Search results for: Heterogeneous Wireless Network
549 Connectionist Approach to Generic Text Summarization
Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad
Abstract:
As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1577548 Neural Networks for Short Term Wind Speed Prediction
Authors: K. Sreelakshmi, P. Ramakanthkumar
Abstract:
Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.Keywords: Short term wind speed prediction, Neural networks, Back propagation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3053547 Intelligent Heart Disease Prediction System Using CANFIS and Genetic Algorithm
Authors: Latha Parthiban, R. Subramanian
Abstract:
Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.
Keywords: CANFIS, genetic algorithms, heart disease, membership function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3970546 ANN Models for Microstrip Line Synthesis and Analysis
Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy
Abstract:
Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2139545 Investigating the Process Kinetics and Nitrogen Gas Production in Anammox Hybrid Reactor with Special Emphasis on the Role of Filter Media
Authors: Swati Tomar, Sunil Kumar Gupta
Abstract:
Anammox is a novel and promising technology that has changed the traditional concept of biological nitrogen removal. The process facilitates direct oxidation of ammonical nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of external carbon sources. The present study investigated the feasibility of Anammox Hybrid Reactor (AHR) combining the dual advantages of suspended and attached growth media for biodegradation of ammonical nitrogen in wastewater. Experimental unit consisted of 4 nos. of 5L capacity AHR inoculated with mixed seed culture containing anoxic and activated sludge (1:1). The process was established by feeding the reactors with synthetic wastewater containing NH4-H and NO2-N in the ratio 1:1 at HRT (hydraulic retention time) of 1 day. The reactors were gradually acclimated to higher ammonium concentration till it attained pseudo steady state removal at a total nitrogen concentration of 1200 mg/l. During this period, the performance of the AHR was monitored at twelve different HRTs varying from 0.25-3.0 d with increasing NLR from 0.4 to 4.8 kg N/m3d. AHR demonstrated significantly higher nitrogen removal (95.1%) at optimal HRT of 1 day. Filter media in AHR contributed an additional 27.2% ammonium removal in addition to 72% reduction in the sludge washout rate. This may be attributed to the functional mechanism of filter media which acts as a mechanical sieve and reduces the sludge washout rate many folds. This enhances the biomass retention capacity of the reactor by 25%, which is the key parameter for successful operation of high rate bioreactors. The effluent nitrate concentration, which is one of the bottlenecks of anammox process was also minimised significantly (42.3-52.3 mg/L). Process kinetics was evaluated using first order and Grau-second order models. The first-order substrate removal rate constant was found as 13.0 d-1. Model validation revealed that Grau second order model was more precise and predicted effluent nitrogen concentration with least error (1.84±10%). A new mathematical model based on mass balance was developed to predict N2 gas in AHR. The mass balance model derived from total nitrogen dictated significantly higher correlation (R2=0.986) and predicted N2 gas with least error of precision (0.12±8.49%). SEM study of biomass indicated the presence of heterogeneous population of cocci and rod shaped bacteria of average diameter varying from 1.2-1.5 mm. Owing to enhanced NRE coupled with meagre production of effluent nitrate and its ability to retain high biomass, AHR proved to be the most competitive reactor configuration for dealing with nitrogen laden wastewater.
Keywords: Anammox, filter media, kinetics, nitrogen removal.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2541544 Tools for Analysis and Optimization of Standalone Green Microgrids
Authors: William Anderson, Kyle Kobold, Oleg Yakimenko
Abstract:
Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1041543 Identification of Impact Loads and Partial System Parameters Using 1D-CNN
Authors: Xuewen Yu, Danhui Dan
Abstract:
The identification of impact loads and some hard-to-obtain system parameters is crucial for analysis, validation, and evaluation activities in the engineering field. This paper proposes a method based on 1D-CNN to identify impact loads and partial system parameters from the measured responses. To this end, forward computations are conducted to provide datasets consisting of triples (parameter θ, input u, output y). Two neural networks are then trained: one to learn the mapping from output y to input u and another to learn the mapping from input and output (u, y) to parameter θ. Subsequently, by feeding the measured output response into the trained neural networks, the input impact load and system parameter can be calculated, respectively. The method is tested on two simulated examples and shows sound accuracy in estimating the impact load (waveform and location) and system parameter.
Keywords: Convolutional neural network, impact load identification, system parameter identification, inverse problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 59542 Spatial Correlation of Channel State Information in Real LoRa Measurement
Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur
Abstract:
The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially LoRaWAN. In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated with each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems to get access to a wider band.
Keywords: IoT, LPWAN, LoRa, RSSI, effective signal power, onsite measurement, smart city, channel reciprocity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 478541 A Hypercube Social Feature Extraction and Multipath Routing in Delay Tolerant Networks
Authors: S. Balaji, M. Rajaram, Y. Harold Robinson, E. Golden Julie
Abstract:
Delay Tolerant Networks (DTN) which have sufficient state information include trajectory and contact information, to protect routing efficiency. However, state information is dynamic and hard to obtain without a global and/or long-term collection process. To deal with these problems, the internal social features of each node are introduced in the network to perform the routing process. This type of application is motivated from several human contact networks where people contact each other more frequently if they have more social features in common. Two unique processes were developed for this process; social feature extraction and multipath routing. The routing method then becomes a hypercube–based feature matching process. Furthermore, the effectiveness of multipath routing is evaluated and compared to that of single-path routing.
Keywords: Delay tolerant networks, entropy, human contact networks, hyper cubes, multipath Routing, social features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1297540 A Computer Model of Language Acquisition – Syllable Learning – Based on Hebbian Cell Assemblies and Reinforcement Learning
Authors: Sepideh Fazeli, Fariba Bahrami
Abstract:
Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.Keywords: Brain modeling, computer models, language acquisition, reinforcement learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1578539 Synthesis and Analysis of Swelling and Controlled Release Behaviour of Anionic sIPN Acrylamide based Hydrogels
Authors: Atefeh Hekmat, Abolfazl Barati, Ebrahim Vasheghani Frahani, Ali Afraz
Abstract:
In modern agriculture, polymeric hydrogels are known as a component able to hold an amount of water due to their 3-dimensional network structure and their tendency to absorb water in humid environments. In addition, these hydrogels are able to controllably release the fertilisers and pesticides loaded in them. Therefore, they deliver these materials to the plants' roots and help them with growing. These hydrogels also reduce the pollution of underground water sources by preventing the active components from leaching. In this study, sIPN acrylamide based hydrogels are synthesised by using acrylamide free radical, potassium acrylate, and linear polyvinyl alcohol. Ammonium nitrate is loaded in the hydrogel as the fertiliser. The effect of various amounts of monomers and linear polymer, measured in molar ratio, on the swelling rate, equilibrium swelling, and release of ammonium nitrate is studied.Keywords: Hydrogel, controlled release, ammonium nitrate fertiliser, sIPN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2148538 High Speed Bitwise Search for Digital Forensic System
Authors: Hyungkeun Jee, Jooyoung Lee, Dowon Hong
Abstract:
The most common forensic activity is searching a hard disk for string of data. Nowadays, investigators and analysts are increasingly experiencing large, even terabyte sized data sets when conducting digital investigations. Therefore consecutive searching can take weeks to complete successfully. There are two primary search methods: index-based search and bitwise search. Index-based searching is very fast after the initial indexing but initial indexing takes a long time. In this paper, we discuss a high speed bitwise search model for large-scale digital forensic investigations. We used pattern matching board, which is generally used for network security, to search for string and complex regular expressions. Our results indicate that in many cases, the use of pattern matching board can substantially increase the performance of digital forensic search tools.Keywords: Digital forensics, search, regular expression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1795537 Analysis of Dropped Call Rate for Long Term Evolution Networks in Bayelsa State, Nigeria
Authors: Chibuzo Emeruwa, Nnamdi N. Omehe
Abstract:
This work attempts to effectively compare Dropped Call Rate (DCR) against industry benchmarks and competitor networks to identify areas for improvement and sets performance targets. Four mobile telecommunication networks operational in Bayelsa State Nigeria were considered. Results obtained shows that MTN and Airtel performed well within the regulator’s benchmark of ≤ 1% in all cases, while Globacom and 9moblie had instances where their performance fell outside the benchmark. The maximum values obtained within the period in view was 18.52% and it was in March 2016 for Globacom while the least value recorded is 0.00% and it was in September 2018 for 9mobile. In the seven years period under review, MTN and Airtel performed within the Nigerian Communication Commission’s (NCC) benchmark all through. This affirms that it is possible for the networks to perform optimally if adequate measures are put in place for improved Quality of Service (QoS).
Keywords: Attempted calls, data, dropped call rate, handover failure rate, key performance indicator, mobile network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 97536 Modeling of Normal and Atherosclerotic Blood Vessels using Finite Element Methods and Artificial Neural Networks
Authors: K. Kamalanand, S. Srinivasan
Abstract:
Analysis of blood vessel mechanics in normal and diseased conditions is essential for disease research, medical device design and treatment planning. In this work, 3D finite element models of normal vessel and atherosclerotic vessel with 50% plaque deposition were developed. The developed models were meshed using finite number of tetrahedral elements. The developed models were simulated using actual blood pressure signals. Based on the transient analysis performed on the developed models, the parameters such as total displacement, strain energy density and entropy per unit volume were obtained. Further, the obtained parameters were used to develop artificial neural network models for analyzing normal and atherosclerotic blood vessels. In this paper, the objectives of the study, methodology and significant observations are presented.Keywords: Blood vessel, atherosclerosis, finite element model, artificial neural networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2295535 Bandwidth Optimization through Dynamic Routing in ATM Networks: Genetic Algorithm and Tabu Search Approach
Authors: Susmi Routray, A. M. Sherry, B. V. R. Reddy
Abstract:
Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.Keywords: Asynchronous Transfer Mode(ATM), GeneticAlgorithm(GA), Tabu Search(TS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1758534 A GA-Based Role Assignment Approach for Web-based Cooperative Learning Environments
Authors: Yi-Chun Chang, Jian-Wei Li
Abstract:
Web-based cooperative learning focuses on (1) the interaction and the collaboration of community members, and (2) the sharing and the distribution of knowledge and expertise by network technology to enhance learning performance. Numerous research literatures related to web-based cooperative learning have demonstrated that cooperative scripts have a positive impact to specify, sequence, and assign cooperative learning activities. Besides, literatures have indicated that role-play in web-based cooperative learning environments enhances two or more students to work together toward the completion of a common goal. Since students generally do not know each other and they lack the face-to-face contact that is necessary for the negotiation of assigning group roles in web-based cooperative learning environments, this paper intends to further extend the application of genetic algorithm (GA) and propose a GA-based algorithm to tackle the problem of role assignment in web-based cooperative learning environments, which not only saves communication costs but also reduces conflict between group members in negotiating role assignments.
Keywords: genetic algorithm (GA), role assignment, role-play; web-based cooperative learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1446533 Post ERP Feral System and use of ‘Feral System as Coping Mechanism
Authors: Tajul Urus, S., Molla, A., Teoh, S.Y.
Abstract:
A number of studies highlighted problems related to ERP systems, yet, most of these studies focus on the problems during the project and implementation stages but not during the postimplementation use process. Problems encountered in the process of using ERP would hinder the effective exploitation and the extended and continued use of ERP systems and their value to organisations. This paper investigates the different types of problems users (operational, supervisory and managerial) faced in using ERP and how 'feral system' is used as the coping mechanism. The paper adopts a qualitative method and uses data collected from two cases and 26 interviews, to inductively develop a casual network model of ERP usage problem and its coping mechanism. This model classified post ERP usage problems as data quality, system quality, interface and infrastructure. The model is also categorised the different coping mechanism through use of 'feral system' inclusive of feral information system, feral data and feral use of technology.Keywords: Case Studies, Coping Mechanism, Post Implementation ERP system, Usage Problem
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1499532 Settlement Prediction for Tehran Subway Line-3 via FLAC3D and ANFIS
Authors: S. A. Naeini, A. Khalili
Abstract:
Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.
Keywords: Settlement, subway line, FLAC3D, ANFIS method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1083531 Reliability Analysis of Underground Pipelines Using Subset Simulation
Authors: Kong Fah Tee, Lutfor Rahman Khan, Hongshuang Li
Abstract:
An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.
Keywords: Underground pipelines, Probability of failure, Reliability and Subset Simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3539530 Arabic Light Stemmer for Better Search Accuracy
Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy
Abstract:
Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1484529 Disturbances of the Normal Operation of Kosovo Power System Regarding Atmospheric Discharges
Authors: B. Prebreza, I. Krasniqi, G. Kabashi, G. Pula, N. Avdiu
Abstract:
This paper discusses aspects of outages in the electric transmission network in the Kosovo Power System caused by the atmospheric discharges.
Frequency and location of the atmospheric discharges in Kosovo territory will be provided by a lightning location system ALARM (Automated Lightning Alert and Risk Management) and from the data from the Meteorological Department in Prishtina International Airport. These data will be used to make comparisons with the actual outages registered in the Kosovo Power System from the Kosovo Transmission, systems and market operator (KOSTT) during a specific time period.
The lines with the worst performance determined, regarding the atmospheric discharges, will be choose for further discussions in terms of over voltages caused by the direct or indirect lightning strokes.
Recommendations for protection in terms of insulator coordination and surge arresters will be given at the end and in this stage dynamic simulation will take part.
Keywords: Atmospheric discharges, dynamic simulations, Kosovo Power System, surge arresters.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1830528 Towards a Security Model against Denial of Service Attacks for SIP Traffic
Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla
Abstract:
Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.
Keywords: Denial-of-service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 978527 A Genetic and Simulated Annealing Based Algorithms for Solving the Flow Assignment Problem in Computer Networks
Authors: Tarek M. Mahmoud
Abstract:
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 2245526 Plasmodium Vivax Malaria Transmission in a Network of Villages
Authors: P. Pongsumpun, I. M. Tang
Abstract:
Malaria is a serious, acute and chronic relapsing infection to humans. It is characterized by periodic attacks of chills, fever, nausea, vomiting, back pain, increased sweating anemia, splenomegaly (enlargement of the spleen) and often-fatal complications.The malaria disease is caused by the multiplication of protozoa parasite of the genus Plasmodium. Malaria in humans is due to 4 types of malaria parasites such that Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale. P.vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax malaria can experience relapses of the disease. Between the relapses, the malaria parasite will remain dormant in the liver of the patient, leading to the patient being classified as being in the dormant class. A mathematical model for the transmission of P. vivax is developed in which the human population is divided into four classes, the susceptible, the infected, the dormant and the recovered. In this paper, we formulate the dynamical model of P. vivax malaria to see the distribution of this disease at the district level.Keywords: Dynamical model, household, local level, Plasmodium Vivax Malaria.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1377525 Trust Based Energy Aware Reliable Reactive Protocol in Mobile Ad Hoc Networks
Authors: M. Pushpalatha, Revathi Venkataraman, T. Ramarao
Abstract:
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 2605524 Multi-Scale Urban Spatial Evolution Analysis Based on Space Syntax: A Case Study in Modern Yangzhou, China
Authors: Dai Zhimei, Hua Chen
Abstract:
The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.
Keywords: Space Syntax, spatial texture, urban space, Yangzhou.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 764523 Evolutionary Techniques Based Combined Artificial Neural Networks for Peak Load Forecasting
Authors: P. Subbaraj, V. Rajasekaran
Abstract:
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 1669522 Effective Software-Based Solution for Processing Mass Downstream Data in Interactive Push VOD System
Authors: Ni Hong, Wu Guobin, Wu Gang, Pan Liang
Abstract:
Interactive push VOD system is a new kind of system that incorporates push technology and interactive technique. It can push movies to users at high speeds at off-peak hours for optimal network usage so as to save bandwidth. This paper presents effective software-based solution for processing mass downstream data at terminals of interactive push VOD system, where the service can download movie according to a viewer-s selection. The downstream data is divided into two catalogs: (1) the carousel data delivered according to DSM-CC protocol; (2) IP data delivered according to Euro-DOCSIS protocol. In order to accelerate download speed and reduce data loss rate at terminals, this software strategy introduces caching, multi-thread and resuming mechanisms. The experiments demonstrate advantages of the software-based solution.Keywords: DSM-CC, data carousel, Euro-DOCSIS, push VOD.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478521 Automatic Light Control in Domotics using Artificial Neural Networks
Authors: Carlos Machado, José A. Mendes
Abstract:
Home Automation is a field that, among other subjects, is concerned with the comfort, security and energy requirements of private homes. The configuration of automatic functions in this type of houses is not always simple to its inhabitants requiring the initial setup and regular adjustments. In this work, the ubiquitous computing system vision is used, where the users- action patterns are captured, recorded and used to create the contextawareness that allows the self-configuration of the home automation system. The system will try to free the users from setup adjustments as the home tries to adapt to its inhabitants- real habits. In this paper it is described a completely automated process to determine the light state and act on them, taking in account the users- daily habits. Artificial Neural Network (ANN) is used as a pattern recognition method, classifying for each moment the light state. The work presented uses data from a real house where a family is actually living.Keywords: ANN, Home Automation, Neural Systems, PatternRecognition, Ubiquitous Computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2056520 Research of Dynamic Location Referencing Method Based On Intersection and Link Partition
Authors: Lv Wei-feng, Dai Xi, Zhu Tong-yu
Abstract:
Dynamic location referencing method is an important technology to shield map differences. These method references objects of the road network by utilizing condensed selection of its real-world geographic properties stored in a digital map database, which overcomes the defections existing in pre-coded location referencing methods. The high attributes completeness requirements and complicated reference point selection algorithm are the main problems of recent researches. Therefore, a dynamic location referencing algorithm combining intersection points selected at the extremities compulsively and road link points selected according to link partition principle was proposed. An experimental system based on this theory was implemented. The tests using Beijing digital map database showed satisfied results and thus verified the feasibility and practicability of this method.
Keywords: Dynamic location referencing, inter-sectionreferencing, road link partition, road link point referencing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1699