2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)最新文献_第2页

A new enhanced secure anonymous communication with authentication and session key agreement in global mobility network 基于身份验证和会话密钥协议的全球移动网络新型增强安全匿名通信

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234490

Prasanta Kumar Roy, Krittibas Parai, Sathi Ball, B. Kumar

{"title":"A new enhanced secure anonymous communication with authentication and session key agreement in global mobility network","authors":"Prasanta Kumar Roy, Krittibas Parai, Sathi Ball, B. Kumar","doi":"10.1109/ICRCICN.2017.8234490","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234490","url":null,"abstract":"Recently, several protocols have been proposed to accomplish user authenticity with proper session key establishment in Global Mobility Network. Unfortunately, some of them still suffer from various security threats and high computational complexity. This article demonstrates a new enhanced two-factor authentication scheme for secure anonymous communication to mutually authenticate the communicating parties and to establish a proper session key between them. The major contributions of this article are 1) to achieve all kind of security goals and 2) to effectively reduce the computational complexity. The underlying construction is developed using Elliptic Curve Cryptography (ECC) along with light-weight processes to ensure the resistibility against well-known security threats and improved computational complexity. The protocol is implemented using HLPSL and formally validated using AVISPA to ensure that it has the ability to withstand several attacks. We have also compared the computational complexity of our protocol with some existing protocols to prove its efficiency.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116243035","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: 4

EEG analysis for working memory modeling in face recognition task 人脸识别任务中工作记忆建模的脑电分析

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234477

Lidia Ghosh, Sricheta Parui, P. Rakshit, A. Konar

{"title":"EEG analysis for working memory modeling in face recognition task","authors":"Lidia Ghosh, Sricheta Parui, P. Rakshit, A. Konar","doi":"10.1109/ICRCICN.2017.8234477","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234477","url":null,"abstract":"The paper proposes a new approach to mode human working memory using EEG-induced fuzzy associativi memory and attempts to recover the encoded memor information from partially supplied instances during memor recall tasks. Experiments are performed to obtain EEG feature from the temporal lobe, representing working memory input an(pre-frontal lobe, representing the working memory outpu during memory encoding process of unknown peoples' face. Thi fuzzy associative memory is built up with these input-outpu features of the working memory, acquired for multiple instances During the recall cycle, we use a notion of fuzzy inversi formulation to recall the input EEG instances from the supplie output instances of the working memory using fuzzy associativ memory, when the subject is asked to remember the original faci from its part, and to our great surprise the model produced inpu instances match with actual brain-generated input instances wit small error. This signifies the importance of the propose(working memory model and inverse formulation in memor retrieval process. Experiments undertaken reveal that the erro metric could successfully be used to diagnose two peopl suffering from Parkinson and three from the early Alzheimer' diseases among a total population of 50 healthy plus 5 brain diseased people.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125749268","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: 8

Recurrent convolution neural networks for classification of protein-protein interaction articles from biomedical literature 用于生物医学文献中蛋白质-蛋白质相互作用文章分类的递归卷积神经网络

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234505

Sabenabanu Abdulkadhar, Gurusamy Murugesan, J. Natarajan

{"title":"Recurrent convolution neural networks for classification of protein-protein interaction articles from biomedical literature","authors":"Sabenabanu Abdulkadhar, Gurusamy Murugesan, J. Natarajan","doi":"10.1109/ICRCICN.2017.8234505","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234505","url":null,"abstract":"Text classification (TC) is a task that assigns a text to one or more classes and predefined categories. Constructing text classifiers with high accuracy is a vital task in biomedical field, given the wealth of information hidden in unlabelled documents. Because of large feature spaces, traditionally discriminative approaches, such as logistic regression and support vector machines with n-gram and semantic features have been utilizedfor biomedical text classification. In this study, we propose Recurrent Convolution Neural Networks (RCNN) based automated technique for classifying protein-protein interaction (PPI) articles. In RCNN model we utilized a recurrent structure to detain the contextual information from word embedding features. Max pooling layer was configured to extract important semantic keywords from the text. We evaluated our approach on two benchmark PPI datasets BioCreative II and BioCreative III. An experimental results show that RCNN based protein-protein interaction classification approach performs better than other state of the art approaches.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"37 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128162378","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: 4

Performance evaluation of web browsers in iOS platform iOS平台下web浏览器的性能评估

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234484

S. Roshan, S. V. Kumar, Manish Kumar

引用次数: 0

PSO and DE based novel quantum inspired automatic clustering techniques 基于PSO和DE的新型量子启发自动聚类技术

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234522

Sandip Dey, S. Bhattacharyya, V. Snás̃el, Alokananda Dey, Satabdwi Sarkar

{"title":"PSO and DE based novel quantum inspired automatic clustering techniques","authors":"Sandip Dey, S. Bhattacharyya, V. Snás̃el, Alokananda Dey, Satabdwi Sarkar","doi":"10.1109/ICRCICN.2017.8234522","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234522","url":null,"abstract":"Clustering, a well-known technique, is used to divide a data set into number of groups, called clusters. Differential evolution and particle swarm optimization are robust, fast and very effective search techniques. To increase computational capability, two different quantum inspired meta-heuristics for automatic clustering, have been proposed here. An application of quantum inspired techniques has been demonstrated for automatic clustering of image data sets. These techniques are able to find optimal number of clusters “on the run” for an image data sets. As the comparative research, a comparison has been made between the proposed techniques and their conventional counterparts for four images data set. Effectiveness of the proposed techniques has been exhibited against the fitness value, standard deviation and mean of the fitness, standard error and computational time. Finally, two separate statistical superiority test, referred to as i-test and Friedman test have been performed to prove the superiority the of proposed approaches in their favor.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814609","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

Volunteer GIS (VGIS) based waste management: A conceptual design and use of web 2.0 for smart waste management in Dhaka City 基于志愿者地理信息系统(VGIS)的废物管理:达卡市智能废物管理的web 2.0概念设计和使用

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234495

S. Labib

{"title":"Volunteer GIS (VGIS) based waste management: A conceptual design and use of web 2.0 for smart waste management in Dhaka City","authors":"S. Labib","doi":"10.1109/ICRCICN.2017.8234495","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234495","url":null,"abstract":"This Waste management is a major issue for rapidly growing megacities in developing countries. Unorganized and poor management system leads towards negative environmental impact, and lowering livability of these cities. How-ever, there are scope for integrating general people in the waste management to improve overall performance. In such context, the aim of this study is to develop and detail, a volunteer GIS based smart waste management system for Dhaka city; in order to ensure active participation of the citizens in resolving poor solid waste management conditions. The study concentrated in developing a Geoweb (Web 2.0) design for collecting waste related problems from the citizens. VGIS concept is developed using web-server and VGIS interface, with JavaScript and Google Maps APIs. The developed Geo-web would allow to report waste related problems (e.g., Illegal waste dumping) by the citizens using geo-tagged marker over a customized Google Map. Additionally, the website would also be used to disseminate waste collection schedule, contact information of the waste collectors for different wards in the city. The system would provide a common platform for citizens' active participation in waste management, and also help bridge the gap between citizens and local government, thus would open opportunities for active e-governance. Successful implementation of the system can help reducing solid waste management problems and create awareness among the citizens regarding waste management and use of internet in improving their surroundings.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964715","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: 18

Reduction of harmonics at output of three-phase VSI using PSO based PWM technique 基于PSO的PWM技术降低三相VSI输出谐波

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234489

A. Sadhukhan, S. Ganguly, P. Gayen

引用次数: 0

Medium scale multi-constraint economic load dispatch using hybrid metaheuristics 基于混合元启发式的中等规模多约束经济负荷调度

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234501

D. Santra, A. Mukherjee, K. Sarker, S. Mondal

引用次数: 1

Design and implementation of a two-layered hybrid cryptosystem 两层混合密码系统的设计与实现

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234529

Sarbajit Manna, Mohit Prajapati, A. Sett, K. Banerjee, S. Dutta

引用次数: 1

Analysis of de-noising techniques of non-stationary ECG signal based on wavelet and PSO optimized parameters for Savitzky golay filter 基于小波和粒子群优化参数的非平稳心电信号去噪技术分析

2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2017-11-01 DOI: 10.1109/ICRCICN.2017.8234478

Ashis Kumar Das, D. Biswas, S. Halder

{"title":"Analysis of de-noising techniques of non-stationary ECG signal based on wavelet and PSO optimized parameters for Savitzky golay filter","authors":"Ashis Kumar Das, D. Biswas, S. Halder","doi":"10.1109/ICRCICN.2017.8234478","DOIUrl":"https://doi.org/10.1109/ICRCICN.2017.8234478","url":null,"abstract":"The bioelectric signals originate from different organs of human body. Out of these ECG is one of the important bioelectric signals for our concern and for investigation of various heart ailments. ECG demonstrates graphical rendition of activity of the heart and by analyzing the ECG signal several heart diseases can be identified. For analysis of ECG signal, it must be noise free. There are several techniques for filtering out the noise from ECG signal. It is imperative to find out a best possible method for ECG Signal de-noising, which may be investigated by finding and comparing the signal-to-signal-plus-noise ratios (SSNR) and root-mean-square deviations (RMSD). By considering a mother wavelet with different levels and threshold, the values of SSNR and RMSD are calculated and compared to achieve a best possible result. Similarly, by utilizing different frame lengths and polynomial orders, the S-G filter is employed to find SSNR and RMSD. The results of these methods are also compared. Finally, the orders and frame lengths of S-G filters can be obtained by optimizing with the help of particle swarm optimization (PSO) technique.","PeriodicalId":166298,"journal":{"name":"2017 Third International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124833237","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: 5