risks

    Science.gov (United States)

    2012-09-01

    Hewlett Packard Enterprise Services) that ended in September 2010.2 To bridge the time between the end of the NMCI contract and the full transition to...some leasehold improvements; and moveable infrastructure associated with local network operations. Award contract for transport services and

  19. Information Technology: Better Informed Decision Making Needed on Navy’s Next Generation Enterprise Network Acquisition

    Science.gov (United States)

    2011-03-01

    million. To bridge the time frame between the end of the NMCI contract and the full transition to NGEN, DON awarded a $3.7 billion continuity of...leasehold improvements; and moveable infrastructure associated with local network operations. End-User Hardware December 2011 Provide end-user

  20. 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.

  1. Gap junction networks can generate both ripple-like and fast ripple-like oscillations

    Science.gov (United States)

    Simon, Anna; Traub, Roger D.; Vladimirov, Nikita; Jenkins, Alistair; Nicholson, Claire; Whittaker, Roger G.; Schofield, Ian; Clowry, Gavin J.; Cunningham, Mark O.; Whittington, Miles A.

    2014-01-01

    Fast ripples (FRs) are network oscillations, defined variously as having frequencies of > 150 to > 250 Hz, with a controversial mechanism. FRs appear to indicate a propensity of cortical tissue to originate seizures. Here, we demonstrate field oscillations, at up to 400 Hz, in spontaneously epileptic human cortical tissue in vitro, and present a network model that could explain FRs themselves, and their relation to ‘ordinary’ (slower) ripples. We performed network simulations with model pyramidal neurons, having axons electrically coupled. Ripples ( 250 Hz, were sustained or interrupted, and had little jitter in the firing of individual axons. The form of model FR was similar to spontaneously occurring FRs in excised human epileptic tissue. In vitro, FRs were suppressed by a gap junction blocker. Our data suggest that a given network can produce ripples, FRs, or both, via gap junctions, and that FRs are favored by clusters of axonal gap junctions. If axonal gap junctions indeed occur in epileptic tissue, and are mediated by connexin 26 (recently shown to mediate coupling between immature neocortical pyramidal cells), then this prediction is testable. PMID:24118191

  2. Social Demand of New Generation Information Network: Introduction to High Spectral Density Optical Communication Technology

    Science.gov (United States)

    Kamiya, Takeshi; Miyazaki, Tetsuya; Kubota, Fumito

    In this section, first, current situation of traffic growth and penetration of broadband services are described. Then social demand, technical issues, and research trend for future information network in the United States, Europe, and Japan are described. Finally, a detailed construction of this book is introduced.

  3. From physical to virtual: interpersonal relations generating networks among students of a graduate course

    Directory of Open Access Journals (Sweden)

    Roberto Vilmar Satur

    2015-09-01

    Full Text Available Introduction: Nowadays, the social networks are more present in people’s daily lives, especially students, becoming a reality in the educational environment. More than entertainment, these networks have been a valuable interaction tools to passing information through. Objective: In this scenario, the aim of this research is to observe the interpersonal and intragroup interaction abilities in a group of undergraduate students in a public university in order to understand the formation and expansion of social networks initiated through personal contact and extended to the virtual universe. In that sense, it aims specifically at mapping the students interpersonal interactions in the creation of social networks and the expansion of their relations. It describes which are the most used forms of interaction and it gets a basic profile data of the actors. Methodology: To better understand the reality of these subjects it has been adopted as an instrument of data collection, a questionnaire consisting of closed questions directed to students of the course mentioned. A total of 95 student names were enrolled in the course in last May, who could be marked by the respondents. The survey was carried out throughout June 2014 and tallied 71 answered questionnaires. After the data collection, the data were tabulate and it was applied the Gephi software. Results: The results show a tendency to form an extensive network within the course, but it is more intense among certain students, forming small groups and the existence of actors-bridge. The article also showed that there was a clear transposition from the personal relationship contact to the virtual environment. Conclusion: Social networks can increasingly serve as a space for communication and interaction, although the use of these networks in education is related to the teaching and learning process, making advances in the ways of interaction and access to information and search among its users

  4. An multi objective heuristic method for calculating the performance of distribution network with distributed generators; Um metodo heuristico multi-objetivo para calcular o desempenho de redes de distribuicao com geradores distribuidos

    Energy Technology Data Exchange (ETDEWEB)

    Ciric, Rade M.; Padilha, Antonio [UNESP, Ilha Solteira, SP (Brazil)

    2002-07-01

    This paper describes the allocation and the performance of the distributed generators installed in a electric power distribution network, and presents a investigation to determining the impacts of distributed generators integration in power systems and the distribution network global performance.

  5. 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.

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

    KAUST Repository

    Mahmood, Nurul Huda; Yilmaz, Ferkan; Alouini, Mohamed-Slim; Ø ien, Geir Egil

    2014-01-01

    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

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

    KAUST Repository

    Zenil, Hector; Kiani, Narsis A.; Tegner, Jesper

    2018-01-01

    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

  8. 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.

  9. ESnet4: next generation network strategy, architecture, and implementation for DOE Science

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Michael; Burrescia, Joseph; Dart, Eli; Gagliardi, Jim; Guok, Chin; Johnston, William; Metzger, Joe; Oberman, Kevin; O' Connor, Mike

    2006-09-15

    The Department of Energy's (DOE) Office of Science is the largest supporter of basic research in the physical sciences in the US. It directly supports the research of 15,000 PhDs, PostDocs and Graduate Students, and operates major scientific facilities at DOE laboratories that serve the entire US research community: other Federal agencies, universities, and industry, as well as the international research and education (R and E) community. ESnet's mission is to provide the network infrastructure that supports the mission of the Office of Science (SC). ESnet must evolve substantially in order to continue meeting the Office of Science mission needs and this paper discusses the development of ESnet's strategy to meet these requirements through a new network architecture and implementation approach.

  10. ESnet4: next generation network strategy, architecture, and implementation for DOE Science

    International Nuclear Information System (INIS)

    Collins, Michael; Burrescia, Joseph; Dart, Eli; Gagliardi, Jim; Guok, Chin; Johnston, William; Metzger, Joe; Oberman, Kevin; O'Connor, Mike

    2006-01-01

    The Department of Energy's (DOE) Office of Science is the largest supporter of basic research in the physical sciences in the US. It directly supports the research of 15,000 PhDs, PostDocs and Graduate Students, and operates major scientific facilities at DOE laboratories that serve the entire US research community: other Federal agencies, universities, and industry, as well as the international research and education (R and E) community. ESnet's mission is to provide the network infrastructure that supports the mission of the Office of Science (SC). ESnet must evolve substantially in order to continue meeting the Office of Science mission needs and this paper discusses the development of ESnet's strategy to meet these requirements through a new network architecture and implementation approach

  11. Sharpness-Aware Low-Dose CT Denoising Using Conditional Generative Adversarial Network.

    Science.gov (United States)

    Yi, Xin; Babyn, Paul

    2018-02-20

    Low-dose computed tomography (LDCT) has offered tremendous benefits in radiation-restricted applications, but the quantum noise as resulted by the insufficient number of photons could potentially harm the diagnostic performance. Current image-based denoising methods tend to produce a blur effect on the final reconstructed results especially in high noise levels. In this paper, a deep learning-based approach was proposed to mitigate this problem. An adversarially trained network and a sharpness detection network were trained to guide the training process. Experiments on both simulated and real dataset show that the results of the proposed method have very small resolution loss and achieves better performance relative to state-of-the-art methods both quantitatively and visually.

  12. Synthesis of Variable Harmonic Impedance in Inverter-Interfaced Distributed Generation Unit for Harmonic Damping Throughout a Distribution Network

    DEFF Research Database (Denmark)

    Wang, Xiongfei; Blaabjerg, Frede; Chen, Zhe

    2012-01-01

    This paper proposes a harmonic impedance synthesis technique for voltage-controlled distributed generation inverters in order to damp harmonic voltage distortion on a distribution network. The approach employs a multiloop control scheme, where a selective harmonic load current feedforward loop...... at the dominant harmonic frequencies. Thus, the harmonic voltage drop on the grid-side inductance and the harmonic resonances throughout a distribution feeder with multiple shunt-connected capacitors can be effectively attenuated. Simulation and laboratory test results validate the performance of the proposed...

  13. New Generation Marketing On Social Media And A Research On Usage Of Social Networks In

    OpenAIRE

    Tolga Kara

    2012-01-01

    In today’s world where technological progresses are quickly changing our lives, firms have to reshape themselves according to this new understanding. Classical business models that focus on producer are replaced by consumer centric new business ideas. Firms which are far away from needs and expectations of consumer will lose their market position and disappear over time. This view shows itself in new communication channels and social media networks offer incredible possibilities for firms. In...

  14. A Next Generation Repository for Sharing Sensitive Network and Security Data

    Science.gov (United States)

    2018-01-01

    protocols, trends regarding the Internet -of- Things (e.g., in terms of traffic growth) or malicious trends (e.g., scanning). 3.2 Darknet Data Network...Cyber-risk & Trust IP – Internet Protocol IODA – Internet Outage Detection and Analysis IoT – Internet of Things IRB – Institutional Review Board...09 13. SUPPLEMENTARY NOTES 14. ABSTRACT Defending critical infrastructure from cyber-security threats, understanding macroscopic Internet and

  15. A class of dynamin-like GTPases involved in the generation of the tubular ER network

    Science.gov (United States)

    Hu, Junjie; Shibata, Yoko; Zhu, Peng-Peng; Voss, Christiane; Rismanchi, Neggy; Prinz, William A.; Rapoport, Tom A.; Blackstone, Craig

    2009-01-01

    The endoplasmic reticulum (ER) consists of tubules that are shaped by the reticulons and DP1/Yop1p, but how the tubules form an interconnected network is unknown. Here, we show that mammalian atlastins, which are dynamin-like, integral membrane GTPases, interact with the tubule-shaping proteins. The atlastins localize to the tubular ER and are required for proper network formation in vivo and in vitro. Depletion of the atlastins or overexpression of dominant-negative forms inhibits tubule interconnections. The Sey1p GTPase in S. cerevisiae is likely a functional ortholog of the atlastins; it shares the same signature motifs and membrane topology and interacts genetically and physically with the tubule-shaping proteins. Cells simultaneously lacking Sey1p and a tubule-shaping protein have ER morphology defects. These results indicate that formation of the tubular ER network depends on conserved dynamin-like GTPases. Since atlastin-1 mutations cause a common form of hereditary spastic paraplegia, we suggest ER shaping defects as a novel neuropathogenic mechanism. PMID:19665976

  16. 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.

  17. 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

    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...... that the amount of energy generated by the vertical neck–head movement of sheep during grazing can be converted to useful electrical power adequate to provide power for operation of wireless sensor nodes on a continuous basis within a MANET-based animal behavior monitoring system.......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...

  18. An Overview of Metallic Nanowire Networks, Promising Building Blocks for Next Generation Transparent Conductors: Emergence, Fundamentals and Challenges

    Science.gov (United States)

    Pirsalami, Sedigheh; Zebarjad, Seyed Mojtaba; Daneshmanesh, Habib

    2017-08-01

    Transparent conductors (TCs) have a wide range of applications in numerous electronic and optoelectronic devices. This review provides an overview of the emergence of metallic nanowire networks (MNNs) as promising building blocks for the next generation transparent conductors. The fundamental aspects, structure-property relations, fabrication techniques and the corresponding challenges are reviewed. Theoretical and experimental researches suggest that nanowires with smaller diameter, longer length and higher aspect ratio have higher performance. Yet, the development of an efficient synthesis technique for the production of MNNs has remained a challenge. The synthesis method is also crucial to the scalability and the commercial potential of these emerging TCs. The most promising techniques for the synthesis together with their advantages, limitations and the recent findings are here discussed. Finally, we will try to show the promising future research trends in MNNs to have an approach to design the next generation TCs.

  19. Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning

    Energy Technology Data Exchange (ETDEWEB)

    Barin, Alexandre; Pozzatti, Luis F.; Canha, Luciane N.; Abaide, Alzenira R. [Federal University of Santa Maria - UFSM, Post-graduation Program of Electric Engineering - PPGEE, Center of Studies of Energy and Environment - CEEMA, Santa Maria, RS (Brazil); Machado, Ricardo Q. [University of Sao Paulo - USP, Sao Carlos, SP (Brazil); Arend, Gustavo [State Electric Energy Company - CEEE-D, Division of Distribution, Porto Alegre, RS (Brazil)

    2010-12-15

    Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent registered, GARP3 registered and DSA-GD software. A multi-objective approach based on the Bellman-Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder. (author)

  20. 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

    The next generation of information technology demands both high capacity and mobility for applications such as high speed wireless access capable of supporting broadband services. The transport of wireless and wireline signals is converging into a common telecommunication infrastructure....... 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...