2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)最新文献_第4页

An alternative solution of skyline operation to reduce computational complexity 一种降低计算复杂度的天际线运算替代方案

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813676

P. Ghosh, S. Sen

{"title":"An alternative solution of skyline operation to reduce computational complexity","authors":"P. Ghosh, S. Sen","doi":"10.1109/ICRCICN.2016.7813676","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813676","url":null,"abstract":"Single-criteria decision making queries can be answered using simple SQL queries, however a multi-criteria decision making problems are often not answered by normal SQL queries. In order to solve these types of queries we may need to use co-operative query languages etc. However using additional query based system incurs extra cost. Moreover, if the criteria in a query are complementary to each other simple SQL queries are not capable of addressing this issue. A query in which multi-criteria decision making is required, often more than a single attribute of the relation is analyzed to fetch the desired result. In this context dominance analysis is performed to obtain a set of points (tuples) those are at least equally good in all the dimensions in compare to other points in the dataset. Skyline points are computed to find points which are not dominated (dominance analysis) by any other point in the system. A point is called “skyline point” if and only if it is not dominated by any other points in the system. Computation of skyline requires comparison of each point to all the other points in the system which in turn increases complexity. The complexity may increase at exponential rate when the numbers of dimensions increase. This research work focuses on the reduction of computational complexity. It is incorporated here by selecting the most important dimension of the database and transfers the other entire dimension in that form. And finally ranks the points accordingly.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130358325","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

Implementation of a spatial domain salient region based digital image watermarking scheme 一种基于空域显著域的数字图像水印方案的实现

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813669

A. Basu, S. Roy, A. Chattopadhyay

引用次数: 12

Secure data transfer in IoT environment: Adopting both cryptography and steganography techniques 物联网环境下的安全数据传输:采用加密和隐写技术

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813674

Ria Das, Indrajit Das

{"title":"Secure data transfer in IoT environment: Adopting both cryptography and steganography techniques","authors":"Ria Das, Indrajit Das","doi":"10.1109/ICRCICN.2016.7813674","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813674","url":null,"abstract":"Owing to the unprecedented growth in computing power, electronics miniaturization and mobile and wireless network interconnections the internet has metamorphosed into Internet of Things (IoT) which refers to next stage of the information revolution whose context involves billions of individuals and devices interconnected to facilitate exchange of huge volume of data and information from diverse locations, demanding the consequent necessity for smart data aggregation followed by an increased obligation to index, hoard and process data with higher efficiency and effectiveness. But along with its myriad offered benefits and applications, emerges a novel complexity aspect in terms of many inherent hassles primarily security concerns during data transfer phases in IoT covering mostly data confidentiality and integrity features. Thus to enhance safe data transfer in smart IoT environment, a security scheme is proposed in this paper which addresses both the aforesaid issues, employing an integrated approach of lightweight cryptography and steganography (Simple LSB Substitution) technique during data transfer between IoT device and Home Server and adoption of combined approach of cryptography and steganography (Proposed MSB-LSB Substitution) technique during data transfer phases between Home Server and Cloud Servers.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115115529","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: 22

Alternate simplistic approach to solve count-to-infinity problem by introducing a new flag in the routing table 通过在路由表中引入一个新标志来解决计数到无穷大问题的另一种简单方法

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813673

Parth Mannan, T. Jayavignesh

引用次数: 2

Cluster analysis for overlapping clusters using genetic algorithm 基于遗传算法的重叠聚类分析

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813542

Sunanda Das, S. Chaudhuri, A. Das

{"title":"Cluster analysis for overlapping clusters using genetic algorithm","authors":"Sunanda Das, S. Chaudhuri, A. Das","doi":"10.1109/ICRCICN.2016.7813542","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813542","url":null,"abstract":"Cluster analysis is an important task almost in all fields including bioinformatics, social networks, agriculture, and so on. It basically explores the natural structure of the data without any prior knowledge about it. In many real data sets, the objects reside in many clusters with different membership values. Many clustering algorithms have been proposed for finding such overlapping clusters to analyze high volume of data. In the paper, genetic algorithm based cluster analysis technique is proposed for finding the optimal set of overlapping clusters. The usefulness of applying the genetic algorithm based optimization technique is to assign a membership value only to the objects which are the members of several clusters, instead of assigning membership values for all clusters like fuzzy clustering algorithm. If any object positively belongs to a cluster, its membership value for this cluster is `1' and `0' for all other clusters. The overall performance of the method is investigated on some popular UCI data sets and the optimality of the clusters is measured by related cluster validation indices. The experimental results show the effectiveness of the proposed method.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114568312","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

An approach to enhance performance of Kaiser window based filter 一种提高Kaiser窗滤波器性能的方法

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813666

P. Das, S. Naskar, S. N. Patra

{"title":"An approach to enhance performance of Kaiser window based filter","authors":"P. Das, S. Naskar, S. N. Patra","doi":"10.1109/ICRCICN.2016.7813666","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813666","url":null,"abstract":"At the time of transmission via any media, signals get affected by unwanted components; which are adverse but inevitable. Elimination of such unwanted components termed as noise from transmitted signals has remained an important as well as puzzling task for the researchers since the preliminary days of Digital Signal Processing. Among a significant number of techniques proposed for removal of noise from signals, use of digital filters has become most effective in multiple ways. Slighter overheads in designing and lower hardware cost have made the Finite Impulse Response (FIR) filters popular. Among a considerable number of techniques, use of different window functions for implementation of digital filters is most acceptable. In this paper a new strategy based on the weight lifting strategy of ants has been proposed for optimizing parameters to design a digital filter using Kaiser Window function. A new innovative objective function has been introduced for optimization that performs based on the signal de-noising capability of the filters implemented by the optimized sets of parameters. A case study was carried out on heart sound signals with a filter designed using Kaiser Window with optimized parameters.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129717964","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

Real-time hand tracking using integrated optical flow and CAMshift algorithm 采用集成光流和CAMshift算法的实时手部跟踪

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813645

Utkarsh Soni, Aditya Trivedi, Nirmal Roberts

引用次数: 3

Performance analysis of different autoregressive methods for spectrum estimation along with their real time implementations 各种自回归谱估计方法的性能分析及其实时实现

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813646

D. Chakraborty, S. Sanyal

{"title":"Performance analysis of different autoregressive methods for spectrum estimation along with their real time implementations","authors":"D. Chakraborty, S. Sanyal","doi":"10.1109/ICRCICN.2016.7813646","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813646","url":null,"abstract":"Recently Spectrum estimation has become an interesting topic for the researchers. Non-parametric methods generally do not have any knowledge about the process being observed. They also suffer from serious drawbacks like sidelobe leakages and unrealistic windowing methods. The second approach being known as parametric method overcomes these shortcomings. In parametric approach initially a suitable model is selected based on apriori knowledge about how the process is generated and then followed by estimating the parameters from the observed data. After calculation of parameters the power spectrum is estimated. In this paper we have studied thoroughly the Autoregressive method of spectrum estimation. We perform both simulation as well as real time implementations on FPGA based radio prototype board known as Wireless Open Access Research Platform (WARP) of RICE University. Various algorithms like Yule-Walker, Burg, Covariance and Modified Covariance have been studied with real time estimation of the statistical parameters by which they are described in AR technique.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132458419","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: 6

Integration of time series models with soft clustering to enhance network traffic forecasting 将时间序列模型与软聚类相结合，增强网络流量预测能力

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813658

Theyazn H. H. Aldhyani, Manish Joshi

{"title":"Integration of time series models with soft clustering to enhance network traffic forecasting","authors":"Theyazn H. H. Aldhyani, Manish Joshi","doi":"10.1109/ICRCICN.2016.7813658","DOIUrl":"https://doi.org/10.1109/ICRCICN.2016.7813658","url":null,"abstract":"The network traffic forecasting is of significant interest in many domains such as bandwidth allocation, congestion control and network management. Hence, forecasting of network traffic has received attention from the computer networks field for achieving guaranteed Quality of Service (QoS) in network. In this paper, we propose a forecasting model that combines conventional time series models with clustering approaches. The conventional linear and non linear time series models namely Weighted Exponential Smoothing (WES), Holt-Trend Exponential Smoothing (HTES), AutoRegressive Moving Average (ARMA), Hybrid model (Wavelet with WES) and AutoRegrssive Neural Network (NARNET) models are applied for forecasting network traffic. Our novelty is application of soft clustering for enhancing the existing time series models that are used to forecast network traffic. Clustering can model network traffic data and its characteristics. We derived a methodology to appropriately use cluster centriods to enhance the results obtained by conventional approach. We experimented with different soft clustering techniques such as Fuzzy C-Means (FCM) and Rough K-Means (RKM) clustering to verify the improvement in forecasting. The results of our integrated model are validated using Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) performance measures. The results show that the integrated model enhances the results obtained using conventional time series forecasting models.","PeriodicalId":254393,"journal":{"name":"2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126746385","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: 11

Multi objective fractional programming by genetic algorithm 遗传算法的多目标分式规划

2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN) Pub Date : 2016-09-01 DOI: 10.1109/ICRCICN.2016.7813644

D. Roy, R. Dasgupta

引用次数: 1