International Conference on Network, Communication and Computing最新文献_第6页

Artificial Neural Networks Based Emotion Classification System through Relative Wavelet Energy of EEG Signal 基于脑电信号相对小波能量的人工神经网络情绪分类系统

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033298

Prima Dewi Purnamasari, A. A. P. Ratna, B. Kusumoputro

{"title":"Artificial Neural Networks Based Emotion Classification System through Relative Wavelet Energy of EEG Signal","authors":"Prima Dewi Purnamasari, A. A. P. Ratna, B. Kusumoputro","doi":"10.1145/3033288.3033298","DOIUrl":"https://doi.org/10.1145/3033288.3033298","url":null,"abstract":"Emotion classification from EEG brain signal has been a widely research topic recently, because of the complexity of processing the multi channels of the brain signal and also the problem on mapping the human emotion itself. This paper discusses the technique to determine the emotion classification from EEG brain signal using a relative wavelet energy (RWE) as a feature vector and an artificial neural networks (ANN) as a classifier. In this research, two types of ANN classifier was utilized and analyzed, namely, Back-propagation Neural Networks (BPNN) and Probabilistic Neural Networks (PNN). Also reducing the number of the EEG channel to be processed is investigated, in order to decrease the computational cost of the classification system. Results showed that the recognition rate of the reduced utilized channels up to 4 channel are incomparable with that of the full utilization of 32 channels. However, 8 and 14 channels still produced sufficient recognition rate. It is also confirmed from experiments that the BPNN shown as a more reliable classifier compare with the PNN method.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125028587","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

An Asynchronous Message-passing Distributed Algorithm for the Generalized Local Critical Section Problem 广义局部临界截面问题的异步消息传递分布式算法

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033341

S. Kamei, H. Kakugawa

引用次数: 5

Design of Cameras Gateway for Remote Monitoring and Human Tracking 用于远程监控和人员跟踪的摄像机网关设计

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033337

Kuei-Chung Chang, P. Liu, H. H. Lin

引用次数: 0

Feasibility Analysis of SCMA in Logging Cable Telemetry Systems with an Optimal 16-point Codebook 基于最优16点码本的SCMA测井电缆遥测系统可行性分析

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033289

Qian Cui, K. Shuang

引用次数: 1

An Architecture of an Academic Search Engine with Personalized Search Result Ranking Mechanism 具有个性化搜索结果排序机制的学术搜索引擎体系结构

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033314

W. Choochaiwattana

{"title":"An Architecture of an Academic Search Engine with Personalized Search Result Ranking Mechanism","authors":"W. Choochaiwattana","doi":"10.1145/3033288.3033314","DOIUrl":"https://doi.org/10.1145/3033288.3033314","url":null,"abstract":"A rapid increasing of information on the Internet and World Wide Web causes information overloaded problem. Thus, search engines become important tools to help WWW users to discover the information they need. With an exponentially increasing of published research paper, community-based research paper sharing systems and academic search engines become indispensable tools for researchers to search for any research papers in their fields of expertise and related fields according to their interests. To improve a quality of research paper searching, an academic search engines' capability should be enhanced. This paper proposed an architecture of an academic search engine with personalized search result ranking mechanism. To evaluate the performance of personalized search result ranking mechanism, twenty-five graduate students were invited to be participants in this research study. As a criterion, the participants were asked to use a prototype of academic search engine to find and bookmark any research papers according to their interests. This would guarantee that each participants' list of interesting research paper could be recorded. The Normalized Discounted Cumulative Gain (NDCG) was used as a metric to determine that performance of personalized search result ranking mechanism. During the experiment, each participant was asked to search for research papers according to their interests. The result of the experiment suggested that the personalized search result ranking mechanism outperformed the original search result ranking. Hence, the proposed architecture of the academic search engine with personalized search engine mechanism does benefit a tasks of research paper discovery. It improves the quality of research paper searching.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128087185","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

OFDM Channel Estimation Based on Fast Approximated Power Iteration Subspace Tracking 基于快速近似功率迭代子空间跟踪的OFDM信道估计

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033321

Qingyun Fang, Yubing Han, Xuan Chen, Kai Qi, Mengyao Qi, Yi Zhang

引用次数: 0

Prototype Selection for k-Nearest Neighbors Classification Using Geometric Median 基于几何中值的k近邻分类原型选择

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033301

Chatchai Kasemtaweechok, W. Suwannik

{"title":"Prototype Selection for k-Nearest Neighbors Classification Using Geometric Median","authors":"Chatchai Kasemtaweechok, W. Suwannik","doi":"10.1145/3033288.3033301","DOIUrl":"https://doi.org/10.1145/3033288.3033301","url":null,"abstract":"The k-Nearest Neighbors classifier (kNN) is a well-known classifier implemented extensively in the data mining research area. The kNN classifier suffers from several drawbacks such as high storage requirements, computational complexity and high sensitivity to noise. Prototype selection is a promising solution for this problem as it reduces the number of data instances. This study proposes Geometric Median Prototype Selection (GMPS) algorithm which is a new efficient method of prototype selection based on the Geometric Median (GM). A set of GMs are selected as the relevant prototypes of the dataset. The selected prototypes form a training set for building a kNN classifier. After creating the classifier, it is tested on a testing set. The performance is measured in terms of accuracy, kappa and processing time and compared with seven state-of-the-art methods on nine standard datasets. The result shows that GMPS methods provide better performance in accuracy, kappa than all considered PS methods while proposed methods are at least 3.5 times faster than other PS methods and 5.5 times faster than 1NN baseline model. However, the proposed classifiers lost to the baseline classifier about 2 percent of accuracy rate and 0.05 of Cohen's kappa statistics.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130653546","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

Acoustic Modeling for Lhasa Tibetan Speech Synthesis Based on DAEM Algorithm 基于DAEM算法的拉萨藏语语音合成声学建模

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033329

Shipeng Xu, Hongzhi Yu, Guanyu Li, Hanbing Zhang, Jun Ma

引用次数: 0

Monitoring and Controlling Method of the Environment Condition in the Animal Breeding Farm by Using Smart Phone 基于智能手机的动物养殖场环境状况监测与控制方法

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033322

M. Chung, Chong-Seong Hong

引用次数: 1

Exploit Kit Website Detection Using HTTP Proxy Logs 利用HTTP代理日志进行网站检测

International Conference on Network, Communication and Computing Pub Date : 2016-12-17 DOI: 10.1145/3033288.3033354

Ivan Nikolaev, Martin Grill, Veronica Valeros

{"title":"Exploit Kit Website Detection Using HTTP Proxy Logs","authors":"Ivan Nikolaev, Martin Grill, Veronica Valeros","doi":"10.1145/3033288.3033354","DOIUrl":"https://doi.org/10.1145/3033288.3033354","url":null,"abstract":"Exploit kits are software toolkits that are used for widespread malware distribution via automated infection of victims' computers through Internet web pages. They are extremely hard to detect as they constantly evolve by frequently changing the hosted domains and URL patterns which draws any signature-based detection ineffective.\u0000 In this paper we analyse common exploit kit characteristics and propose a detection method that relies solely on the information extracted from HTTP proxy logs that are commonly available in most enterprise networks. Our method leverages exploit kit characteristics that are common across different exploit kit families and are unlikely to change as they are crucial for the exploitation process.\u0000 We perform two sets of experiments to evaluate the efficacy of the proposed method. The first set uses network traces of a number of publicly available malicious samples to estimate recall of the proposed method. Second set of experiments uses real network traffic collected in large number of corporate networks to estimate the precision. Both sets of experiments show satisfying performance of the algorithm.","PeriodicalId":253625,"journal":{"name":"International Conference on Network, Communication and Computing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115749975","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: 7