International Journal of Computer Science and Applications最新文献_第2页

Regularized Compression of A Noisy Blurred Image 噪声模糊图像的正则化压缩

International Journal of Computer Science and Applications Pub Date : 2016-12-31 DOI: 10.5121/IJCSA.2016.6601

P. Favati, G. Lotti, O. Menchi, F. Romani

引用次数: 0

Detecting Unknown Insider Threat Scenarios 检测未知的内部威胁场景

International Journal of Computer Science and Applications Pub Date : 2016-12-31 DOI: 10.5121/IJCSA.2016.6602

M. S. Lodhi, Rahul Kaul

引用次数: 2

ENERGY EFFICIENT, LIFETIME IMPROVING AND SECURE PERIODIC DATA COLLECTION PROTOCOL FOR WIRELESS SENSOR NETWORKS 无线传感器网络的节能、寿命改善和安全定期数据收集协议

International Journal of Computer Science and Applications Pub Date : 2016-06-30 DOI: 10.5121/IJCSA.2016.6301

P. Anuja, Dr. Raju Shanmugam

{"title":"ENERGY EFFICIENT, LIFETIME IMPROVING AND SECURE PERIODIC DATA COLLECTION PROTOCOL FOR WIRELESS SENSOR NETWORKS","authors":"P. Anuja, Dr. Raju Shanmugam","doi":"10.5121/IJCSA.2016.6301","DOIUrl":"https://doi.org/10.5121/IJCSA.2016.6301","url":null,"abstract":"The most emerging prominent sensor network applications collect data from sensor nodes and monitors periodically. Resource constraint Sensor motes sense the environment and transit data to the remote sink via multiple hops. Minimum energy dissipation and secure data transmission are crucial to such applications. This paper delivers an energy efficient, lifetime improving, secure periodic Data Gathering scheme that is a hybrid of heuristic path establishment and secure data transmission. This protocol uses artificial intelligence (AI) based A* heuristic search algorithm to establish energy efficient admissible optimal path to sink in terms of high residual energy, minimum hop counts and high link quality. This scheme also adopts block encryption Rivest Cipher (RC6) Algorithm to secure the transmission of packets. This code and speed optimized block encryption provides confidentiality against critical data and consumes less energy for encryption. This proposed method increases the network lifetime there by reducing the total traffic load. Evaluation of performance analysis of this algorithm using Network Simulator (NS2) shows the superiority of the proposed scheme.","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"26 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86643334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A Novel Clustering Algorithm For Coverage A Large Scale In Wireless Sensor Networks 一种新的无线传感器网络大覆盖聚类算法

International Journal of Computer Science and Applications Pub Date : 2016-04-30 DOI: 10.5121/IJCSA.2016.6201

Wassim Jerbi, Abderrahmen Guermazi, H. Trabelsi

引用次数: 11

An Advance Solar Power Generation and Control of Brushless DC Motor Using Phase Current Infusion of Sensor Less Vector Control 一种新型无刷直流电动机的无传感器矢量控制与相电流注入太阳能发电

International Journal of Computer Science and Applications Pub Date : 2016-01-01 DOI: 10.12783/IJCSA.2016.0501.01

A. Sundaram, G. Ramesh

{"title":"An Advance Solar Power Generation and Control of Brushless DC Motor Using Phase Current Infusion of Sensor Less Vector Control","authors":"A. Sundaram, G. Ramesh","doi":"10.12783/IJCSA.2016.0501.01","DOIUrl":"https://doi.org/10.12783/IJCSA.2016.0501.01","url":null,"abstract":"Solar power is a promising solution in recent environmental aspects so several methods of generation were implemented in past to reach advances in generation capacity and critical conditions of solar. This paper deals with Non-inverting Four Switch buck-boost converter (NFSBBC) which is presented to reach advances in generation with respect to solar condition. The advances of generation include maximum power point tracking using incremental conductance, reliable buck boost operation and voltage stability ratio. Incremental conductance can track rapidly on solar power than perturb and observer method, so proposed power generation draws a continuous power across DC-Link inverter drive for wide speed operation of brushless DC motor. A new phase current infusion is implemented to estimate flux, torque and control of speed in wide range without external infusion and sensing loops in present sensor less vector control. 110W/50V capacity of solar is implemented for present solar power generation; output capacity of converter reaches from 25-100V using buck boost operation. 25V/1500 rpm capacity of brushless DC Motor is controlled using proposed sensor less vector using current infusing logic.","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"17 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81381061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

BK Web-Based E-Voting System: Ensuring Confidence with Votes and Results Verification BK基于网络的电子投票系统:通过投票和结果验证确保信心

International Journal of Computer Science and Applications Pub Date : 2016-01-01 DOI: 10.12783/IJCSA.2016.0501.02

Ben Beklisi Kwame Ayawli, G. A. Gershon

引用次数: 5

A Metadesign Approach in Ontology Construction 本体构建中的元设计方法

International Journal of Computer Science and Applications Pub Date : 2016-01-01 DOI: 10.12783/IJCSA.2016.0502.02

Mesnan Silalahi

引用次数: 0

Modified Clustering Algorithm for Energy Efficiency Utilizing Fuzzy Logic in WSN (MCF) 基于模糊逻辑的WSN能效改进聚类算法(MCF)

International Journal of Computer Science and Applications Pub Date : 2016-01-01 DOI: 10.12783/IJCSA.2016.0502.01

Tuba Firdaus, Meenakshi Yadav

{"title":"Modified Clustering Algorithm for Energy Efficiency Utilizing Fuzzy Logic in WSN (MCF)","authors":"Tuba Firdaus, Meenakshi Yadav","doi":"10.12783/IJCSA.2016.0502.01","DOIUrl":"https://doi.org/10.12783/IJCSA.2016.0502.01","url":null,"abstract":"A number of research have taken place in the field of Wireless Sensor Networks (WSN) as there is continuous need of advancement in the field of wireless communication, digital technology and micro-electro-mechanical systems(MEMS) . So the need of growth of low cost, low power, multifunctional sensor nodes have been required. A Wireless Sensor Network is a collection of sensor nodes that have the capability of sensing any environmental phenomenon, processing that information and then sending that data to the base station. A single sensor node is not capable of capturing desired information from a particular region so a collection of nodes are arranged to get accurate and sufficient result. This collection of sensor nodes along with a base station will collaboratively form a network that is known as Wireless Sensor Network. As limited energy is one of the most important constraint of WSN so it must be assured that it is utilized in most efficient way. Clustering is best approach to remove redundant data transmission to base station. Each cluster has a cluster head that is responsible for transmitting data to base station for that cluster members. Cluster head (CH) collect the data from all members of its cluster and perform aggregation on these data to remove redundancy then send it to base station. So appropriate CH election is very important for improving efficiency. In this thesis we have presented a clustering approach that has taken a heterogeneous environment and uses fuzzy logic to elect CHs more efficiently. We have combined two parameters Distance and Residual Energy and apply fuzzy rules on that to find the priority of a node for being a CH. Simulation shows that using fuzzy logic in SEP (Stability Election Protocol) will improve the energy efficiency by providing better load distribution and utilizing the benefits of heterogeneity of network. We have shown our analysis on two parameters- Number of dead nodes and average energy of nodes","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"5 1","pages":"24-34"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88843401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Evaluation with Web Developers of Capturing User Interaction with Rich Internet Applications for Usability Evaluation 与Web开发人员一起对捕获富互联网应用程序的用户交互进行可用性评估

International Journal of Computer Science and Applications Pub Date : 2015-10-01 DOI: 10.12783/ijcsa.2015.0402.02

Luciano T. E. Pansanato, A. Rivolli, Douglas Felipe Pereira

引用次数: 6

The Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends: How Much Does the Size of Learning Rate Matter? 人工神经网络在预测TCP/IP流量趋势中的泛化能力:学习率的大小有多大关系?

International Journal of Computer Science and Applications Pub Date : 2015-04-01 DOI: 10.12783/ijcsa.2015.0401.02

V. Moyo, K. Sibanda

{"title":"The Generalization Ability of Artificial Neural Networks in Forecasting TCP/IP Traffic Trends: How Much Does the Size of Learning Rate Matter?","authors":"V. Moyo, K. Sibanda","doi":"10.12783/ijcsa.2015.0401.02","DOIUrl":"https://doi.org/10.12783/ijcsa.2015.0401.02","url":null,"abstract":"Artificial Neural Networks (ANNs) have attracted increasing attention from researchers in many fields. They have proved to be one of the most powerful tools in the domain of forecasting and analysis of various time series. The ability to model almost any kind of function regardless of its degree of nonlinearity, positions ANNs as good candidates for predicting and modelling self-similar time series such as TCP/IP traffic. Inspite of this, one of the most difficult and least understood tasks in the design of ANN models is the selection of the most appropriate size of the learning rate. Although some guidance in the form of heuristics is available for the choice of this parameter, none have been universally accepted. In this paper we empirically investigate various sizes of learning rates with the aim of determining the optimum learning rate size for generalization ability of an ANN trained on forecasting TCP/IP network traffic trends. MATLAB Version 7.4.0.287’s Neural Network toolbox version 5.0.2 (R2007a) was used for our experiments. The results are found to be promising in terms of ease of design and use of ANNs. We found from the experiments that, depending on the difficulty of the problem at hand, it is advisable to set the learning rate to 0.1 for the standard Backpropagation algorithm and to either 0.1 or 0.2 if used in conjunction with the momentum term of 0.5 or 0.6. We advise minimal use of the momentum term as it greatly interferes with the training process of ANNs. Although the information obtained from the tests carried out in this paper is specific to the problem considered, it provides users of Back-propagation networks with a valuable guide on the behaviour of ANNs under a wide range of operating conditions. It is important to note that the guidelines accrued from this paper are of an assistive and not necessarily restrictive nature to potential ANN modellers.","PeriodicalId":39465,"journal":{"name":"International Journal of Computer Science and Applications","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2015-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75239244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3