Search results for: river networks
1595 Tree-on-DAG for Data Aggregation in Sensor Networks
Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik
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Computing and maintaining network structures for efficient data aggregation incurs high overhead for dynamic events where the set of nodes sensing an event changes with time. Moreover, structured approaches are sensitive to the waiting time that is used by nodes to wait for packets from their children before forwarding the packet to the sink. An optimal routing and data aggregation scheme for wireless sensor networks is proposed in this paper. We propose Tree on DAG (ToD), a semistructured approach that uses Dynamic Forwarding on an implicitly constructed structure composed of multiple shortest path trees to support network scalability. The key principle behind ToD is that adjacent nodes in a graph will have low stretch in one of these trees in ToD, thus resulting in early aggregation of packets. Based on simulations on a 2,000-node Mica2- based network, we conclude that efficient aggregation in large-scale networks can be achieved by our semistructured approach.Keywords: Aggregation, Packet Merging, Query Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19191594 Minimizing Energy Consumption in Wireless Sensor Networks using Binary Integer Linear Programming
Authors: Chompunut Jantarasorn, Chutima Prommak
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The important issue considered in the widespread deployment of Wireless Sensor Networks (WSNs) is an efficiency of the energy consumption. In this paper, we present a study of the optimal relay station planning problems using Binary Integer Linear Programming (BILP) model to minimize the energy consumption in WSNs. Our key contribution is that the proposed model not only ensures the required network lifetime but also guarantees the radio connectivity at high level of communication quality. Specially, we take into account effects of noise, signal quality limitation and bit error rate characteristics. Numerical experiments were conducted in various network scenarios. We analyzed the effects of different sensor node densities and distribution on the energy consumption.
Keywords: Binary Integer Linear Programming, BILP, Energy consumption, Optimal node placement and Wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21901593 Continuity Planning in Supply Chain Networks: Degrees of Freedom and Application in the Risk Management Process
Authors: Marco Bötel, Tobias Gelau, Wendelin Gross
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Supply chain networks are frequently hit by unplanned events which lead to disruptions and cause operational and financial consequences. It is neither possible to avoid disruption risk entirely, nor are network members able to prepare for every possible disruptive event. Therefore a continuity planning should be set up which supports effective operational responses in supply chain networks in times of emergencies. In this research network related degrees of freedom which determine the options for responsive actions are derived from interview data. The findings are further embedded into a common risk management process. The paper provides support for researchers and practitioners to identify the network related options for responsive actions and to determine the need for improving the reaction capabilities.Keywords: Supply Chain Risk Management, Business Continuity Planning, Degrees of Freedom, Risk Management Process, Mitigation Measures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19071592 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network
Authors: Motonobu Hattori
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In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20841591 Visualisation and Navigation in Large Scale P2P Service Networks
Authors: H. Unger, H. Coltzau
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In Peer-to-Peer service networks, where peers offer any kind of publicly available services or applications, intuitive navigation through all services in the network becomes more difficult as the number of services increases. In this article, a concept is discussed that enables users to intuitively browse and use large scale P2P service networks. The concept extends the idea of creating virtual 3D-environments solely based on Peer-to-Peer technologies. Aside from browsing, users shall have the possibility to emphasize services of interest using their own semantic criteria. The appearance of the virtual world shall intuitively reflect network properties that may be of interest for the user. Additionally, the concept comprises options for load- and traffic-balancing. In this article, the requirements concerning the underlying infrastructure and the graphical user interface are defined. First impressions of the appearance of future systems are presented and the next steps towards a prototypical implementation are discussed.
Keywords: Internet Operating System, Peer-To-Peer, Service Exploration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12731590 A Maximum Parsimony Model to Reconstruct Phylogenetic Network in Honey Bee Evolution
Authors: Usha Chouhan, K. R. Pardasani
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Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hybridization in plants lead to reticulate networks, therefore, the methods of constructing trees fail in constructing reticulate networks. In this paper a model has been employed to reconstruct phylogenetic network in honey bee. This network represents reticulate evolution in honey bee. The maximum parsimony approach has been used to obtain this reticulate network.Keywords: Hybridization, HGT, Reticulate networks, Recombination, Species, Parsimony.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15971589 A Distributed Topology Control Algorithm to Conserve Energy in Heterogeneous Wireless Mesh Networks
Authors: F. O. Aron, T. O. Olwal, A. Kurien, M. O. Odhiambo
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A considerable amount of energy is consumed during transmission and reception of messages in a wireless mesh network (WMN). Reducing per-node transmission power would greatly increase the network lifetime via power conservation in addition to increasing the network capacity via better spatial bandwidth reuse. In this work, the problem of topology control in a hybrid WMN of heterogeneous wireless devices with varying maximum transmission ranges is considered. A localized distributed topology control algorithm is presented which calculates the optimal transmission power so that (1) network connectivity is maintained (2) node transmission power is reduced to cover only the nearest neighbours (3) networks lifetime is extended. Simulations and analysis of results are carried out in the NS-2 environment to demonstrate the correctness and effectiveness of the proposed algorithm.Keywords: Topology Control, Wireless Mesh Networks, Backbone, Energy Efficiency, Localized Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13871588 Designing a Novel General Sorting Network Constructor Using Artificial Evolution
Authors: Michal Bidlo, Radek Bidlo, Lukas Sekanina
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A method is presented for the construction of arbitrary even-input sorting networks exhibiting better properties than the networks created using a conventional technique of the same type. The method was discovered by means of a genetic algorithm combined with an application-specific development. Similarly to human inventions in the area of theoretical computer science, the evolved invention was analyzed: its generality was proven and area and time complexities were determined.Keywords: Development, genetic algorithm, program, sorting network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12781587 Weaknesses and Strengths Analysis over Wireless Network Security Standards
Authors: Daniel Padilla, Edward Guillen
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Several wireless networks security standards have been proposed and widely implemented in both business and home environments in order to protect the network from unauthorized access. However, the implementation of such standards is usually achieved by network administrators without even knowing the standards- weaknesses and strengths. The intention of this paper is to evaluate and analyze the impact over the network-s security due to the implementation of the wireless networks security standards WEP, WPA and WLAN 802.1X.
Keywords: 802.1X, vulnerabilities analysis, WEP, wireless security, WPA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23691586 Seismic Alert System based on Artificial Neural Networks
Authors: C. M. A. Robles G., R. A. Hernandez-Becerril
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We board the problem of creating a seismic alert system, based upon artificial neural networks, trained by using the well-known back-propagation and genetic algorithms, in order to emit the alarm for the population located into a specific city, about an eminent earthquake greater than 4.5 Richter degrees, and avoiding disasters and human loses. In lieu of using the propagation wave, we employed the magnitude of the earthquake, to establish a correlation between the recorded magnitudes from a controlled area and the city, where we want to emit the alarm. To measure the accuracy of the posed method, we use a database provided by CIRES, which contains the records of 2500 quakes incoming from the State of Guerrero and Mexico City. Particularly, we performed the proposed method to generate an issue warning in Mexico City, employing the magnitudes recorded in the State of Guerrero.Keywords: Seismic Alert System, Artificial Neural Networks, Genetic Algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17131585 Investigation of Artificial Neural Networks Performance to Predict Net Heating Value of Crude Oil by Its Properties
Authors: Mousavian, M. Moghimi Mofrad, M. H. Vakili, D. Ashouri, R. Alizadeh
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The aim of this research is to use artificial neural networks computing technology for estimating the net heating value (NHV) of crude oil by its Properties. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The network with 8 neurons in one hidden layer was selected and prediction of this network has been good agreement with experimental data.
Keywords: Neural Network, Net Heating Value, Crude Oil, Experimental, Modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15711584 Recognition of Noisy Words Using the Time Delay Neural Networks Approach
Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha
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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.
Keywords: Neural networks, Noise, Speech Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19281583 Key Issues and Challenges of Intrusion Detection and Prevention System: Developing Proactive Protection in Wireless Network Environment
Authors: M. Salman, B. Budiardjo, K. Ramli
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Nowadays wireless technology plays an important role in public and personal communication. However, the growth of wireless networking has confused the traditional boundaries between trusted and untrusted networks. Wireless networks are subject to a variety of threats and attacks at present. An attacker has the ability to listen to all network traffic which becoming a potential intrusion. Intrusion of any kind may lead to a chaotic condition. In addition, improperly configured access points also contribute the risk to wireless network. To overcome this issue, a security solution that includes an intrusion detection and prevention system need to be implemented. In this paper, first the security drawbacks of wireless network will be analyzed then investigate the characteristics and also the limitations on current wireless intrusion detection and prevention system. Finally, the requirement of next wireless intrusion prevention system will be identified including some key issues which should be focused on in the future to overcomes those limitations.Keywords: intrusion detection, intrusion prevention, wireless networks, proactive protection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39191582 Design of Non-Blocking and Rearrangeable Modified Banyan Network with Electro-Optic MZI Switching Elements
Authors: Ghanshyam Singh, Tirtha Pratim Bhattacharjee, R. P. Yadav, V. Janyani
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Banyan networks are really attractive for serving as the optical switching architectures due to their unique properties of small depth and absolute signal loss uniformity. The fact has been established that the limitations of blocking nature and the nonavailability of proper connections due to non-rearrangeable property can be easily ruled out using electro-optic MZI switches as basic switching elements. Combination of the horizontal expansion and vertical stacking of optical banyan networks is an appropriate scheme for constructing non-blocking banyan-based optical switching networks. The interconnected banyan switching fabrics (IBSF) have been considered and analyzed to best serve the purpose of optical switching with electro-optic MZI basic elements. The cross/bar state interchange for the switches has been facilitated by appropriate voltage switching or the by the switching of operating wavelength. The paper is dedicated to the modification of the basic switching element being used as well as the architecture of the switching network.Keywords: MZI switch, Banyan network, Reconfigurable switches.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16371581 Effectiveness of Infrastructure Flood Control Due to Development Upstream Land Use: Case Study of Ciliwung Watershed
Authors: Siti Murniningsih, Evi Anggraheni
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Various infrastructures such as dams, flood control dams and reservoirs have been developed in the 19th century until the 20th century. These infrastructures are very effective in controlling the river flows and in preventing inundation in the urban area prone to flooding. Flooding in the urban area often brings large impact, affecting every aspect of life and also environment. Ciliwung is one of the rivers allegedly contributes to the flooding problems in Jakarta; various engineering work has been done in Ciliwung river to help controlling the flooding. One of the engineering work is to build Ciawi Dam and Sukamahi Dam. In this research, author is doing the flood calculation with Nakayasu Method, while the previous flooding in that case study is computed using Level Pool Routine. The effectiveness of these dams can be identified by using flood simulation of existing condition and compare it to the flood simulation after the dam construction. The final goal of this study is to determine the effectiveness of flood mitigation infrastructure located at upstream area in reducing the volume of flooding in Jakarta.
Keywords: Effectiveness, flood simulation, infrastructure flooding, level pool routine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12191580 Proposal of Commutation Protocol in Hybrid Sensors and Vehicular Networks for Intelligent Transport Systems
Authors: Taha Bensiradj, Samira Moussaoui
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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.
Keywords: HSVN, ITS, VANET, WSN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12271579 Multimode Dynamics of the Beijing Road Traffic System
Authors: Zundong Zhang, Limin Jia, Xiaoliang Sun
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The Beijing road traffic system, as a typical huge urban traffic system, provides a platform for analyzing the complex characteristics and the evolving mechanisms of urban traffic systems. Based on dynamic network theory, we construct the dynamic model of the Beijing road traffic system in which the dynamical properties are described completely. Furthermore, we come into the conclusion that urban traffic systems can be viewed as static networks, stochastic networks and complex networks at different system phases by analyzing the structural randomness. As well as, we demonstrate the evolving process of the Beijing road traffic network based on real traffic data, validate the stochastic characteristics and the scale-free property of the network at different phasesKeywords: Dynamic Network Models, Structural Randomness, Scale-free Property, Multi-mode character
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15221578 Mobile Ad-Hoc Service Grid – MASGRID
Authors: Imran Ihsan, Muhammad Abdul Qadir, Nadeem Iftikhar
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Mobile devices, which are progressively surrounded in our everyday life, have created a new paradigm where they interconnect, interact and collaborate with each other. This network can be used for flexible and secure coordinated sharing. On the other hand Grid computing provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In this paper, efforts are made to map the concepts of Grid on Ad-Hoc networks because both exhibit similar kind of characteristics like Scalability, Dynamism and Heterogeneity. In this context we propose “Mobile Ad-Hoc Services Grid – MASGRID".Keywords: Mobile Ad-Hoc Networks, Grid Computing, Resource Discovery, Routing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17831577 Environmental Interference Cancellation of Speech with the Radial Basis Function Networks: An Experimental Comparison
Authors: Nima Hatami
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In this paper, we use Radial Basis Function Networks (RBFN) for solving the problem of environmental interference cancellation of speech signal. We show that the Second Order Thin- Plate Spline (SOTPS) kernel cancels the interferences effectively. For make comparison, we test our experiments on two conventional most used RBFN kernels: the Gaussian and First order TPS (FOTPS) basis functions. The speech signals used here were taken from the OGI Multi-Language Telephone Speech Corpus database and were corrupted with six type of environmental noise from NOISEX-92 database. Experimental results show that the SOTPS kernel can considerably outperform the Gaussian and FOTPS functions on speech interference cancellation problem.Keywords: Environmental interference, interference cancellation of speech, Radial Basis Function networks, Gaussian and TPS kernels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15541576 A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks
Authors: Tarek M. Mahmoud
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Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22451575 An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks
Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu
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Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.
Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15731574 To Join or Not to Join: The Effects of Healthcare Networks
Authors: Tal Ben-Zvi, Donald N. Lombardi
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This study uses a simulation to establish a realistic environment for laboratory research on Accountable Care Organizations. We study network attributes in order to gain insights regarding healthcare providers- conduct and performance. Our findings indicate how network structure creates significant differences in organizational performance. We demonstrate how healthcare providers positioning themselves at the central, pivotal point of the network while maintaining their alliances with their partners produce better outcomes.Keywords: Social Networks, Decision-Making, Accountable Care Organizations, Performance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15291573 Trust Based Energy Aware Reliable Reactive Protocol in Mobile Ad Hoc Networks
Authors: M. Pushpalatha, Revathi Venkataraman, T. Ramarao
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Trust and Energy consumption is the most challenging issue in routing protocol design for Mobile ad hoc networks (MANETs), since mobile nodes are battery powered and nodes behaviour are unpredictable. Furthermore replacing and recharging batteries and making nodes co-operative is often impossible in critical environments like military applications. In this paper, we propose a trust based energy aware routing model in MANET. During route discovery, node with more trust and maximum energy capacity is selected as a router based on a parameter called 'Reliability'. Route request from the source is accepted by a node only if its reliability is high. Otherwise, the route request is discarded. This approach forms a reliable route from source to destination thus increasing network life time, improving energy utilization and decreasing number of packet loss during transmission.Keywords: Mobile Ad Hoc Networks, Trust, Energy, Reliability, AODV, TEA-AODV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26051572 CoP-Networks: Virtual Spaces for New Faculty’s Professional Development in the 21st Higher Education
Authors: Eman AbuKhousa, Marwan Z. Bataineh
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The 21st century higher education and globalization challenge new faculty members to build effective professional networks and partnership with industry in order to accelerate their growth and success. This creates the need for community of practice (CoP)-oriented development approaches that focus on cognitive apprenticeship while considering individual predisposition and future career needs. This work adopts data mining, clustering analysis, and social networking technologies to present the CoP-Network as a virtual space that connects together similar career-aspiration individuals who are socially influenced to join and engage in a process for domain-related knowledge and practice acquisitions. The CoP-Network model can be integrated into higher education to extend traditional graduate and professional development programs.Keywords: Clustering analysis, community of practice, data mining, higher education, new faculty challenges, social networks, social influence, professional development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9661571 Pseudo-almost Periodic Solutions of a Class Delayed Chaotic Neural Networks
Authors: Farouk Cherif
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This paper is concerned with the existence and unique¬ness of pseudo-almost periodic solutions to the chaotic delayed neural networks (t)= —Dx(t) ± A f (x (t)) B f (x (t — r)) C f (x(p))dp J (t) . t-o Under some suitable assumptions on A, B, C, D, J and f, the existence and uniqueness of a pseudo-almost periodic solution to equation above is obtained. The results of this paper are new and they complement previously known results.
Keywords: Chaotic neural network, Hamiltonian systems, Pseudo almost periodic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12991570 Evolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting
Authors: P. Subbaraj, V. Rajasekaran
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This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.
Keywords: Combined ANN, Evolutionary Programming, Particle Swarm Optimization, Genetic Algorithm and Peak load forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16691569 Geochemistry of Natural Radionuclides Associated with Acid Mine Drainage (AMD) in a Coal Mining Area in Southern Brazil
Authors: Juliana A. Galhardi, Daniel M. Bonotto
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Coal is an important non-renewable energy source of and can be associated with radioactive elements. In Figueira city, Paraná state, Brazil, it was recorded high uranium activity near the coal mine that supplies a local thermoelectric power plant. In this context, the radon activity (Rn-222, produced by the Ra-226 decay in the U-238 natural series) was evaluated in groundwater, river water and effluents produced from the acid mine drainage in the coal reject dumps. The samples were collected in August 2013 and in February 2014 and analyzed at LABIDRO (Laboratory of Isotope and Hydrochemistry), UNESP, Rio Claro city, Brazil, using an alpha spectrometer (AlphaGuard) adjusted to evaluate the mean radon activity concentration in five cycles of 10 minutes. No radon activity concentration above 100 Bq.L-1, which was a previous critic value established by the World Health Organization. The average radon activity concentration in groundwater was higher than in surface water and in effluent samples, possibly due to the accumulation of uranium and radium in the aquifer layers that favors the radon trapping. The lower value in the river waters can indicate dilution and the intermediate value in the effluents may indicate radon absorption in the coal particles of the reject dumps. The results also indicate that the radon activities in the effluents increase with the sample acidification, possibly due to the higher radium leaching and the subsequent radon transport to the drainage flow. The water samples of Laranjinha River and Ribeirão das Pedras stream, which, respectively, supply Figueira city and receive the mining effluent, exhibited higher pH values upstream the mine, reflecting the acid mine drainage discharge. The radionuclides transport indicates the importance of monitoring their activity concentration in natural waters due to the risks that the radioactivity can represent to human health.Keywords: Radon, radium, acid mine drainage, coal
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20321568 Application of Feed-Forward Neural Networks Autoregressive Models with Genetic Algorithm in Gross Domestic Product Prediction
Authors: E. Giovanis
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In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16611567 An Algorithm for Determining the Arrival Behavior of a Secondary User to a Base Station in Cognitive Radio Networks
Authors: Danilo López, Edwin Rivas, Leyla López
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This paper presents the development of an algorithm that predicts the arrival of a secondary user (SU) to a base station (BS) in a cognitive network based on infrastructure, requesting a Best Effort (BE) or Real Time (RT) type of service with a determined bandwidth (BW) implementing neural networks. The algorithm dynamically uses a neural network construction technique using the geometric pyramid topology and trains a Multilayer Perceptron Neural Networks (MLPNN) based on the historical arrival of an SU to estimate future applications. This will allow efficiently managing the information in the BS, since it precedes the arrival of the SUs in the stage of selection of the best channel in CRN. As a result, the software application determines the probability of arrival at a future time point and calculates the performance metrics to measure the effectiveness of the predictions made.
Keywords: Cognitive radio, MLPNN, base station, prediction, best effort, real time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14331566 Control of Chaotic Dynamical Systems using RBF Networks
Authors: Yoichi Ishikawa, Yuichi Masukake, Yoshihisa Ishida
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This paper presents a novel control method based on radial basis function networks (RBFNs) for chaotic dynamical systems. The proposed method first identifies the nonlinear part of the chaotic system off-line and then constructs a model-following controller using only the estimated system parameters. Simulation results show the effectiveness of the proposed control scheme.Keywords: Chaos, nonlinear plant, radial basis function network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1631