2015 Fifth International Conference on Communication Systems and Network Technologies最新文献

Gesture Recognition Based on Fusion Features from Multiple Spiking Neural Networks 基于多脉冲神经网络融合特征的手势识别

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.214

Liuping Huang, Qingxiang Wu, Yanfeng Chen, SanLiang Hong, Xi Huang

引用次数: 4

Performance Analysis for Android Runtime Environment Android运行环境的性能分析

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.52

Radhakishan Yadav, R. S. Bhadoria

引用次数: 18

A Step toward Speeding Up Cross-Cut Shredded Document Reconstruction 加速横切粉碎文件重建的一步

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.69

A. S. Atallah, E. Emary, M. El-Mahallawy

引用次数: 5

A Compact Frequency Selective Surface Based Band-Stop Filter for WLAN Applications 一种用于WLAN应用的紧凑型频率选择表面带阻滤波器

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.116

Kiran Aseri, S. Yadav, M. Sharma

引用次数: 10

Planar Coupled-Fed Monopole Antenna for Nine-Band LTE/WWAN/GPS Mobile Handset Application 面向九波段LTE/WWAN/GPS手机应用的平面耦合馈电单极天线

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.282

Lindsey Chou, Chia-Hao Ku

引用次数: 1

Performance Analysis of Color Space for Optimum Skin Color Detection 最佳肤色检测的色彩空间性能分析

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.88

Amit Kumar, Shivani Malhotra

引用次数: 4

A Quantum Parallel Self Organizing Neural Network (QPSONN) for Pure Color Object Extraction from a Noisy Background 基于量子并行自组织神经网络(QPSONN)的噪声背景下纯彩色目标提取

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.55

S. Bhattacharyya, Pankaj Pal, Sandip Bhowmick

{"title":"A Quantum Parallel Self Organizing Neural Network (QPSONN) for Pure Color Object Extraction from a Noisy Background","authors":"S. Bhattacharyya, Pankaj Pal, Sandip Bhowmick","doi":"10.1109/CSNT.2015.55","DOIUrl":"https://doi.org/10.1109/CSNT.2015.55","url":null,"abstract":"In this article, a quantum version of the parallel self organizing neural network (QPSONN) architecture for extraction of pure color objects from a noisy perspective is proposed. The QPSONN architecture operates in a phased manner to process input noisy pure color images. After the segregation of the pure color inputs into pure color components in the initial phase, these components are subsequently forwarded for processing to three component quantum multilayer self organizing neural network (QMLSONN) architectures composed of three processing layers viz., input, hidden and output layers characterized by qubits based neurons. The interconnection weights are represented by single qub it rotation gates. Quantum measurements at the component output layers destroy the quantum states of the processed information facilitating adjustment of network interconnection weights by a quantum back propagation algorithm using linear indices of fuzziness. Finally, a fusion of the stable component outputs are brought about in a sink layer to produce extracted outputs. Results of application of the QPSONN are demonstrated on a synthetic and a real life spanner image with various degrees of Gaussian noise. A comparison with the classical PSONN architecture reveals the extraction and time efficiency of the proposed QPSONN architecture.","PeriodicalId":334733,"journal":{"name":"2015 Fifth International Conference on Communication Systems and Network Technologies","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126609354","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

Implementation of Dynamic Association Rule Mining Using Back Navigation Approach 利用反向导航方法实现动态关联规则挖掘

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.272

S. Huria, Jaiteg Singh

{"title":"Implementation of Dynamic Association Rule Mining Using Back Navigation Approach","authors":"S. Huria, Jaiteg Singh","doi":"10.1109/CSNT.2015.272","DOIUrl":"https://doi.org/10.1109/CSNT.2015.272","url":null,"abstract":"ARM (Association Rule Mining), one of the most frequently used technique in the domain of data mining and machine learning. Using association rule mining or rule learning extracts the hidden patterns in terms of the association between entities of the training data set. This technique is applied on number of data sets by different researchers and academicians, still this area is under research as the domain and data sets increase very frequently. Association rule learning is a mainstream and generally inquired about system for finding intriguing relations between variables in expansive databases. It is proposed to distinguish solid rules found in databases utilizing distinctive measures of interestingness. Based on the idea of solid rules, Rakesh Agrawal et al. presented association rules for finding regularities between items in expansive scale exchange information recorded by purpose of-offer (POS) frameworks in markets. The data set can be utilized as the premise for choices about promoting exercises, for example, e.g., limited time estimating or item positions. Notwithstanding the above illustration from business crate investigation association rules are utilized today in numerous application regions including Web utilization mining, interruption recognition, Continuous generation, and bioinformatics. This manuscript highlight and implements a novel approach for association rule mining using back navigation and is implemented on the unique dataset.","PeriodicalId":334733,"journal":{"name":"2015 Fifth International Conference on Communication Systems and Network Technologies","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117199273","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

Large File Transmission Using Self-Adaptive Data Fragmentation in Opportunistic Networks 机会网络中基于自适应数据碎片的大文件传输

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.273

Long Feng, Yong Zhang, Hongjun Li

引用次数: 9

Fingerprint Segmentation Using Scale Vector Algorithm 基于尺度矢量算法的指纹分割

2015 Fifth International Conference on Communication Systems and Network Technologies Pub Date : 2015-10-01 DOI: 10.1109/CSNT.2015.137

Rohan Nimkar, A. Mishra

引用次数: 4